{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Vegetarian Classifier\n", "\n", "### Problem statement: Can we develop a classifier that can label someone as vegetarian or not?\n", "\n", "### Data: Instacart's 3 million orders dataset, from Kaggle. https://www.kaggle.com/c/instacart-market-basket-analysis/data. The data does not label shoppers as vegetarian or not, so we'll have to label the data ourselves. We'll assume that if someone has purchased meat, then they are _not_ a vegetarian. (Of course, this is a huge assumption- someone who eats meat could easily buy their meat from a store that isn't included in this dataset).\n", "\n", "### Implication of labelling data ourselves: We will have to exclude any meat purchases from our training data. If we didn't, then the classifier would learn to use only those purchases to label our shoppers as vegetarian or not. But this works well- we'll end up finding information in the data _other than_ explicit meat purchases (or absence of them) that imply that someone is vegetarian." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Imports, garbage collection" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import gc\n", "import pandas as pd\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import warnings\n", "from IPython.core.interactiveshell import InteractiveShell\n", "%matplotlib inline\n", "InteractiveShell.ast_node_interactivity = \"all\"\n", "colour = sns.color_palette()\n", "warnings.filterwarnings('ignore')\n", "gc.collect()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Read in Instacart data" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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order_iduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order
125393291prior1208
223987951prior230715.0
34737471prior331221.0
422547361prior440729.0
54315341prior541528.0
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" ], "text/plain": [ " order_id user_id eval_set order_number order_dow order_hour_of_day \\\n", "1 2539329 1 prior 1 2 08 \n", "2 2398795 1 prior 2 3 07 \n", "3 473747 1 prior 3 3 12 \n", "4 2254736 1 prior 4 4 07 \n", "5 431534 1 prior 5 4 15 \n", "\n", " days_since_prior_order \n", "1 \n", "2 15.0 \n", "3 21.0 \n", "4 29.0 \n", "5 28.0 " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/html": [ "
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product_idproduct_nameaisle_iddepartment_id
11Chocolate Sandwich Cookies6119
22All-Seasons Salt10413
33Robust Golden Unsweetened Oolong Tea947
44Smart Ones Classic Favorites Mini Rigatoni Wit...381
55Green Chile Anytime Sauce513
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" ], "text/plain": [ " product_id product_name aisle_id \\\n", "1 1 Chocolate Sandwich Cookies 61 \n", "2 2 All-Seasons Salt 104 \n", "3 3 Robust Golden Unsweetened Oolong Tea 94 \n", "4 4 Smart Ones Classic Favorites Mini Rigatoni Wit... 38 \n", "5 5 Green Chile Anytime Sauce 5 \n", "\n", " department_id \n", "1 19 \n", "2 13 \n", "3 7 \n", "4 1 \n", "5 13 " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/html": [ "
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order_idproduct_idadd_to_cart_orderreordered
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" ], "text/plain": [ " order_id product_id add_to_cart_order reordered\n", "1 1 49302 1 1\n", "2 1 11109 2 1\n", "3 1 10246 3 0\n", "4 1 49683 4 0\n", "5 1 43633 5 1" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/html": [ "
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order_idproduct_idadd_to_cart_orderreordered
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" ], "text/plain": [ " order_id product_id add_to_cart_order reordered\n", "1 2 33120 1 1\n", "2 2 28985 2 1\n", "3 2 9327 3 0\n", "4 2 45918 4 1\n", "5 2 30035 5 0" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "### Define column names, and column datatypes. ###\n", "prod_cols = ['product_id','product_name','aisle_id','department_id']\n", "prod_dtypes= {'product_id':str,'product_name':str,'aisle_id':str,'department_id':str}\n", "order_cols = ['order_id','user_id','eval_set','order_number','order_dow',\n", " 'order_hour_of_day','days_since_prior_order']\n", "order_dtypes = {'order_id':str,'user_id':str,'eval_set':str,'order_number':str,\n", " 'order_dow':str,'order_hour_of_day':str,'days_since_prior_order':str}\n", "order_prods_cols = ['order_id','product_id','add_to_cart_order','reordered']\n", "order_prods_dtypes = {'order_id':str,'product_id':str,'add_to_cart_order':str,'reordered':str}\n", "department_names = [\"department_id\", \"department\"]\n", "department_dtypes = {\"department_id\":str, \"department\":str}\n", "aisle_names = [\"aisle_id\", \"aisle\"]\n", "aisle_dtypes = {\"aisle_id\":str, \"aisle\":str}\n", "\n", "### Paths to the various files ###\n", "prod_path = '/home/serena/workspace/Jupyter/Instacart/products.csv'\n", "order_path = '/home/serena/workspace/Jupyter/Instacart/orders.csv'\n", "order_prods_path = '/home/serena/workspace/Jupyter/Instacart/order_products__train.csv'\n", "order_prods_prior_path = '/home/serena/workspace/Jupyter/Instacart/order_products__prior.csv'\n", "department_path = '/home/serena/workspace/Jupyter/Instacart/departments/departments.csv'\n", "aisle_path = '/home/serena/workspace/Jupyter/Instacart/aisles/aisles.csv'\n", "\n", "### Read the files to dataframes ###\n", "prods = pd.read_csv(prod_path, names=prod_cols, dtype=prod_dtypes, na_filter=False)\n", "orders = pd.read_csv(order_path, names=order_cols, dtype=order_dtypes, na_filter=False)\n", "order_prods = pd.read_csv(order_prods_path, names=order_prods_cols, dtype=order_prods_dtypes, na_filter=False)\n", "order_prods_prior = pd.read_csv(order_prods_prior_path, names=order_prods_cols, dtype=order_prods_dtypes, na_filter=False)\n", "departments = pd.read_csv(department_path, names=department_names, dtype=department_dtypes)\n", "prods = prods.iloc[1:]\n", "orders = orders.iloc[1:]\n", "order_prods = order_prods.iloc[1:]\n", "order_prods_prior = order_prods_prior.iloc[1:]\n", "departments = departments.iloc[1:]\n", "# Combine order_prods and order_prods_prior\n", "# order_prods contains the most recent orders for a shopper\n", "# order_prods_prior contains earlier orders\n", "order_prods_all = pd.concat([order_prods, order_prods_prior], axis=0)\n", "\n", "### View the first rows of each file ###\n", "orders.head()\n", "prods.head()\n", "order_prods.head()\n", "order_prods_prior.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We want to identify shoppers who are vegetarian. The product information we get is product_id, product_name, aisle_id, and department_id. The first step is then to identify what meat-centric departments exist in the Instacart data. " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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department_iddepartment
11frozen
22other
33bakery
44produce
55alcohol
66international
77beverages
88pets
99dry goods pasta
1010bulk
1111personal care
1212meat seafood
1313pantry
1414breakfast
1515canned goods
1616dairy eggs
1717household
1818babies
1919snacks
2020deli
2121missing
\n", "
" ], "text/plain": [ " department_id department\n", "1 1 frozen\n", "2 2 other\n", "3 3 bakery\n", "4 4 produce\n", "5 5 alcohol\n", "6 6 international\n", "7 7 beverages\n", "8 8 pets\n", "9 9 dry goods pasta\n", "10 10 bulk\n", "11 11 personal care\n", "12 12 meat seafood\n", "13 13 pantry\n", "14 14 breakfast\n", "15 15 canned goods\n", "16 16 dairy eggs\n", "17 17 household\n", "18 18 babies\n", "19 19 snacks\n", "20 20 deli\n", "21 21 missing" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "### View the departments dataframe.###\n", "departments" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can identify department 12, \"meat seafood\" as the meat department. We'll assume that if shoppers have purchased from department 12, then they're not vegetarian. Shoppers who _have not_ purchased from department 12 will be assumed to be vegetarian." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The order_prods size is : (1384617, 4)\n", "The order_prods_prior size is : (32434489, 4)\n", "The order_products_all size is : (33819106, 4)\n" ] } ], "source": [ "### Size of the tables: (number of rows, number of columns) ###\n", "# E.g. order_prods has 1384618 rows, and 4 columns: order_id, product_id, add_to_cart_order, reordered\n", "print(\"The order_prods size is : \", order_prods.shape)\n", "print(\"The order_prods_prior size is : \", order_prods_prior.shape)\n", "print(\"The order_products_all size is : \", order_prods_all.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### This notebook is being run locally, so let's try to keep the size of the data small if we can. Let's use order_prods_prior since it has less orders than order_products_all, but still more than just a shopper's most recent orders (order_prods). Let's join the order_prods_prior and orders tables together, so that we get a shopper's history (order_prods_prior) along with specific order information (like day of week). We'll also need to join the prods table to these two, so that we can get department_id's and identify the shoppers who are vegetarian." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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order_idproduct_idadd_to_cart_orderreorderedproduct_nameaisle_iddepartment_iduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_order
023312011Organic Egg Whites8616202279prior35098.0
122898521Michigan Organic Kale834202279prior35098.0
22932730Garlic Powder10413202279prior35098.0
324591841Coconut Butter1913202279prior35098.0
423003550Natural Sweetener1713202279prior35098.0
\n", "
" ], "text/plain": [ " order_id product_id add_to_cart_order reordered product_name \\\n", "0 2 33120 1 1 Organic Egg Whites \n", "1 2 28985 2 1 Michigan Organic Kale \n", "2 2 9327 3 0 Garlic Powder \n", "3 2 45918 4 1 Coconut Butter \n", "4 2 30035 5 0 Natural Sweetener \n", "\n", " aisle_id department_id user_id eval_set order_number order_dow \\\n", "0 86 16 202279 prior 3 5 \n", "1 83 4 202279 prior 3 5 \n", "2 104 13 202279 prior 3 5 \n", "3 19 13 202279 prior 3 5 \n", "4 17 13 202279 prior 3 5 \n", "\n", " order_hour_of_day days_since_prior_order \n", "0 09 8.0 \n", "1 09 8.0 \n", "2 09 8.0 \n", "3 09 8.0 \n", "4 09 8.0 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "order_data = order_prods_prior.merge(prods, on = \"product_id\", how = \"left\")\n", "final_order_data = order_data.merge(orders, on = \"order_id\", how = \"left\")\n", "final_order_data.head()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "There are 113891 shoppers who have purchased meat or seafood.\n", "So there are 92318 shoppers who are vegetarian.\n", "As a reminder, there are 206209 shoppers in the database.\n" ] } ], "source": [ "### Count the number of vegetarians. ###\n", "# First look at \"not vegetarians\"- these are people who have purchased from the meat seafood category.\n", "not_vegetarians = list(final_order_data[final_order_data.department_id == \"12\"].user_id.unique())\n", "print(\"There are %s shoppers who have purchased meat or seafood.\" %len(not_vegetarians))\n", "print(\"So there are %s shoppers who are vegetarian.\" % (final_order_data.user_id.nunique()- len(not_vegetarians)))\n", "print(\"As a reminder, there are %s shoppers in the database.\" %final_order_data.user_id.nunique())" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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order_idproduct_idadd_to_cart_orderreorderedproduct_nameaisle_iddepartment_iduser_ideval_setorder_numberorder_doworder_hour_of_daydays_since_prior_orderveg
02331208.01Organic Egg Whites8616202279prior3598.01
12289858.01Michigan Organic Kale834202279prior3598.01
2293278.00Garlic Powder10413202279prior3598.01
32459188.01Coconut Butter1913202279prior3598.01
42300358.00Natural Sweetener1713202279prior3598.01
\n", "
" ], "text/plain": [ " order_id product_id add_to_cart_order reordered product_name \\\n", "0 2 33120 8.0 1 Organic Egg Whites \n", "1 2 28985 8.0 1 Michigan Organic Kale \n", "2 2 9327 8.0 0 Garlic Powder \n", "3 2 45918 8.0 1 Coconut Butter \n", "4 2 30035 8.0 0 Natural Sweetener \n", "\n", " aisle_id department_id user_id eval_set order_number order_dow \\\n", "0 86 16 202279 prior 3 5 \n", "1 83 4 202279 prior 3 5 \n", "2 104 13 202279 prior 3 5 \n", "3 19 13 202279 prior 3 5 \n", "4 17 13 202279 prior 3 5 \n", "\n", " order_hour_of_day days_since_prior_order veg \n", "0 9 8.0 1 \n", "1 9 8.0 1 \n", "2 9 8.0 1 \n", "3 9 8.0 1 \n", "4 9 8.0 1 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "### Create veg column. ###\n", "final_order_data[\"veg\"] = np.where(final_order_data[\"user_id\"].isin(not_vegetarians), 0, 1)\n", "### Convert values to numeric ##\n", "final_order_data[\"order_dow\"] = pd.to_numeric(final_order_data[\"order_dow\"])\n", "final_order_data[\"order_hour_of_day\"] = pd.to_numeric(final_order_data[\"order_hour_of_day\"])\n", "final_order_data[\"order_number\"] = pd.to_numeric(final_order_data[\"order_number\"])\n", "final_order_data[\"days_since_prior_order\"] = pd.to_numeric(final_order_data[\"days_since_prior_order\"])\n", "final_order_data[\"add_to_cart_order\"] = pd.to_numeric(final_order_data[\"days_since_prior_order\"])\n", "final_order_data[\"reordered\"] = pd.to_numeric(final_order_data[\"reordered\"])\n", "final_order_data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# EDA: Group specific features.\n", "\n", "## Let's do some exploratory data analysis to try to understand the differences between vegetarians vs non-vegetarians." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Number of purchases per day of week, per group." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def count_plot(data, col):\n", " f, axes = plt.subplots(2, 1, figsize=(16,12), sharex=True)\n", " plt.figure(figsize=(20,8))\n", " g1 = sns.countplot(x=col, data=data[data.veg==1], ax=axes[0])\n", " g1.set_title(\"vegetarian\")\n", " g2 = sns.countplot(x=col, data=data[data.veg==0], ax=axes[1])\n", " g2.set_title(\"not vegetarian\")\n", " plt.tight_layout()\n", " \n", "count_plot(final_order_data, \"order_dow\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### In the plots above, it's not entirely clear what day is which (Instacart didn't specify this in the Kaggle competition).\n", "\n", "#### You can see that there is a difference between vegetarians and non-vegetarians- vegetarians seem to shop mostly on day 1, which is unique to this group." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Histogram of order hour of day per group." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "count_plot(final_order_data, \"order_hour_of_day\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can see that there is a slight difference in behaviour of shoppers who are vegetarian vs those who are not. The vegetarian distribution has a spike in shopping in the morning, compared to all other shoppers.\n", "\n", "\n", "## Distribution of days since prior order of each group." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def count_plot_dist(data,col):\n", " f, axes = plt.subplots(2, 1, figsize=(14,14), sharex=True)\n", " plt.figure(figsize=(20,8))\n", " g1 = sns.countplot(x=col, data=data[data.veg==1], ax=axes[0])\n", " g1.set_title(\"vegetarian\")\n", " g1.set_xlabel('')\n", " g2 = sns.countplot(x=col, data=data[data.veg==0], ax=axes[1])\n", " g2.set_title(\"not vegetarian\")\n", " plt.tight_layout()\n", "\n", "count_plot_dist(final_order_data,\"days_since_prior_order\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### The number of days since a shopper's prior order shows a distribution with spikes at 7 days, 14 days, 21 days, and 30 days since a previous order, for both groups. That implies that people tend to shop weekly- so someone may choose to do their shopping on Sundays, while another shopper may choose to shop on Wednesdays. I assume the spike on the right hand side is because if any shopper has more than 30 days between orders, it's set to 30.\n", "\n", "#### If we focus on the \"not veg\" group vs the \"veg\" group, we see that there is a slight difference between the two.\n", "\n", "## Heat map of order hour of day vs order day of week- this lets us see the most frequent values." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Heatmap of day of week vs hour of day\n", "def dow_vs_hour(data):\n", " group=\"veg\"\n", " grouped_df0 = data[data[group]==0].groupby([\"order_dow\", \"order_hour_of_day\"])[\"order_number\"].aggregate(\"count\").reset_index()\n", " grouped_df0 = grouped_df0.pivot('order_dow', 'order_hour_of_day', 'order_number')\n", " grouped_df1 = data[data[group]==1].groupby([\"order_dow\", \"order_hour_of_day\"])[\"order_number\"].aggregate(\"count\").reset_index()\n", " grouped_df1 = grouped_df1.pivot('order_dow', 'order_hour_of_day', 'order_number') \n", " f, axes = plt.subplots(1, 2, figsize=(12,4), sharex=True)\n", " plt.figure(figsize=(16,8)) \n", " g0 = sns.heatmap(grouped_df0,ax=axes[0])\n", " g0.set_title(\"Frequency of Day of week Vs Hour of day: Not {}\".format(group))\n", " g1 = sns.heatmap(grouped_df1,ax=axes[1])\n", " g1.set_title(\"Frequency of Day of week Vs Hour of day: {}\".format(group))\n", " plt.tight_layout()\n", " plt.show()\n", " \n", "dow_vs_hour(final_order_data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### It seems that vegetarians show a high affinity for shopping around 9/10 am on Day 0 and 1." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### The results imply that order hour of day and order day of week are possible factors that can differentiate people in binary segments." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Purchase count per department, for each group." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def proportion_plot_both_groups(data):\n", " group=\"veg\"\n", " data = data[data.department!=\"meat seafood\"] \n", " x, y, hue = \"department\", \"purchase_proportion\", group\n", " hue_order = [group, \"not_{}\".format(group)]\n", " plt.figure(figsize=(10,6))\n", " (data[x]\n", " .groupby(data[hue])\n", " .value_counts(normalize=True)\n", " .rename(y)\n", " .reset_index()\n", " .pipe((sns.barplot, \"data\"), x=x, y=y, hue=hue))\n", " plt.xticks(rotation='45')\n", " l = plt.legend(loc=\"upper right\")\n", " l.set_title('Non-{group} (0) vs {group} (1)'.format(group=group))\n", "\n", "merged_data = final_order_data.merge(departments, on = \"department_id\")\n", "proportion_plot_both_groups(merged_data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Here we care about the distribution of the two groups relative to each other, rather than the actual purchase counts. If the distributions are different then we can assume that purchase count per department is a feature that differentiates the vegetarian and non-vegetarian groups. We can't really see much of a difference here- the distributions are a bit different but nothing huge- so that seems to imply that this feature may not be hugely important." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Reordering tendencies vegetarians vs non vegetarians.\n", "\n", "#### Department reorder ratio is the ratio of how many times a group reorders from a certain department, versus how often they do not reorder (reorder a new item). For example, a 0.55 department reorder ratio for vegetarians for department A would mean that 55% of a vegetarians' orders from department A are items they are reordering." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def reorders_plot_both_groups(data):\n", " group=\"veg\" \n", " data = data[data.department!=\"meat seafood\"] \n", " plot_title=\"Department wise reorder ratio: {group} vs Not {group}\".format(group=group)\n", " grouped_df = data.groupby([\"department\",group])[\"reordered\"].aggregate(\"mean\").reset_index()\n", " plt.figure(figsize=(10,6))\n", " sns.pointplot(grouped_df['department'].values, grouped_df['reordered'].values, \n", " alpha=0.8, color=colour[2], hue=grouped_df[group])\n", " plt.ylabel('Reorder ratio', fontsize=12)\n", " plt.xlabel('Department', fontsize=12)\n", " plt.title(plot_title, fontsize=15)\n", " plt.xticks(rotation='45')\n", " plt.show()\n", "\n", "reorders_plot_both_groups(merged_data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### It appears that vegetarians re-order bulk foods more than non-vegetarians. Department reorder ratio may be an important feature in differentiating vegetarians and non-vegetarians" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Reorder tendencies and day of week.\n", "\n", "#### Day of week reorder ratio is how often a group reorders items on a particular day of week, versus how much they do not reorder (order a new item)." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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ebtPTafbrd6vqbJr338U0F/n+R5p/sp5MczzZelV1bN82PZrkUOB84GtJdq+qGwYNfoL2CTTHy/1z+7isqh47NGA5Ps//AHw+yUk0PZu7AX/Qznt0jHVfApyc5K9p3m/70PSYroiP07y+X0ryLzS9W8fSfP5XhX+h2c8Xt6/3BjQnSvyI5kSXVeUcmsMkfklzQlOvcd9zVbU0yanA8Ukeojlr+M1tveUZFdHyqkk+C8NHtx6MchYfTRJxPcue3fYUmtPVb6bpDRmi6RnZrafOE4F/pxk+eYBmmHavvrYvBc4fJZ430fyQ3E/zX+kujHDmI82P4dU0X6Z30XxZ/0XP/M/Qc2mEcfbBiHVpvlA/TZOs3EkzrPc6Hn85kj9u99WDPHZ88IiXLRl334wS36E0CeVvaJKclzDCWZw0vQVXt/tuKc2lK7Ya63Vu5z2L5oy7e2gSqC+x7NnMr6P5z31J2/Z1NMnc8Fmlh9MMOd5JMzx2DfDWAbZr3NeaZsj5x+22X0Pzgzzi+4fmgO4Cfn/A132Q9+qo+22E9g5q1/9XPWUvactOH6H+8Iksw+u/iaZ3/Pk9ddaluQTLovb9dRvwVdrLobR1lnkvtMt8jWZIbctRYt2avrNcV8Xnd4x98912fe8YZf6Yn+e2zp/RfOfcR3PpnjcxztnpNN9jH6M59u1XNInR8GvSe4Zv0XOZlNFee5rP9TXtvplPk1jewWBnuQ7S/k40/8TdR/NP21nA0wd43T7D4N93G7btF/CcEeYP8p5bj2bo9pft6/Vv7fbcvTzvCx/L9xj+wpWk1Vrbi3cQsE01x/VpNZbkb2gudbNxNScnaAol+TqwdlWt6DGKGodDrpJWa2nurrA9zXDV8SZzq5/2ZJxjac5+vY/mrOGjgU+ZzE2+JHvS9HT+D7A2zT9Sr6K9+4wmxqSdFJFk7zS3V1mU5JgR5p+YZH77uD7J3T3zDktyQ/s4rKd85zS3y1mU5nY06W9X0hrvkzRDUxfRDP1o9fMgzbF8n6YZ/nsLzeEffz6VQa3B7qU5E/Y8msNuXkxzqMT5UxrVam5Shlzb601dT3MbkiGas4EOqaqFo9T/M2CnqnpLko1pjtOYTTOmfzWwc1XdleRK4H00xw1dBPxbVfVfGFWSJGm1Nlk9dLsCi6pqcTUXLp3D408x73UIzZl40NzX7pKqurOaU6ovAfZOshnNLVAuryYrPYPBrsckSZK0WpmsY+i2oDnzcdgQzfj647Snpm9DcybPaMtu0T6GRigfqc0jaG6UzJOe9KSdn/vc5y7/FkiSJE2yq6+++o6qGvfCzJOV0I10bNtoY70H05zyPnydptGWHbjNqjoFOAVg9uzZNW/eWJfdkiRJmh6S/HSQepM15DrEsvcWnEVz+5GRHMxvh1vHWnaIZW9cPFabkiRJq63JSuiuArZNsk2SdWiStrn9ldrLC2xEc7uXYRcDr0myUZKNgNfQXMz258A9SV7ant16KHDBRG+IJEnSdDMpQ65V9XCSI2mSsxk0V0VfkOQEmqtXDyd3hwBzqufU26q6M8mHaZJCgBOqaviGv++iuQL2+sBX2ockSdIaZY27U4TH0EmStOZ46KGHGBoa4v7775/qUMa03nrrMWvWLNZee+1lypNcXVWzx1veO0VIkqTV1tDQEBtuuCFbb7010/X+A1XF0qVLGRoaYptttlmhNibtThGSJEmT7f7772eTTTaZtskcQBI22WSTlepFNKGTJEmrtemczA1b2RhN6CRJkjrOhE6SJKnjTOgkSZI6zrNcJUmSehx99NFstdVWvPvd7wbguOOOY8MNN+TRRx/l3HPP5YEHHuANb3gDxx9/PAAf/vCHOfPMM9lyyy3ZdNNN2XnnnfnABz4wqTHbQydJktTj4IMP5pxzznls+txzz2XmzJnccMMNXHnllcyfP5+rr76ayy67jHnz5vFf//Vf/OAHP+Dzn/88U3WtW3voJEmSeuy0007cfvvt3HrrrSxZsoSNNtqIa665hq997WvstNNOANx7773ccMMN3HPPPey3336sv/76ALz+9a+fkphN6CRJkvoccMABnH/++dx2220cfPDB3HTTTRx77LG84x3vWKbeiSeeOEURLsshV0mSpD4HH3wwc+bM4fzzz+eAAw5gr7324vTTT+fee+8F4JZbbuH222/n5S9/ORdeeCH3338/9957L1/+8penJF576CRJkvo8//nP55577mGLLbZgs802Y7PNNuPaa6/lZS97GQAbbLABn/vc59hll13Yd999edGLXsRWW23F7NmzecpTnjLp8aaqJn2lU2n27Nk1VQcsSpKkyXXttdfyvOc9b0LXce+997LBBhtw3333sfvuu3PKKafw4he/eLnbGSnWJFdX1ezxlrWHTpIkaSUcccQRLFy4kPvvv5/DDjtshZK5lWVCJ0mStBLOOuusqQ7BkyIkSZK6zoROkiSp40zoJEmSOs6ETpIkqeM8KUKSJK0xHrr77lXa3tpPfepA9b761a/yvve9j0ceeYS3ve1tHHPMMas0DnvoJEmSJtAjjzzCe97zHr7yla+wcOFCzj77bBYuXLhK12FCJ0mSNIGuvPJKnv3sZ/OsZz2LddZZh4MPPpgLLrhgla7DhE6SJGkC3XLLLWy55ZaPTc+aNYtbbrllla7DhE6SJGkCjXSb1SSrdB0mdJIkSRNo1qxZ3HzzzY9NDw0Nsfnmm6/SdZjQSZIkTaBddtmFG264gRtvvJEHH3yQOXPmsO+++67SdXjZEkmStMYY9DIjq9Jaa63FSSedxF577cUjjzzCW97yFp7//Oev2nWs0tYkSZL0OPvssw/77LPPhLXvkKskSVLHmdBJkiR1nAmdJElSx5nQSZIkddykJXRJ9k5yXZJFSUa8I22SA5MsTLIgyVlt2Z5J5vc87k+yfzvvM0lu7Jm342RtjyRJ0nQxKWe5JpkBnAy8GhgCrkoyt6oW9tTZFjgW2K2q7kryNICq+hawY1tnY2AR8LWe5o+qqvMnYzskSZKmo8m6bMmuwKKqWgyQZA6wH7Cwp87bgZOr6i6Aqrp9hHYOAL5SVfdNcLySJGk1dPXbj1il7e186ikD1XvLW97Cl770JZ72tKfx4x//eJXGAJM35LoFcHPP9FBb1ms7YLsk30tyRZK9R2jnYODsvrKPJLkmyYlJ1h1p5UmOSDIvybwlS5as6DZIkiStkMMPP5yvfvWrE9b+ZCV0I92Btv9OtWsB2wJ7AIcApyV57HLOSTYDXgBc3LPMscBzgV2AjYGjR1p5VZ1SVbOravbMmTNXdBskSZJWyO67787GG288Ye1PVkI3BGzZMz0LuHWEOhdU1UNVdSNwHU2CN+xA4AtV9dBwQVX9vBoPAJ+mGdqVJElao0xWQncVsG2SbZKsQzN0OrevzheBPQGSbEozBLu4Z/4h9A23tr12JAmwP7DqB6UlSZKmuUk5KaKqHk5yJM1w6Qzg9KpakOQEYF5VzW3nvSbJQuARmrNXlwIk2Zqmh+/bfU2fmWQmzZDufOCdk7E9kiRJ08lkneVKVV0EXNRX9qGe5wX8RfvoX/YmHn8SBVX1ylUeqCRJUsdMWkInSZI01Qa9zMiqdsghh3DppZdyxx13MGvWLI4//nje+ta3rrL2TegkSZIm2Nln9191bdXyXq6SJEkdZ0InSZLUcSZ0kiRptdacdzm9rWyMJnSSJGm1td5667F06dJpndRVFUuXLmW99dZb4TY8KUKSJK22Zs2axdDQENP9Xu7rrbces2bNWuHlTegkSdJqa+2112abbbaZ6jAmnEOukiRJHWdCJ0mS1HEmdJIkSR1nQidJktRxJnSSJEkdZ0InSZLUcSZ0kiRJHWdCJ0mS1HEmdJIkSR1nQidJktRxJnSSJEkdZ0InSZLUcSZ0kiRJHWdCJ0mS1HEmdJIkSR1nQidJktRxJnSSJEkdZ0InSZLUcSZ0kiRJHWdCJ0mS1HEmdJIkSR1nQidJktRxJnSSJEkdZ0InSZLUcZOW0CXZO8l1SRYlOWaUOgcmWZhkQZKzesofSTK/fcztKd8myfeT3JDknCTrTMa2SJIkTSeTktAlmQGcDLwW2B44JMn2fXW2BY4Fdquq5wPv75n9m6rasX3s21P+j8CJVbUtcBfw1oncDkmSpOlosnrodgUWVdXiqnoQmAPs11fn7cDJVXUXQFXdPlaDSQK8Eji/LfossP8qjVqSJKkDJiuh2wK4uWd6qC3rtR2wXZLvJbkiyd4989ZLMq8tH07aNgHurqqHx2gTgCRHtMvPW7JkycpvjSRJ0jSy1iStJyOUVd/0WsC2wB7ALOA7SXaoqruBZ1bVrUmeBXwzyY+AXw3QZlNYdQpwCsDs2bNHrCNJktRVk9VDNwRs2TM9C7h1hDoXVNVDVXUjcB1NgkdV3dr+XQxcCuwE3AE8NclaY7QpSZK02pushO4qYNv2rNR1gIOBuX11vgjsCZBkU5oh2MVJNkqybk/5bsDCqirgW8AB7fKHARdM+JZIkiRNM5OS0LXHuR0JXAxcC5xbVQuSnJBk+KzVi4GlSRbSJGpHVdVS4HnAvCQ/bMs/WlUL22WOBv4iySKaY+o+NRnbI0mSNJ2k6ehac8yePbvmzZs31WFIkiSNK8nVVTV7vHreKUKSJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6btISuiR7J7kuyaIkx4xS58AkC5MsSHJWW7ZjksvbsmuSHNRT/zNJbkwyv33sOFnbI0mSNF2sNRkrSTIDOBl4NTAEXJVkblUt7KmzLXAssFtV3ZXkae2s+4BDq+qGJJsDVye5uKrubucfVVXnT8Z2SJIkTUeT1UO3K7CoqhZX1YPAHGC/vjpvB06uqrsAqur29u/1VXVD+/xW4HZg5iTFLUmSNO1NVkK3BXBzz/RQW9ZrO2C7JN9LckWSvfsbSbIrsA7wk57ij7RDsScmWXeklSc5Ism8JPOWLFmyclsiSZI0zUxWQpcRyqpvei1gW2AP4BDgtCRPfayBZDPgP4E3V9WjbfGxwHOBXYCNgaNHWnlVnVJVs6tq9syZdu5JkqTVy2QldEPAlj3Ts4BbR6hzQVU9VFU3AtfRJHgkeTLwZeBvquqK4QWq6ufVeAD4NM3QriRJ0hploIQuydpJjm/PKL0/yeJ2ep0B13MVsG2SbdplDgbm9tX5IrBnu75NaYZgF7f1vwCcUVXn9cW1Wfs3wP7AjweMR5IkabUx6Fmu/0TT+/UO4KfAVsDfAk8G/ny8havq4SRHAhcDM4DTq2pBkhOAeVU1t533miQLgUdozl5dmuRPgN2BTZIc3jZ5eFXNB85MMpNmSHc+8M4Bt0eSJGm1kar+Q9lGqJQMAS+qqqU9ZZsCP6yq/pMbprXZs2fXvHnzpjoMSZKkcSW5uqpmj1dv0GPoRjqpYaxySZIkTZJBE7rzgAuT7JXkee0lRb4InDtxoUmSJGkQgx5D90Hgb2ju9rA5zRmqZwN/P0FxSZIkaUADJXTt3R0+1D4kSZI0jYya0CXZvaoua5+/crR6VfXNiQhMkiRJgxmrh+7/ATu0zz81Sp0CnrVKI5IkSdJyGTWhq6odep5vMznhSJIkaXkNeqeIC0Yp//yqDUeSJEnLa9DLluw5SvkeqygOSZIkraAxz3Jtb80FsE7P82HPorkNmCRJkqbQeJct2bL9+4Se59CcDHEzcNwExCRJkqTlMGZCV1VvBkjy31V16uSEJEmSpOUx6IWFTwVIsiGwKT33cK2qxRMTmiRJkgYxUEKX5HnAWcCLaIZb0/4FmDExoUmSJGkQg57l+gngW8DGwK+AjYBPAodNUFySJEka0EA9dDQ9c6+uqoeSpKp+meQo4MfA5yYuPEmSJI1n0B66+4G12+d3JHnvkOWwAAAYAUlEQVRmu+wmExKVJEmSBjZoQvcd4MD2+fnAV4BvA9+ciKAkSZI0uEHPcj2wZ/KvaIZaNwTOmIigJEmSNLhxE7okM4BvAHtV1QNV9SgeNydJkjRtjDvkWlWPANsMUleSJEmTb9Ak7XjgE0m2SjIjyROGHxMZnCRJksY36GVLTmv//mlP2fDFhb2wsCRJ0hQaNKHbZkKjkCRJ0gob9CzXn050IJIkSVoxHgMnSZLUcSZ0kiRJHWdCJ0mS1HGDXlj4emD7qnpg4kNSlz10991Ttu5rjvrglK0bYOdTT5nS9UuS1lyDXlj4EWC9iQ9HkiRJy2vQy5Z8HDg3yT8AQzTXnwOgqhZPRGCSJEkazKDH0J0EvBr4FnADsKh93DDoipLsneS6JIuSHDNKnQOTLEyyIMlZPeWHJbmhfRzWU75zkh+1bf5bkgwajyRJ0upi0OvQrdTJE+1xeCfTJIVDwFVJ5lbVwp462wLHArtV1V1JntaWbwz8HTCbpmfw6nbZu4BPAEcAVwAXAXsDX1mZWCVJkrpmuRK1JFsmeekKrGdXYFFVLa6qB4E5wH59dd4OnNwmalTV7W35XsAlVXVnO+8SYO8kmwFPrqrLq6qAM4D9VyA2SZKkThsooUvyzCTfA/4X+HpbdkCS08Ze8jFbADf3TA+1Zb22A7ZL8r0kVyTZe5xlt2ifj9XmcPxHJJmXZN6SJUsGDFmSJKkbBu2h+yTwZWBD4KG27BKaIdRBjHRsW/VNrwVsC+wBHAKcluSpYyw7SJtNYdUpVTW7qmbPnDlzwJAlSZK6YdCEblfgo1X1KG3SVFW/BJ4y4PJDwJY907OAW0eoc0FVPVRVNwLX0SR4oy071D4fq01JkqTV3qAJ3S+AZ/cWJNke+NmAy18FbJtkmyTrAAcDc/vqfBHYs217U5oh2MXAxcBrkmyUZCPgNcDFVfVz4J4kL23Pbj0UuGDAeCRJklYbgyZ0HwO+lOTNwFpJDgHOAf5xkIWr6mHgSJrk7Frg3KpakOSEJPu21S4GliZZSHN5lKOqamlV3Ql8mCYpvAo4oS0DeBdwGs0lVH6CZ7hKkqQ10KCXLTk9yZ00lwi5GTgM+Nuq+uKgK6qqi2guLdJb9qGe5wX8Rft43PqB00conwfsMGgMkiRJq6NB7xRBm7wNnMB11VTeixRg7ac+dUrXL0nqlqvffsSUrt/7WE8PoyZ0Sd4ySANt75kkqcP8Z1bqtrF66P6053mA3YDbaIZctwSeAXyXEYZCJUlaU0x1MizBGAldVe05/DzJvwNfrKqP95S9D/idiQ1PkiRJ4xn0GLo/ATbtKzsJuAN47yqNSJIkSctl0ITuNmBf4As9Za8Hbh+5uqTlNdXDNh7DJEndNWhC917g/CRH0RxD90xge+BNExWYJEmSBjPodeguSfIsYB9gc5r7un65qpZOZHCSNCh7OCWtycZN6JLMAK4Htq+q/5z4kCRJkrQ8xr31V1U9AjwCrDfx4UiSJGl5DXoM3ceBc5P8AzAE1PCMqlo8EYFJkiRpMIMmdCe1f1/dV17AjFUXjiRJkpbXoCdFjDs0K0mSpKkxaA8dAEmeCWwBDFXVzRMTkiRJkpbHQD1vSTZL8m1gEfB54CdJLkuy+YRGJ0mSpHENOpT6CeCHwEZVtRmwEfAD4D8mKjBJkiQNZtAh15cDm1XVQwBV9eskHwRumbDIJEmSNJBBE7q7aG719cOesucAU3tpdkmS1Gne5WXVGDSh+yfg60k+BfwU2Ap4M/C3ExWYJEmSBjPoZUtOTfIT4I+AFwK3AodU1TcnMjhJkiSNb+DLlrTJmwmcJEnSNDPoZUvWTfKRJIuT/LIte02SIyc2PEmSJI1n0MuWnAjsAPwxv72P6wLgXRMRlCRJkgY36JDrG4Bnt5creRSgqm5JssXEhSZJkqRBDNpD9yB9yV+SmcDSVR6RJEmSlsugPXTnAZ9N8ufQ3AoM+DgwZ6ICkzS5rn77EVO6/p1PPWVK1y9JXTZoD91fATcBPwKeCtxAc+mSEyYmLEmSJA1q0OvQPQi8H3h/O9R6R1XVOItJkiRpEgzaQ/eYqlpSVZXkhUnOm4igJEmSNLgxe+iSPBE4FtiRZpj1OGBT4P8CrwY+O8HxSZLWAFN5DKfHb2p1MN6Q68nATsDFwGuBFwDPpUnk3l5Vd0xseJIkSRrPeAndXsCOVXV7kn8Hfga8oqq+M/GhSZIkaRDjHUO3QVXdDlBVQ8C9K5rMJdk7yXVJFiU5ZoT5hydZkmR++3hbW75nT9n8JPcn2b+d95kkN/bM23FFYpMkSeqy8Xro1kqyJ5Dhgv7pqvrmeCtJMoNm+PbVwBBwVZK5VbWwr+o5VbXM/WGr6ls0x/CRZGNgEfC1nipHVdX548UgSZK0uhovobsdOL1nemnfdAHPGmA9uwKLqmoxQJI5wH5Af0I3ngOAr1TVfcu5nCRJ0mprzCHXqtq6qrYZ4zFIMgewBXBzz/RQW9bvjUmuSXJ+ki1HmH8wcHZf2UfaZU5Msu5IK09yRJJ5SeYtWbJkwJAlSZK6YbmvQ7eCMkJZ/4WJLwS2rqoXAl+n75Io7e3GXkBzxu2wY2nOut0F2Bg4eqSVV9UpVTW7qmbPnDlzxbZAkiRpmpqshG4I6O1xm0Vz67DHVNXSqnqgnTwV2LmvjQOBL1TVQz3L/LwaDwCfphnalSRJWqNMVkJ3FbBtkm2SrEMzdDq3t0LbAzdsX+DavjYOoW+4dXiZJAH2B368iuOWJEma9ga6l+vKqqqHkxxJM1w6Azi9qhYkOQGYV1Vzgfcm2Rd4GLgTOHx4+SRb0/Twfbuv6TPbe8sGmA+8c4I3RZJGNJV3OgDvdiCt6SYloQOoqouAi/rKPtTz/FiaY+JGWvYmRjiJoqpeuWqjlCRJ6p7JGnKVJEnSBDGhkyRJ6jgTOkmSpI4zoZMkSeo4EzpJkqSOM6GTJEnqOBM6SZKkjjOhkyRJ6jgTOkmSpI4zoZMkSeo4EzpJkqSOM6GTJEnqOBM6SZKkjjOhkyRJ6jgTOkmSpI4zoZMkSeo4EzpJkqSOM6GTJEnqOBM6SZKkjjOhkyRJ6jgTOkmSpI4zoZMkSeo4EzpJkqSOM6GTJEnqOBM6SZKkjjOhkyRJ6jgTOkmSpI4zoZMkSeo4EzpJkqSOM6GTJEnqOBM6SZKkjjOhkyRJ6rhJS+iS7J3kuiSLkhwzwvzDkyxJMr99vK1n3iM95XN7yrdJ8v0kNyQ5J8k6k7U9kiRJ08WkJHRJZgAnA68FtgcOSbL9CFXPqaod28dpPeW/6Snft6f8H4ETq2pb4C7grRO1DZIkSdPVZPXQ7QosqqrFVfUgMAfYb2UaTBLglcD5bdFngf1XKkpJkqQOmqyEbgvg5p7pobas3xuTXJPk/CRb9pSvl2RekiuSDCdtmwB3V9XD47RJkiPa5ectWbJkJTdFkiRpepmshC4jlFXf9IXA1lX1QuDrND1uw55ZVbOBPwI+nuR3BmyzKaw6papmV9XsmTNnLn/0kiRJ09hkJXRDQG+P2yzg1t4KVbW0qh5oJ08Fdu6Zd2v7dzFwKbATcAfw1CRrjdamJEnSmmCyErqrgG3bs1LXAQ4G5vZWSLJZz+S+wLVt+UZJ1m2fbwrsBiysqgK+BRzQLnMYcMGEboUkSdI0tNb4VVZeVT2c5EjgYmAGcHpVLUhyAjCvquYC702yL/AwcCdweLv484BPJnmUJgH9aFUtbOcdDcxJ8vfAD4BPTcb2SJIkTSeTktABVNVFwEV9ZR/qeX4scOwIy/038IJR2lxMcwatJEnSGss7RUiSJHWcCZ0kSVLHmdBJkiR1nAmdJElSx5nQSZIkddykneWqwVz99iOmdP07n3rKlK5fkiQtP3voJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjpurakOQJIkaapc/fYjpnT9O596yippxx46SZKkjjOhkyRJ6jgTOkmSpI4zoZMkSeo4EzpJkqSOM6GTJEnqOBM6SZKkjjOhkyRJ6jgTOkmSpI4zoZMkSeq4SUvokuyd5Loki5IcM8L8w5MsSTK/fbytLd8xyeVJFiS5JslBPct8JsmNPcvsOFnbI0mSNF1Myr1ck8wATgZeDQwBVyWZW1UL+6qeU1VH9pXdBxxaVTck2Ry4OsnFVXV3O/+oqjp/QjdAkiRpGpusHrpdgUVVtbiqHgTmAPsNsmBVXV9VN7TPbwVuB2ZOWKSSJEkdM1kJ3RbAzT3TQ21Zvze2w6rnJ9myf2aSXYF1gJ/0FH+kXebEJOuOtPIkRySZl2TekiVLVmIzJEmSpp/JSugyQln1TV8IbF1VLwS+Dnx2mQaSzYD/BN5cVY+2xccCzwV2ATYGjh5p5VV1SlXNrqrZM2fauSdJklYvk5XQDQG9PW6zgFt7K1TV0qp6oJ08Fdh5eF6SJwNfBv6mqq7oWebn1XgA+DTN0K4kSdIaZbISuquAbZNsk2Qd4GBgbm+Ftgdu2L7AtW35OsAXgDOq6ryRlkkSYH/gxxO2BZIkSdPUpJzlWlUPJzkSuBiYAZxeVQuSnADMq6q5wHuT7As8DNwJHN4ufiCwO7BJkuGyw6tqPnBmkpk0Q7rzgXdOxvZIkiRNJ5OS0AFU1UXARX1lH+p5fizNMXH9y30O+Nwobb5yFYcpSZLUOd4pQpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjTOgkSZI6zoROkiSp40zoJEmSOs6ETpIkqeMmLaFLsneS65IsSnLMCPMPT7Ikyfz28baeeYcluaF9HNZTvnOSH7Vt/luSTNb2SJIkTReTktAlmQGcDLwW2B44JMn2I1Q9p6p2bB+ntctuDPwd8BJgV+DvkmzU1v8EcASwbfvYe2K3RJIkafqZrB66XYFFVbW4qh4E5gD7DbjsXsAlVXVnVd0FXALsnWQz4MlVdXlVFXAGsP9EBC9JkjSdpcmFJnglyQHA3lX1tnb6T4GXVNWRPXUOB/4PsAS4Hvjzqro5yQeA9arq79t6fwv8BrgU+GhV/X5b/nvA0VX1uhHWfwRNTx7Ac4DrJmI7V5FNgTumOoiOct+tHPffynH/rRz334pz362c6b7/tqqqmeNVWmsyIgFGOratP5O8EDi7qh5I8k7gs8Arx1h2kDabwqpTgFMGD3fqJJlXVbOnOo4uct+tHPffynH/rRz334pz362c1WX/TdaQ6xCwZc/0LODW3gpVtbSqHmgnTwV2HmfZofb5qG1KkiStCSYrobsK2DbJNknWAQ4G5vZWaI+JG7YvcG37/GLgNUk2ak+GeA1wcVX9HLgnyUvbs1sPBS6Y6A2RJEmabiZlyLWqHk5yJE1yNgM4vaoWJDkBmFdVc4H3JtkXeBi4Ezi8XfbOJB+mSQoBTqiqO9vn7wI+A6wPfKV9dF0nhoanKffdynH/rRz338px/604993KWS3236ScFCFJkqSJ450iJEmSOs6ETpIkqeNM6CRJkjrOhE6SJKnjJuvCwhpBkufS3AJtC5qLIt8KzK2qa8dcUFoF2vffFsD3q+renvK9q+qrUxdZNyTZFaiquqq9N/XewP9W1UVTHFrnJDmjqg6d6ji6KMnLaW6v+eOq+tpUxzPdJXkJcG1V/SrJ+sAxwIuBhcA/VNUvpzTAleBZrlMkydHAITT3tR1qi2fRXKNvTlV9dKpiWx0keXNVfXqq45iukrwXeA/N9R53BN5XVRe08/6nql48lfFNd0n+DngtzT/FlwAvobkd4e/TXCfzI1MX3fSWZG5/EbAn8E2Aqtp30oPqkCRXVtWu7fO303yOv0BzjdYL/e0YW5IFwIvay6mdAtwHnA+8qi3/wykNcCWY0E2RJNcDz6+qh/rK1wEWVNW2UxPZ6iHJz6rqmVMdx3SV5EfAy6rq3iRb03yh/WdV/WuSH1TVTlMa4DTX7r8dgXWB24BZPf/xf7+qXjilAU5jSf6HpjfkNH57G8ezaf6Zpaq+PXXRTX+9n88kVwH7VNWSJE8CrqiqF0xthNNbkmur6nnt82X+eU0yv6p2nLroVo5DrlPnUWBz4Kd95Zu18zSOJNeMNgt4+mTG0kEzhodZq+qmJHsA5yfZipHvk6xlPVxVjwD3JflJVf0KoKp+k8TP79hmA+8D/ho4qqrmJ/mNidzAntDeNekJNJ0ySwCq6tdJHp7a0Drhxz0jOD9MMruq5iXZDnhovIWnMxO6qfN+4BtJbgBubsueCTwbOHLKouqWpwN7AXf1lQf478kPp1NuS7JjVc0HaHvqXgecDvgf/vgeTPLEqrqP3953miRPwX/IxlRVjwInJjmv/fsL/C1aHk8Brqb5nqskz6iq25JsgP+MDeJtwL8m+RvgDuDyJDfT/A6/bUojW0kOuU6hJE+gOZh1C5oP4hBwVfufv8aR5FPAp6vquyPMO6uq/mgKwuqEJLNoepluG2HeblX1vSkIqzOSrFtVD4xQvimwWVX9aArC6qQkfwDsVlV/NdWxdFmSJwJPr6obpzqWLkiyIfAsmn8mhqrqF1Mc0kozoZMkSeo4r0MnSZLUcSZ0kiRJHWdCJ0krIclzkvwgyT3t9f0me/1bJ6kknlggrcH8ApDUOUluojnL+WHgEZrrmp0BnNKeRTmZPghc6rX7JE0le+gkddXrq2pDYCvgo8DRwKemII6tgAVTsF5JeowJnaROq6pfVtVc4CDgsCQ7QHM5jHYo9FdJbk5y3PAySb6c5M9620lyTZL9R1pHkn2TLEhyd5JLkwxfaf6bNLetOinJve3FSXuX27O9q8Tw9NeTXNkz/d3hdSbZPMl/JVmS5Mbe4dskT0hyTJKfJFma5NwkG48S6xuT3DS8HyStGUzoJK0WqupKmms5/l5b9GvgUOCpwB8A7+pJ2D4L/MnwskleRHM9yIv6222TtLNpLgY+s61zYZJ1quqVwHeAI6tqg6q6vm/xy4FnJ9m0PcZtB2BWkg3b24TtDHynvSblhcAP2zheBbw/yV5tO+8F9gdeQXOHmbuAk0eI9c3APwK/X1U/HmC3SVpNmNBJWp3cCmwMUFWXVtWPqurRqrqGJil7RVvvAmDbJMP3TP5T4JyqenCENg8CvlxVl7T3Xv4YsD7wu+MFU1X3A/OA3WlueXUN8F1gN+ClwA1VtRTYBZhZVSdU1YNVtRg4lfb+psA7gL+uqqH2gsbHAQf0nQjxfuAoYI+qWjRebJJWL54UIWl1sgVwJ0CSl9AcW7cDsA6wLnAeQFU9kORc4E+SHA8cAhwwSpvL3HO5qh5tbxW0xYAxfRvYg6b38Ns0vWuvAB5op6E5Dm/zJHf3LDeDpvdveP4X+u4T+wjL3rP4KOCEqhoaMC5JqxF76CStFpLsQpNkDd8K7ixgLrBlVT0F+A+WvdflZ4E/phnevK+qLh+l6VtpEqrh9QTYErhlwNCGE7rd2+ffpknoXsFvE7qbgRur6qk9jw2rap+e+a/tm79eVfXG8Brgb5K8ccC4JK1GTOgkdVqSJyd5HTAH+FzPfVQ3BO6sqvuT7Aosc2/fNoF7FPi/wH+OsYpzgT9I8qokawN/SdO79t8DhvjfwHNo7tt8ZVUtoEkQXwJc1ta5EvhVkqOTrJ9kRpId2iQVmmT0I0m2ard5ZpL9+tazANgbODnJvgPGJmk1YUInqasuTHIPTe/VXwP/Ary5Z/67gRPaOh+iScz6nQG8APjcaCupqutoTqD4d+AO4PU0l0wZ6Xi7kZb/NfA/wIKeZS4HflpVt7d1Hmnb3RG4sV3PacBT2vr/StPb+LV2e66gSQj71/VD4HXAqUleO0h8klYPqaqpjkGSpkSSQ4EjqurlUx2LJK0Me+gkrZGSPJGmF++UqY5FklaWCZ2kNU57fbclwC9oTp6QpE5zyFWSJKnj7KGTJEnqOBM6SZKkjjOhkyRJ6jgTOkmSpI4zoZMkSeq4/w8g7mlTn5frdgAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def reorders_dow_both_groups(data):\n", " group=\"veg\"\n", " plot_title = \"Reorder ratio across day of week for {group} and non-{group}\".format(group=group)\n", " grouped_df = data.groupby([\"order_dow\", group])[\"reordered\"].aggregate(\"mean\").reset_index()\n", " plt.figure(figsize=(10,6))\n", " sns.barplot(grouped_df['order_dow'].values, grouped_df['reordered'].values, \n", " alpha=0.8, color=colour[3], hue=grouped_df[group])\n", " plt.ylabel('Reorder ratio', fontsize=12)\n", " plt.xlabel('Day of week', fontsize=12)\n", " plt.title(plot_title, fontsize=15)\n", " plt.xticks(rotation='vertical')\n", " plt.ylim(0.5, 0.7)\n", " plt.show()\n", "\n", "reorders_dow_both_groups(final_order_data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### It apears that vegetarian reorder rate is lower on the weekends compared to non-vegetarians who reorder at fairly consistent rates regardless of day of the week. That's interesting- reorder ratio per day of week could be a meaningful feature for the model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# EDA: Department x User Features" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "def plot_correlations(feature_df, col_prefix):\n", " group = \"veg\"\n", " to_drop = \"{}_12\".format(col_prefix)\n", " feature_df = feature_df.drop(to_drop, axis=1)\n", " plot_title = \"Correlation matrix (Pearson) for the {group} group.\".format(group=group)\n", " labels = final_order_data[[\"user_id\", group]].drop_duplicates()\n", " labels=labels[labels[group]==1]\n", " df = feature_df.merge(labels,on=\"user_id\")\n", " corr = df.corr()\n", " # Generate a mask for the upper triangle\n", " mask = np.zeros_like(corr, dtype=np.bool)\n", " mask[np.triu_indices_from(mask)] = True\n", " # Set up the matplotlib figure\n", " f, ax = plt.subplots(figsize=(10, 8))\n", " # Generate a custom diverging colormap\n", " cmap = sns.diverging_palette(220, 10, as_cmap=True)\n", " # Draw the heatmap with the mask and correct aspect ratio\n", " sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.5, center=0,\n", " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n", " plt.title(plot_title, fontsize=15)\n", " \n", "def plot_group_proportions(feature_df, order_data, col, n, format_xticks):\n", " group = \"veg\"\n", " data = feature_df.merge(order_data[[\"user_id\", group]].drop_duplicates(), on = \"user_id\")\n", " x, y, hue = col, \"purchase_proportion\", group\n", " hue_order = [group, \"not_{}\".format(group)]\n", " plt.figure(figsize=(12,6))\n", " (data[x]\n", " .groupby(data[hue])\n", " .value_counts(normalize=True)\n", " .rename(y)\n", " .reset_index()\n", " .pipe((sns.barplot, \"data\"), x=x, y=y, hue=hue))\n", " plt.xticks(rotation='45')\n", " ax = plt.gca()\n", " if format_xticks is True:\n", " for index, label in enumerate(ax.xaxis.get_ticklabels()):\n", " if index % n != 0:\n", " label.set_visible(False)\n", " l = plt.legend(loc=\"upper right\")\n", " l.set_title('Non-{group} (0) vs {group} (1)'.format(group=group))\n", " \n", "def feature_correlation(f1, f2):\n", " feature = f1.merge(f2, on = \"user_id\")\n", " corr = feature.corr()\n", " # Generate a mask for the upper triangle\n", " mask = np.zeros_like(corr, dtype=np.bool)\n", " mask[np.triu_indices_from(mask)] = True\n", " # Set up the matplotlib figure\n", " f, ax = plt.subplots(figsize=(11, 9))\n", " # Generate a custom diverging colormap\n", " cmap = sns.diverging_palette(220, 10, as_cmap=True)\n", " # Draw the heatmap with the mask and correct aspect ratio\n", " sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.5, center=0,\n", " square=True, linewidths=.5, cbar_kws={\"shrink\": .5}) \n", "\n", "def get_dept_reorder_rate(data):\n", " dept_reorder_rate = data.groupby([\"user_id\", \"department_id\"])[\"reordered\"].aggregate(\"mean\").reset_index(name=\"reorder_rate\")\n", " dept_reorder_rate = dept_reorder_rate.pivot_table(index='user_id', columns='department_id', values='reorder_rate')\n", " dept_reorder_rate.fillna(0, inplace=True)\n", " dept_reorder_rate.columns = ['reord_rt_dept_' + str(col) for col in dept_reorder_rate.columns]\n", " return dept_reorder_rate\n", "\n", "def get_num_dept_reorders(data):\n", " dept_num_reorders = data.groupby([\"user_id\", \"department_id\"])[\"reordered\"].aggregate(\"sum\").reset_index(name=\"num_reorders\")\n", " dept_num_reorders = dept_num_reorders.pivot_table(index='user_id', columns='department_id', values='num_reorders')\n", " dept_num_reorders.fillna(0, inplace=True)\n", " dept_num_reorders.columns = ['num_reorder_dept_' + str(col) for col in dept_num_reorders.columns]\n", " return dept_num_reorders\n", "\n", "def get_time_bw_dept_purchases(data):\n", " avg_time_bw_dept = data.groupby([\"user_id\",\"department_id\"])[\"days_since_prior_order\"].aggregate(\"mean\").reset_index(name=\"avg_days_bw_order_dept\")\n", " avg_time_bw_dept[\"avg_days_bw_order_dept\"] = round(avg_time_bw_dept[\"avg_days_bw_order_dept\"],1)\n", " avg_time_bw_dept = avg_time_bw_dept.pivot_table(index='user_id', columns='department_id', values='avg_days_bw_order_dept')\n", " avg_time_bw_dept.fillna(0, inplace=True)\n", " avg_time_bw_dept.columns = ['avg_days_bw_dept_' + str(col) for col in avg_time_bw_dept.columns]\n", " return avg_time_bw_dept" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Number of times purchased from each department: correlation between departments" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def get_num_dept_purchases(data):\n", " num_dept_purchases = data.groupby([\"user_id\", \"department_id\"]).size().reset_index(name=\"num_orders\")\n", " num_dept_purchases = num_dept_purchases.pivot_table(index='user_id', columns='department_id', values='num_orders')\n", " num_dept_purchases.fillna(0, inplace=True)\n", " num_dept_purchases.columns = ['dept_' + str(col) for col in num_dept_purchases.columns]\n", " # Drop the columns that were used to define the segments\n", " # We don't need to see them in the correlation plot\n", " return num_dept_purchases\n", "\n", "num_dept_purchases = get_num_dept_purchases(final_order_data) # Feature\n", "plot_correlations(num_dept_purchases, \"dept\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can see from the correlation matrix the some of the features (number of times purchased from each individual department) is correlated. This implies that some of these features may be dropped. For example, dept 9 and dept 1 are highly correlated (see the bottom left corner), so this means we could use either dept_1 or dept_9 as a feature, and could throw out one of them.\n", "\n", "## Number of unique department purchases" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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5SpIkSa1U/KY2mXkdcF2PaZMbhqdTdS/pud5FwEWl85MkSZJKKX5TG0mSJGllZbEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVS/NJ/kqSVx5hjL2h6nRlfmlAgE0laPtiyLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVYrEtSZIkFWKxLUmSJBVisS1JkiQVUrzYjoi9I2JWRMyOiON6mf/GiLgtIuZHxIE95h0eEX+sH4eXzlWSJElqpaLFdkQMAM4C9gFGAYdGxKgei80BjgAu6bHuYOA/gR2AccB/RsT6JfOVJEmSWmlg4ecfB8zOzPsAImIasD/w++4FMvOBet7CHuvuBfwwM5+o5/8Q2Bu4tHDOklYyc6Zs0/Q6wyfP7DfxJUnllO5GsjHwUMN4Vz2t9LqSJElSx5UutqOXadnKdSNiYkTcGhG3PvbYY00lJ0mSJJVUutjuAoY1jA8FHmnlupl5dmaOzcyxQ4YMedmJSpIkSa1Wus/2dGDziBgJPAwcAry7j+veAPxXw0mRewLHtz5FSZ1mn2VJUn9VtGU7M+cDk6gK57uByzPzroiYEhH7AUTE9hHRBRwEfCsi7qrXfQL4AlXBPh2Y0n2ypCRJkrQiKN2yTWZeB1zXY9rkhuHpVF1Eelv3HOCcoglKkiRJhXgHSUmSJKkQi21JkiSpEIttSZIkqRCLbUmSJKmQpk6QjIgBwL80rpeZc1qdlCRJktQf9LnYjoiPAP8J/BlYWE9OYNsCeUmSJEkrvGZato8BtszMuaWSkSRJkvqTZvpsPwQ8VSoRSZIkqb9ppmX7PuCnEXEt8Gz3xMw8reVZSZIkSf1AM8X2nPqxWv2QJElaZMyxFzS9zowvTSiQibT86HOxnZknAETE2tVoPl0sK0nSy/Jyip2r1v5S0+sMnzyz6XUkaWXU5z7bEbF1RNwO3AncFREzImKrcqlJkiRJK7ZmTpA8G/h4Zm6SmZsAnwC+XSYtSZIkacXXTLG9Zmb+pHskM38KrNnyjCRJkqR+oqmrkUTE54AL6/H3Ave3PiVJkiSpf2im2D4KOAH4LhDAz4EjSyQlqf3mTNmmqeU9QU6SpKVr5mokTwJHF8xFkiRJ6leWWmxHxFcy86MRcQ2QPedn5n5FMpMkSZJWcH1p2e7uo31qyUQkSZKk/mapxXZmzqgHR2fmVxvnRcQxwM9KJCZJkiSt6Jq59N/hvUw7okV5SJIkSf1OX/psHwq8G9g0Iq5umLU2MLdUYpIkSdKKri99tn8NPAq8Evhyw/S/A3eUSEqSJEnqD/rSZ/vBiOgCnslM+2dLkiRJfdSnPtuZuQD4R0SsWzgfSZIkqd9o5g6S84CZEfFD4JnuiZnpjW4kSZKkXjRTbF9bPyRJkiT1QTO3az8/IlYDtqgnzcrM58ukJUmSJK34+lxsR8SbgPOBB4AAhkXE4Zn58zKpSZIkSSu2ZrqRfBnYMzNnAUTEFsClwJgSiUmSJEkrumbuILlqd6ENkJn3AKu2PiVJkiSpf2imZfvWiJgKXFiPvweY0fqUJEmSpP6hmWL734EPA0dT9dn+OfD1EklJkiRJ/UEzVyN5NiLOBH4ELKS6GslzxTKTVjJzpmzT1PLDJ88slIkkSWqVZq5G8jbgm8C9VC3bIyPiA5n5g1LJSZIkSSuyZk6Q/DKwW2a+KTN3BXYDTl/aShGxd0TMiojZEXFcL/NXj4jL6vk3R8SIevqqEXF+RMyMiLsj4vgmcpUkSZI6rpli+y+ZObth/D7gL0taISIGAGcB+wCjgEMjYlSPxd4HPJmZm1EV76fU0w8CVs/MbaguL/iB7kJckiRJWhE0U2zfFRHXRcQREXE4cA0wPSIOiIgDFrPOOGB2Zt5X9++eBuzfY5n9qW6WA3AFsHtEBJDAmhExEFgDeA74WxP5SpIkSR3VTLE9CPgzsCvwJuAxYDDwdmDfxayzMfBQw3hXPa3XZTJzPvAUsAFV4f0M8CgwBzg1M59oIl9JkiSpo5q5GsmRL+P5o7en6uMy44AFwEbA+sAvIuL/MvO+F60cMRGYCDB8+PCXkaIkSZJURp9btiNiaERcFRF/iYg/R8SVETF0Kat1AcMaxocCjyxumbrLyLrAE8C7gesz8/nM/AvwK2BszwCZeXZmjs3MsUOGDOnr5kiSJEnFNdON5FzgaqqW5o2p+myfu5R1pgObR8TIiFgNOKR+jkZXA4fXwwcCP87MpOo68uaorAnsCPyhiXwlSZKkjmrmDpJDMrOxuD4vIj66pBUyc35ETAJuAAYA52TmXRExBbg1M68GpgIXRsRsqhbtQ+rVz6Iq5u+k6mpybmbe0US+kqQVQLM3dAJv6iRpxdFMsf14RLwXuLQePxSYu7SVMvM64Loe0yY3DM+jusxfz/We7m26JEmStKJophvJUcDBwJ+orhByYD1NkiRJUi/61LJd35zmXZm5X+F8JEmSpH6jTy3bmbmAl96MRpIkSdISNNNn+1cRcSZwGdXNZgDIzNtanpUkSZLUDzRTbO9c/53SMC2BN7cuHUmSJKn/aOYOkruVTESSJEnqb5q5g+QGEXFGRNwWETMi4qsRsUHJ5CRJkqQVWTOX/psGPAa8i+qyf49R9d+WJEmS1Itm+mwPzswvNIx/MSLe0eqEJEmSpP6imZbtn0TEIRGxSv04GLi2VGKSJEnSiq6ZYvsDwCXAs/VjGvDxiPh7RPytRHKSJEnSiqyZq5GsvaT5EbFVZt617ClJ0optzLEXNLX8VUv8dJUkrciaadlemgtb+FySJEnSCq+VxXa08LkkSZKkFV4ri+1s4XNJkiRJK7xWFtuSJEmSGrSy2H6uhc8lSZIkrfD6fDWSiAjgPcCmmTklIoYDr8rMWwAyc8dCOUptMWfKNk2vM3zyzAKZSJKk/qKZlu2vAzsBh9bjfwfOanlGkiRJUj/RzO3ad8jM10XE7QCZ+WRErFYoL0mSJGmF10zL9vMRMYD6qiMRMQRYWCQrSZIkqR9optg+A7gK2DAiTgR+CfxXkawkSZKkfqCZ27VfHBEzgN2pbmDzjsy8u1hmkiRJ0gquzy3bEfEa4P7MPAu4E9gjItYrlpkkSZK0gmumG8mVwIKI2Az4H2AkcEmRrCRJkqR+oJlie2FmzgcOAL6amR8DXl0mLUmSJGnF1+zVSA4FJgDfr6et2vqUJEmSpP6hmWL7SKqb2pyYmfdHxEjgojJpSZIkSSu+Zq5G8nvg6Ibx+4GTSyQlSZIk9Qd9LrYjYnPgJGAUMKh7emZuWiAvSZIkaYXXTDeSc4FvAPOB3YALgAtLJCVJkiT1B31u2QbWyMwfRURk5oPA5yPiF8B/FspNkqTi5kzZpul1hk+eWSATSf1RM8X2vIhYBfhjREwCHgY2LJOWJEmStOJrphvJR4FXUJ0kOQY4DDi8RFKSJElSf9DM1Uim14NPU10GUJIkSdIS9LllOyK2iIhvR8SNEfHj7kcf1ts7ImZFxOyIOK6X+atHxGX1/JsjYkTDvG0j4qaIuCsiZkbEoJ7rS5IkScurZvpsfwf4JvBtYEFfVoiIAcBZwB5AFzA9Iq6ur9nd7X3Ak5m5WUQcApwCjI+IgVQ3zTksM38XERsAzzeRryRJktRRzRTb8zPzG00+/zhgdmbeBxAR04D9gcZie3/g8/XwFcCZERHAnsAdmfk7gMyc22RsSZIkqaOW2o0kIgZHxGDgmoj4UES8untaPX1JNgYeahjvqqf1ukxmzgeeAjYAtgAyIm6IiNsi4lN93CZJkiRpudCXlu0ZQAJRjx/bMC+BJd1BMnqZln1cZiCwC7A98A/gRxExIzN/9KKVIyYCEwGGDx++hFQkSZKk9lpqsZ2ZI5fh+buAYQ3jQ4FHFrNMV91Pe13giXr6zzLzcYCIuA54HfCiYjszzwbOBhg7dmzPQl6SJEnqmGauRvLhiFivYXz9iPjQUlabDmweESMjYjXgEODqHstczQvX6z4Q+HFmJnADsG1EvKIuwnflxX29JUmSpOVaMze1eX9m/rV7JDOfBN6/pBXqPtiTqArnu4HLM/OuiJgSEfvVi00FNoiI2cDHgeManv80qoL9t8BtmXltE/lKkiRJHdXM1UhWiYioW527L+u32tJWyszrgOt6TJvcMDwPOGgx615Edfk/rQTmTNmm6XWGT55ZIBNJkqTWaKbYvhG4PCK+SXUC4weB64tkJUmSJPUDzRTbn6K66se/U11B5Ebgf0okJUmSJPUHfSq26y4j52fme6nuIilJkiRpKfp0gmRmLgCG1FcUkSRJktQHzXQjeQD4VURcDTzTPTEzT2t1UpIkSVJ/0Eyx/Uj9WAVYu0w6kiRJUv/R52I7M08omYgkSZLU3/S52I6In1Bd8u9FMvPNLc1IkiRJ6iea6UbyyYbhQcC7gPmtTUeSlt2YYy9oavmr7BgnSSqkmW4kM3pM+lVE/KzF+UiSJEn9RjPdSAY3jK4CjAVe1fKMJEmSpH6imW4kM3ihz/Z8qksBvq/VCUmSJEn9RTPF9ijgQ8AuVEX3L4BbSyQlSZIk9QfNFNvnA38DzqjHDwUuBA5qdVKSJElSf9BMsb1lZm7XMP6TiPhdqxOSJEmS+otVmlj29ojYsXskInYAftX6lCRJkqT+oZmW7R2ACRExpx4fDtwdETOBzMxtW56dJEmStAJrptjeu1gWkiRJUj/UzE1tHiyZiCRJktTfNNOyLUmStNwac+wFTS0/40sTCmUivaCZEyQlSZIkNcFiW5IkSSrEYluSJEkqxGJbkiRJKsRiW5IkSSrEYluSJEkqxGJbkiRJKsRiW5IkSSrEYluSJEkqxGJbkiRJKsRiW5IkSSrEYluSJEkqZGCnE9DyY86UbZpeZ/jkmQUykSRJ6h9s2ZYkSZIKsdiWJEmSCrEbiSRJHWQXPql/K96yHRF7R8SsiJgdEcf1Mn/1iLisnn9zRIzoMX94RDwdEZ8snaskSZLUSkWL7YgYAJwF7AOMAg6NiFE9Fnsf8GRmbgacDpzSY/7pwA9K5ilJkiSVULplexwwOzPvy8zngGnA/j2W2R84vx6+Atg9IgIgIt4B3AfcVThPSZIkqeVKF9sbAw81jHfV03pdJjPnA08BG0TEmsCngRMK5yhJkiQVUbrYjl6mZR+XOQE4PTOfXmKAiIkRcWtE3PrYY4+9zDQlSZKk1it9NZIuYFjD+FDgkcUs0xURA4F1gSeAHYADI+K/gfWAhRExLzPPbFw5M88GzgYYO3Zsz0JekiRJ6pjSxfZ0YPOIGAk8DBwCvLvHMlcDhwM3AQcCP87MBN7QvUBEfB54umehLUmSJC3PihbbmTk/IiYBNwADgHMy866ImALcmplXA1OBCyNiNlWL9iElc5IkSZLapfhNbTLzOuC6HtMmNwzPAw5aynN8vkhykiRJUkHeQVJSy4059oKmlr9q7UKJSJLUYcXvIClJkiStrCy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEIGdjoBvWDOlG2aXmf45JkFMpEkSVIr2LItSZIkFWKxLUmSJBViNxKpHxpz7AVNr3PV2gUSkSRpJWfLtiRJklSIxbYkSZJUiMW2JEmSVIjFtiRJklSIxbYkSZJUiFcjkSRpJdbsDdW8mZrUHFu2JUmSpEKKF9sRsXdEzIqI2RFxXC/zV4+Iy+r5N0fEiHr6HhExIyJm1n/fXDpXSZIkqZWKFtsRMQA4C9gHGAUcGhGjeiz2PuDJzNwMOB04pZ7+OPBJtLqkAAAX7klEQVT2zNwGOBy4sGSukiRJUquVbtkeB8zOzPsy8zlgGrB/j2X2B86vh68Ado+IyMzbM/ORevpdwKCIWL1wvpIkSVLLlC62NwYeahjvqqf1ukxmzgeeAjboscy7gNsz89lCeUqSJEktV/pqJNHLtGxmmYjYiqpryZ69BoiYCEwEGD58+MvLUpIkSSqgdMt2FzCsYXwo8MjilomIgcC6wBP1+FDgKmBCZt7bW4DMPDszx2bm2CFDhrQ4fUmSJOnlK11sTwc2j4iREbEacAhwdY9lrqY6ARLgQODHmZkRsR5wLXB8Zv6qcJ6SJElSyxUttus+2JOAG4C7gcsz866ImBIR+9WLTQU2iIjZwMeB7ssDTgI2Az4XEb+tHxuWzFeSJElqpeJ3kMzM64Drekyb3DA8Dziol/W+CHyxdH6SJElSKd6uXZIkqQXGHHtBU8vP+NKEQploeeLt2iVJkqRCLLYlSZKkQuxGIhXQ7E+JAFetXSARSZLUUbZsS5IkSYVYbEuSJEmFWGxLkiRJhVhsS5IkSYVYbEuSJEmFWGxLkiRJhVhsS5IkSYV4ne0Gc6Zs0/Q6wyfPLJCJJEmS+gNbtiVJkqRCLLYlSZKkQiy2JUmSpEIstiVJkqRCLLYlSZKkQiy2JUmSpEK89J8kSeqYZi+76yV3taKxZVuSJEkqxJZt9Utjjr2g6XWuWrtAIpIkaaVmy7YkSZJUiMW2JEmSVIjFtiRJklSIxbYkSZJUiMW2JEmSVIjFtiRJklSIxbYkSZJUiMW2JEmSVIg3tVER3lRGkiTJlm1JkiSpGFu2JUmSVnAv5xflGV+aUCAT9WTLtiRJklSIxbYkSZJUiN1IJEnSSmnOlG2aXmf45JkFMlF/ZrHdT3k1EEmSpM4r3o0kIvaOiFkRMTsijutl/uoRcVk9/+aIGNEw7/h6+qyI2Kt0rpIkSVIrFS22I2IAcBawDzAKODQiRvVY7H3Ak5m5GXA6cEq97ijgEGArYG/g6/XzSZIkSSuE0t1IxgGzM/M+gIiYBuwP/L5hmf2Bz9fDVwBnRkTU06dl5rPA/RExu36+mwrnLEmSVJx9xlcOpYvtjYGHGsa7gB0Wt0xmzo+Ip4AN6um/6bHuxuVSbS37TEuSpJWF1/levMjMck8ecRCwV2b+v3r8MGBcZn6kYZm76mW66vF7qVqwpwA3ZeZF9fSpwHWZeWWPGBOBifXolsCsZUj5lcDjy7D+sjK+8VfW+Cvzthvf+Mb3s8f4K2b8TTJzyNIWKt2y3QUMaxgfCjyymGW6ImIgsC7wRB/XJTPPBs5uRbIRcWtmjm3Fcxnf+MZfMWIb3/jGX3njr8zbbvz2xS99NZLpwOYRMTIiVqM64fHqHstcDRxeDx8I/Dir5vargUPqq5WMBDYHbimcryRJktQyRVu26z7Yk4AbgAHAOZl5V0RMAW7NzKuBqcCF9QmQT1AV5NTLXU51MuV84MOZuaBkvpIkSVIrFb+pTWZeB1zXY9rkhuF5wEGLWfdE4MSiCb5YS7qjGN/4xl+hYhvf+MZfeeOvzNtu/DbFL3qCpCRJkrQyK34HSUmSJGllZbGt5UJ9I6OVTkSs2eH4r1pZ970kSe1gsc2i28p3KvZmETE2IlbvUPytImLXiNigA7F3qa+9TmZmJ4q+iHh7RBzT7rh17P2BUyJiww7F3wu4ihdfYrOd8XeMiMPqv6t1IP7m9f/egE5+BjTywKez3P+d0en93un4y0sO7RYRwyJite5Gp4jotzVpv92wvoiILQAyc0EnvmwjYl/gu8CXgPO682lj/H2AS4GPARdExKvaFHeViFgL+BZwfER8EBYV3G17T0bEnsAXqK5401YRsStwCvC9zPxLB+LvWcd/NfCJDsTfj+rElLcAnwQ2aXP8dwBXAMcDpwEf6MSvDBGxQ32wuz107qBzedHubY+InSJi74jYA6r93+b4+3Q3OHRCRKzRqdh1/FdB+/d7Q/zNOxU/It4cEe+PiPd3Koce+bT7f+9twA+ArwHnRsSWmbmwXTVAu7d3pS2260L3txFxCbS/4I6InYFTgcMzczfgSeC4NsZ/E/BV4P9l5juA54Ct2xE7Mxdm5tPA+VSXftw5Ij7WPa8dOdT7/0JgYmb+MCLWjYhNIuIV7YgPjAH+p469UUTsURde65YOHBFvAb4OvIfq+vWvjYg3lo7bEH8D4MPAuzPzcOBvwOiI2DAiBrUp/geAQzPzXcDvgCOBj0XE2qXjN+SxD3AR1evwmajuktvWgjsi1mlHnCXEf139C9c4aG/BERFvBb4JvBn4aH0A2D2v+P6v3+v/Dpxd/8rVVvUvW5Pa8T+3mPj7AGdExGYdir8H8OuIOKoDsfcBzqC6id97IuLQhnnt+t8fFxGvj4ix0L7PnagMA04GJgGTgZuBn0TEVu0ouOtC/2N1o19brJTFdt2CNQn4KPBcRFwEHWnhPjkzb6+H/xMYHO3rTvJn4AOZeUvdurAD1QfvtyLiwDb9w8+n6sJwPjAuIk6LiJPqf8bS7825wPPAq+vi63+Bb1D9wtCO7Z/fMHwFcBTVe/KsiFi/cOwBwITMvAtYE5gFbAVt+6CfD6wB/Gtd7L0JmAB8BfhsG1qY5wNrAd2taucADwJDgH0LxwYWdV07HJiSmROptn/LiLiizqn4F19EHAD8oj7Ia/t3Qd3gMRWYCHwyIj7QxtivA6YAH8zMTwG319M3hPbs//qyt9cA3wO+EhGH1zkUfy3qYu+/gel1Ho3z2lFw7UD1y+Y3M3N2j3nt2P69qX5R/gH150Abi9w1qWqPT2fmqVSf/7Sz6K2LzW8DbwOOjohvtSt2fUD9CHAT8EfgL5n5Zari+8aI2KJko1tUvyJeDnwIeHfbCu7MXCkfwEZUX7ivpHqzX9Tm+AOAdRqGh1J94A+pp23Qxlw+A3y2Hj4SuKw7j8JxXwMcVw9/AvgHcFYbt3s74D6gC3g/1cHnUVRdawYXjr01VZE7DTiynrYpVUvbXm3a/lXqv3sDfwK2aeO+PxCYAfwG+Fw97c3AecB2bYj/QapfNg6jupb/RVSt3ee0cR98Gjisx7RfAN9qQ+wRwC+BH9bvwbHUl4Jt07b/G3BH92tNda+F09sYfxywYz08mOrL/5r6PfG1NsRftf67f73tY6gKj1OofnEcUDD2KOB+ql/1ADYAtmz8/y/9XgDeC5xYD29EVfRNaJi/SsHYb6q/a8dQHWD/Cdijje+9NevPubcBo4EH6u/cXwNXtiH+K6gOMnavx4cDf2nHZx+wGbB9/Z67DPhUj/mfqvfNoFLvQWA3YE/gdcBPqH5lXav0e2+lbNkGyMxHMvPpzHyc6kt2je4W7vqnzX8tHH9BZv6tHg3gr8ATmflYRLwH+GK0qT9dZp6YmV+sh88F1qY9J839k6o17/1Uxc/JwPB2tXBl5u+oWjJPysxvZ9W95RxgfaoPoJKx76Tqq7wDMLKedh/VgdeQkrEbclhY/72eqv/0vm36VYHMvIKqv/YvqFsVM/PHVO+9dvTfvhS4nqrAf0VmvjczvwVsWLJrRbz4vIyHgU9HRON77Z3ABhExqlQOtYXAZzJzD6pzFiYDYyLiRTc6K9jKtQbw9fp/EKr3wOujOmGqWMtavHCezi3A9Pq9fihwfGa+naoP/9ZRdbMrGf/5etIdwAGZOYOqpfdjwMAse7fkNaiKrYV1C+9lVK38p0XE1+r8Snfn6QLWq7sTfB94A1UL67Q6fsnuhK+g+kVjRmY+BnwRODQKd+FreO2fAX4LHEH1uXt5Zo7PzJ2BYY1dSkqlAvyd6tdtMnMO1a/LO0TEl4sFfeEctVOBE4CLgQ9FxPENi10OPJuZ81r9HozqYhTbArcBMzLzNqquu+8Cjmho4S7Tu6D0kcyK8qBq4T4X+ANVC8PQDuRwHnASVYtfW1oZ6XH0WL/xZgCvalP8KcAc4O31+G7AsA6+D7q3/1/aEGsgVfeB+4D31Y9bgdd0aLt/ScEWtcXE3af+v9sT2I/qg3BEG+Ov0jA8gap1ac1Csfal+vVmWsO0LwAPAcMbpk0DdiiUwxYNw+s2DH+OqmV3+3q8yOdPj/jdv+INoCqAruGFX/s2L7j/L+0xffUe41OBnQvGv6Rh2vpUfXcPpjro+SxVF7fxhff964HTgXupGjqCqoHl/4A3tOG13w64mupX1Y83TL8JOLpQ/C17jHf/sjeuzmWTxumFXvvG//1X1J85b2mY9t/AgW3Y/5+nOuA5iOog70yqX1a/DaxXIPbOVLXVv9XjZ1Md5GxE9f3/WapW7yOovgPXL7D/7wB+SlXkN/6KsyPwY+AQqq6cF1Id8LZ2H5R4UVfUB1WrQlt/Tq/jBrBa/cE3p8QXTR9yWJ2q2LsL2LqNcYcBYxrGi/182IfX4Kj6C2+rNsd+HfBfwJfb/d7rkcfltLHQrWOuBxwN/Ay4gTZ0IVlMHt2vfakic02qlvSJVAfVlzbM+wLVSZofqIuPu4GRBXJ4SbEJrNYw/DngEqpfmO4ANiwUv7Hg6C54VgGuA9ah6tpzdSu/cHvZ/xc1zBvYMHwAMJ268GpT/JOBZ4F31eO7Apu1Yd+PA97ZY7nzqLvXtOG990GqhoavUR/4UXUjOLJN8Rtf96nANa2Ou5jXvvFg63Cq7/xx9fzbaSiKC2z/ZQ3TjqEqck/hhW5N3wNeXSD+zsARDeNDgGvr4U2Bc6hO2r+VFn8G89JC/+vUXWZ44S7qw4BHqRo+ti3xPvB27bX6pLTLgU9k5h0dyuEIqhNW7upA7FWBPYB7M3NWB+JHdvDNWP90vSvwp8z8Q6fy6IRO7/s6h7WpPvj+ttSFy8TfhOoLZ/ZSF375MTaiuvLKIKq++c9n5qH1vHdSnag1BvhKVt2MWhl7TeBKqp9xd6YqNN5bz1s9M5+th38KbEF13sDMNsUfQHWweynwFFU/1gmZ2dJLcvay/+c15LAqVbFzFNUVolq6/xcT/7nMfHfdlWWzzLynxP9iL/t+tcx8dz1vjcz8Zz38Lqqf1Q/MzAfbFP/9VOdv/ICqlf9gqgOAln0G9+W9HxGvpGptPS0zf9mq2A059Hztn83M99TzPge8lupA87g2/O+v3v2502O591IdAL0jq+61rcxhANUvhn+rh19N9UvWWzPz0frz9+F6madaHHtnqgOY8+rxIVQt+OOpPoMX1stcB7y+VP1lsd0gIgZljzOz2xy/40WPpPLqK+CcTVVwHRoRWwFPt7LI6SXmYovNev4WVP13j8gX+lK3M/7/UhX67yx9wN+w//+Zme+tz9HZi6q1rdgB1xLij6YqwO4uFG+xxV49/3Cqn9CPbNOBRuOB5i5UhfYOwIUlXvs+vPdeQXVFsNMz80+tjt8jl+7X/vnMPCQiNqUqtH+fmc8VitnrgV49byDV+TNTqE6a/W2JHBpyGVjn8b3M3L0u8t8AfLT7wK/F8RZX6O+Z1TlyG1GdIDwnM+9tdfxFeVjbSVL71a1pX6JqbRoAvCkzu9oUu7dir/sLv6WtWn2MvznVlZAuanWL9hJyaNz/AbyxdKG1mPg7Ub3+u7Xj9e9l37+W6lyZ67M6Sbtd8bsPNLcF5mbmw6Vj94jfvf1jqfov/yXbd5+H7tf+9VTvvba89nXsntu/NVVXjlva/P4/j6rrxp5UB/gt+yVtCTF7FvrvoTrIOz6rE1eLWWmvRiJJnVQXtXdQ3djine36sq1jz6XqI/58RPwB+A4wux2Fdi/x7wGuBb7arkK7zqFx/7+rnYVGj/jrUV2RpC2vf499P4uqn+5V7Si0e8SfV8f/LlXB2Ra9vPenUXUtaUuhXefQ/dqvQxtf+zp2z9f/KuDWdr3/6yterUbVmv0e4JB2FNoAmTk/qxvqPRQRJwEfp7q5XNFCGyy2Jakj6vNE3kr1c2Zbvmwa9VLsPdKh+OtQFbt/bmf8Tu//Tsbv5UDj0Q7Gb+uBZo/463Uifqffez32f1v/97PyHNWJ4ftk5h/bFXsxhX5bztGzG4kkdUgnzxPp9EnhnY5f59Dp83Q6Er/T+35lj1/nsNL+79c5dOwctU5cjMJiW5JWUitrsanO7/uVPX6nrczb34lC32JbkiRJKsQ+25IkSVIhFtuSJElSIRbbkiRJUiEW25IkSVIhFtuStBgRMSIiWn776l7iHFHfNrhfxOmrOp8z2xjvgfrufYubf3RE3B0RF7crJ0n9n8W2JHVQRAwAjgDaUQS3K86L1Nu4IvgQ8NbMfE/jxPo2z5L0slhsS1ru1S3Md0fEtyPiroi4MSLWiIifRsTYeplXRsQD9fAREfG/EXFNRNwfEZMi4uMRcXtE/CYiBi8h1piI+F1E3AR8uGH6gIj4UkRMj4g7IuID9fQ3RcTPI+KqiPh9RHwzIlap530jIm6tcz6h4bkeiIjJEfFL4FBgLHBxRPy23q4HIuK/IuKmev3XRcQNEXFvRHyw4XmObcjnhKXsqwN7iXNynfMdEXHqEvbJefV2/SIi7omIfRv285kNy30/It5UDz8dEVMi4mZgp4jYPiJ+Xe/bWyJi7Xq1jSLi+oj4Y0T8d8NzLW7fvSTniBgSEVfW+2J6RLy+nr5Bvf23R8S3WMJtwSPim8CmwNUR8bGI+HxEnB0RNwIXRMSgiDg3ImbWz7dbwz54We81SSuJzPThw4eP5foBjADmA6Pr8cuB9wI/BcbW014JPFAPHwHMBtYGhgBPAR+s550OfHQJse4Adq2HvwTcWQ9PBD5bD68O3AqMBN4EzKMq1AYAPwQOrJcbXP8dUOe6bT3+APCphpiLtqNh/r835HtHw7b8pZ6+J3A2VQG5CvB94I2L21c94wCDgVm8cL+F9ZawT84Drq/jbA50AYPq/Xxmw3LfB95UDydwcD28GnAfsH09vg4wsF7/PqrbRg8CHgSGLW7fLS5n4BJgl3p4OHB3PXwGMLkeflud0yuXsJ0PdM8HPg/MANaoxz8BnFsP/yswp2EfvKz3mg8fPlaOhy3bklYU92fmb+vhGVRF5ZL8JDP/npmPURVA19TTZy5u3YhYl6qA+1k96cKG2XsCEyLit8DNwAZUhSfALZl5X2YuAC4FdqmnHxwRtwG3A1sBoxqe77Kl5H91Q743N2zLvIhYr85nz/q5b6MqALvz6cu++hvVQcL/RMQBwD+Wks/lmbkwM/9IVSD/61KWXwBcWQ9vCTyamdMBMvNvmTm/nvejzHwqq7vZ/R7YpJ7e275bXM5vAc6sX5urgXXqlvM3AhfVMa8FnlxKzj1dnZn/rId3oX4/ZOYfqA4MtqjnNf1ek7TysB+apBXFsw3DC4A1qFpwuxsNBi1h+YUN4wtZ/GdfULV+Lm7eRzLzhhdNrLpN9FwnI2Ik8Emq1twnI+K8Hjk+s5g4PfNvzL0x/wBOysxv9chnBL3vqxcnmDk/IsYBuwOHAJOANy8hn5dsIy/e//Di7ZtXH3zAkvdrz1wHLm7fLSHnVYCdGgrjKmhEb3k3o/E1WmwXFF7ee03SSsKWbUkrsgeAMfXwgcv6ZJn5V+CpiOhumW48Ue4G4N8jYlWAiNgiItas542LiJF1X+3xwC+puko8Uz/fvwD7LCH036m6ITTjBuCoiFirzmfjiNhwKessilOvt25mXgd8FBi9lHUPiohVIuI1VF1mZlHt/9H19GHAuMWs+weqvtnb17HXjiWfdNjrvltCzjdSFd7Uy3VP/zn1axgR+wDrL2Ubl6Txubag6q4yaxmeT9JKwiNuSSuyU4HLI+Iw4Mctes4jgXMi4h9UBW23/6HqEnBbVE2mjwHvqOfdBJwMbENVlF2VmQsj4nbgLqpuF79aQszzgG9GxD+BnfqSZGbeGBGvBW6qW3CfpurHvmAJqzXG2Qf4XkQMomq1/dhSQs4Cfgb8C1Wf5HkR8SvgfqruEndSdWfpLdfnImI88LWIWAP4J1XXj8Vt2+8Ws+/WXkzORwNnRcQdVN9rPwc+CJwAXFp3R/kZVT/rl+vrVPtuJlWL/hGZ+Wy97yVpsbpPMpEkvQx1N5JPZua+nc6llLobx/cz84pO5yJJKxq7kUiSJEmF2LItaaUUEWcBr+8x+auZeW4n8lkeRMRngIN6TP5OZp7YiXxKiIgNgB/1Mmv3zJzb7nwk9X8W25IkSVIhdiORJEmSCrHYliRJkgqx2JYkSZIKsdiWJEmSCrHYliRJkgr5/0Gpypvu+hcaAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def get_num_unique_dept_purchases(data):\n", " num_unique_dept = data.groupby([\"user_id\"])[\"department\"].aggregate(\"nunique\").reset_index()\n", " num_unique_dept.columns = [\"user_id\", \"num_departments_purchased_from\"]\n", " return num_unique_dept\n", "\n", "num_unique_dept = get_num_unique_dept_purchases(merged_data) # Feature\n", "plot_group_proportions(num_unique_dept, final_order_data, \"num_departments_purchased_from\", 0, False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### From the plots above we can see that the number of unique departments purchased from differs in distribution for shoppers in the vegetarian/not groups. This implies that this feature could be useful for our model.\n", "\n", "## User's department re-order rate: i.e. proportion of orders from that department that are re-orders: correlation between departments" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dept_reorder_rate = get_dept_reorder_rate(merged_data) # Feature\n", "plot_correlations(dept_reorder_rate,\"reord_rt_dept\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Again, we see some correlation, but nothing too strong.\n", "\n", "## Number of times reordered from department" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "image/png": 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rVPuTTf28kcpPSekt8qW0o8l+EbxDNpX0L7RciTY21TG4qNxWdZU4vq3OSanzwZbVk73S+x7pM3iVbJTmIbJ78xWfi/HpHLyT9g0odc5K9YdsOu1D4KyiPDeTBU77tnJcp5JNhffMpZVtt6hsH7JbUPwqfd8Kt24ZnctzNtk1dJvIAvg/Kz6XZT7LjwN3Az8nWzSxlmyhziFF+c4gGwkqtH8j8LFyn0eFz/M/KFqRWu13IaVPJlsA8x5ZcPvVov1TKLGKskwbu5H9f3o19X9GK9+5rT4vsus2v0IWbL1Ldt3ZInKriFtpu3c650HpW6d8nGyUtHCsvyMLkP5HUf/vIPtZ9Hvgu+n411XR/ump7nfIRtXHkbvtTmufQTXfiZTnuHRu3gZ+QhY0llrNemvq9ytki4tmAX2L6vro55Jf3eul9AGamXVradXtGrLbkxSvAtxppJHAV4BxEdGZ0/I7LGVPEdklItp0zaikvya7B+WfRMuV49uUpGayPzKu3F5t2vblaVYz2yFENsV7M3AZW9/SYWcyCVjqQK42JP0l2SjsM2QrTM8gGznf6okXJcreQTad+3uyW41cC/xwewZytnNwMGdmO5LvAbtL6hMR5W5nsaNbT+nn01r7vEW24vXrZFOuvyC76e+DrZbK9CO7RKIf2XW9c8hu/GtWU55mNTMzM+vGfGsSMzMzs27MwZyZmZlZN+Zr5nY+nlc3M7PuTpWz7Dw8MmdmZmbWjTmYMzMzM+vGHMyZmZmZdWMO5szMzMy6MQdzZmZmZt2YgzkzMzOzbszBHCCpQdLwGtc5QNLKDpS/poo890p6tSPtmJmZWffW7YI5SR26N15Hy6c6enS0jipUDOaAGcCx27gfZmZm1oW1O5hLI08vSrpb0guSFkjqmR/lktRfUnPanijpEUnzJK2WNFnS5ZKelbRU0l6ttNUg6SZJi4DLJO0t6SFJT6XX6JRvr9RGU6pzSEqfIqle0gJgZurn7JRvDtAz19Z4SY2SnpH0gKReKb1Z0nWSlgCnlennMEnPSWoELs6l95B0c+prk6QLU/pYSYslPSxplaQ7JdVJmgr0lLRC0v3lzktELAbeqObzMjMzsx1TR0fmDgCmRcTBwDrglAr5BwNnASOBG4G3I+JQoBE4u0LZvhFxZETcCtwO3BYRI1Kb96Q81wPPRsQQspGtmbnyw4ATI+IsYFJqe0jqxzDIgk/gWmBcRBwGLAcuz9XxTkSMiYjZZfo4Hbg0IkYVpZ8HrE/9HQGcL2lg2jcSuAI4BNgPODkirgY2RcTQiJhQ4byYmZnZTqyjwdzqiFiRtp8GBlTI/3hEbIiI14D1wLyU/nwVZefktscB35O0ApgL7CmpNzAGuA8gIhYC/ST1SWXmRsSmtH0E8L9TviagKaUfDgwCnkh1nwP8cZk+tJDa6RsRi1LSfbnd44GzU50/BfqRBcIAyyLi5Yj4EJiVjqGmJF0gabmk5fX19bWu3szMzDpRR68feze3/SHZdOUHbAkSd2sl/+bc+81V9GVjbrsOGJULzgCQVOpZbYVnkW4sk96iCuDRiDizij6UKlvuuacCLomI+S0SpbElytT82akRUQ8Uojg/m9XMzGwHsi0WQDSTpi2BU7dB/QALgMmFN5KGps3FwISUNhZYGxFvliifzzcYGJLSlwKjJe2f9u0u6cBqOhQR64D1kgoja/np0fnAJEm7pHoPlLRH2jdS0kBJdcAZwJKU/n4hv5mZmVk52yKYu4UscHkS6L8N6ge4FBieFhOsAi5K6VMK6cBUsmnSUu4AeqV8VwHLANL070RgVtq3FPhsG/p1LjAtLYDIjxreA6wCnkm3EbmLLSORjamvK4HVwMMpvR5oam0BhKRZqfxBktZIOq8NfTUzM7MdgCI869ZZ0ujhlRFx/HZs1h+4mZl1d6Uuq9ppdbv7zJmZmZnZFl1qZE7SNGB0UfLtETG9M/pTzvbsp6R+wGMldh0dEa+3o8qu84GbmZm1j0fmcrpUMGfbhT9wMzPr7hzM5Xia1czMzKwbczBnZmZm1o05mDMzMzPrxjr6BAjrht554Wc1q2u3g9tyGz4zMzOrNY/MmZmZmXVjDubMzMzMujEHc2ZmZmbdmIM5MzMzs27MwZyZmZlZN7ZTBXOSGiQNr3GdAySt7ED5a6rIc6+kV4vbkbSXpEcl/SL9+4n29sPMzMy6py4bzEnq0G1TOlo+1dGjo3VUoWIwB8wAji2RfjXwWEQcQPb81qtr2C8zMzPrBioGc2nk6UVJd0t6QdICST3zo1yS+ktqTtsTJT0iaZ6k1ZImS7pc0rOSlkraq5W2GiTdJGkRcJmkvSU9JOmp9Bqd8u2V2mhKdQ5J6VMk1UtaAMxM/Zyd8s0BeubaGi+pUdIzkh6Q1CulN0u6TtIS4LQy/Rwm6TlJjcDFufQekm5OfW2SdGFKHytpsaSHJa2SdKekOklTgZ6SVki6v9x5iYjFwBsldp0I/Fva/jfgpHJ1mJmZ2Y6p2pG5A4BpEXEwsA44pUL+wcBZwEjgRuDtiDgUaATOrlC2b0QcGRG3ArcDt0XEiNTmPSnP9cCzETGEbGRrZq78MODEiDgLmJTaHpL6MQyy4BO4FhgXEYcBy4HLc3W8ExFjImJ2mT5OBy6NiFFF6ecB61N/RwDnSxqY9o0ErgAOAfYDTo6Iq4FNETE0IiZUOC+l/GFE/BYg/fsHpTJJukDScknL6+vr29GMmZmZdVXVTkWujogVaftpYECF/I9HxAZgg6T1wLyU/jwwpELZObntccAgSYX3e0rqDYwhBZQRsVBSP0l9Up65EbEpbR8BfDfla5LUlNIPBwYBT6S6dyULNEv1oYXUTt+IWJSS7gOOS9vjgSGSTk3v+5AFwu8ByyLi5VTHrHQMD1Y4FzUREfVAIYqLWj4BwszMzDpXtcHcu7ntD8mmKz9gy8jebq3k35x7v7mKNjfmtuuAUbngDADlorucKFE+n96iCuDRiDizij6UKluqzsK+SyJifotEaWyJMuXqaItXJO0TEb+VtA/wag3qNDMzs26kIwsgmknTlsCpreTriAXA5MIbSUPT5mJgQkobC6yNiDdLlM/nG8yWUcGlwGhJ+6d9u0s6sJoORcQ6YL2kMSkpPz06H5gkaZdU74GS9kj7RkoaKKkOOANYktLfL+Rvh7nAOWn7HOA/2lmPmZmZdVMdCeZuIQtcngT616g/xS4FhqfFBKuAi1L6lEI6MJUtAU2xO4BeKd9VwDKAiHgNmAjMSvuWAm15Yvy5wLS0ACI/angPsAp4Jt1G5C62jEQ2pr6uBFYDD6f0eqCptQUQaVq2EThI0hpJ56VdU4FjJP0COCa9NzMzs52IImox22etSaOHV0bE8Z3dF2p8zdxuB7clBjYzM6uJUpdb7bS67H3mzMzMzKyyDt9Ytz0kTQNGFyXfHhHTO6M/5dSqnxHRADRUaKsf2Y1/ix0dEa+3pT0zMzPbeXiadefjaVYzM+vuPM2a42lWMzMzs27MI3M7H3/gZmbW3XlkLqdTrpmzzvX7+79fs7o+MeF0Pnhtbc3qA/jY3tvqTjdmZmY7Hk+zmpmZmXVjDubMzMzMujEHc2ZmZmbdmIM5MzMzs27MwZyZmZlZN+ZgzszMzKwb26mCOUkNkobXuM4BklZ2oPw1VeS5V9Krxe1IOk3SC5I21/q4zMzMrHvossGcpA7dA6+j5VMdPTpaRxUqBnPADODYEukrgZOBxbXskJmZmXUfFYO5NPL0oqS70yjQAkk986NckvpLak7bEyU9ImmepNWSJku6XNKzkpZK2quVthok3SRpEXCZpL0lPSTpqfQanfLtldpoSnUOSelTJNVLWgDMTP2cnfLNAXrm2hovqVHSM5IekNQrpTdLuk7SEuC0Mv0cJuk5SY3Axbn0HpJuTn1tknRhSh8rabGkhyWtknSnpDpJU4GeklZIur/ceYmIxcAbJdJfjIiflytnZmZmO75qR+YOAKZFxMHAOuCUCvkHA2cBI4Ebgbcj4lCgETi7Qtm+EXFkRNwK3A7cFhEjUpv3pDzXA89GxBCyka2ZufLDgBMj4ixgUmp7SOrHMMiCT+BaYFxEHAYsBy7P1fFORIyJiNll+jgduDQiRhWlnwesT/0dAZwvaWDaNxK4AjgE2A84OSKuBjZFxNCImFDhvLSbpAskLZe0vL6+fls1Y2ZmZp2g2qnI1RGxIm0/DQyokP/xiNgAbJC0HpiX0p8HhlQoOye3PQ4YJH30CLY9JfUGxpACyohYKKmfpD4pz9yI2JS2jwC+m/I1SWpK6YcDg4AnUt27kgWapfrQQmqnb0QsSkn3Acel7fHAEEmnpvd9yALh94BlEfFyqmNWOoYHK5yLmoiIeqAQxUUtH+dlZmZmnavaYO7d3PaHZNOVH7BlZG+3VvJvzr3fXEWbG3PbdcCoXHAGgHLRXU7hAfIby6S3qAJ4NCLOrKIPpcqWe1i9gEsiYn6LRGlsiTJ+4L2ZmZl1WEcWQDSTpi2BU1vJ1xELgMmFN5KGps3FwISUNhZYGxFvliifzzeYLaOCS4HRkvZP+3aXdGA1HYqIdcB6SWNSUn56dD4wSdIuqd4DJe2R9o2UNFBSHXAGsCSlv1/Ib2ZmZtZWHQnmbiELXJ4E+teoP8UuBYanxQSrgItS+pRCOjAVOKdM+TuAXinfVcAygIh4DZgIzEr7lgKfbUO/zgWmpQUQ+VHDe4BVwDPpNiJ3sWUksjH1dSWwGng4pdcDTa0tgEjTso3AQZLWSDovpX9R0hpgFPBDSfPL1WFmZmY7JkV4tm9bS6OHV0bE8Z3dF2p8zdwnJpzOB6+trVl9AB/be1v9bWBmZjuIUpdb7bS67H3mzMzMzKyyDt9Ytz0kTQNGFyXfHhHTO6M/5dSqnxHRADRUaKsf8FiJXUdHxOttac/MzMx2Hp0SzEXExZVzdb7t2c8UsA2tmNHMzMwsx9OsZmZmZt2YF0DsfPyBm5lZd+cFEDmdMs1qnWvN5P9Vs7r2/d7NbFiwsGb1AfQefxRr77y3ZvX1v+jLNavLzMysq/E0q5mZmVk35mDOzMzMrBtzMGdmZmbWjTmYMzMzM+vGHMyZmZmZdWMO5szMzMy6sZ0qmJPUIGl4jescIGllB8pfU0WeeyW9WtyOpBskNUlaIWmBpE+1tx9mZmbWPXXZYE5Sh+6B19HyqY4eHa2jChWDOWAGcGyJ9JsjYkhEDAV+AFxXy46ZmZlZ11cxmEsjTy9KulvSC2kEqGd+lEtSf0nNaXuipEckzZO0WtJkSZdLelbSUkl7tdJWg6SbJC0CLpO0t6SHJD2VXqNTvr1SG02pziEpfYqkekkLgJmpn7NTvjlAz1xb4yU1SnpG0gOSeqX0ZknXSVoCnFamn8MkPSepEbg4l95D0s2pr02SLkzpYyUtlvSwpFWS7pRUJ2kq0DONrN1f7rxExGLgjRLpb+be7oGf7mBmZrbTqXZk7gBgWkQcDKwDTqmQfzBwFjASuBF4OyIOBRqBsyuU7RsRR0bErcDtwG0RMSK1eU/Kcz3wbEQMIRvZmpkrPww4MSLOAialtoekfgyDLPgErgXGRcRhwHLg8lwd70TEmIiYXaaP04FLI2JUUfp5wPrU3xHA+ZIGpn0jgSuAQ4D9gJMj4mpgU0QMjYgJFc5LSZJulPQrYAJlRuYkXSBpuaTl9fX17WnGzMzMuqhqpyJXR8SKtP00MKBC/scjYgOwQdJ6YF5Kfx4YUqHsnNz2OGCQ9NEj2PaU1BsYQwooI2KhpH6S+qQ8cyNiU9o+AvhuytckqSmlHw4MAp5Ide9KFmiW6kMLqZ2+EbEoJd0HHJe2xwNDJJ2a3vchC4TfA5ZFxMupjlnpGB6scC4qiohvAN+Q9HVgMvB3JfLUA4UoLmr5OC8zMzPrXNUGc+/mtj8km678gC0je7u1kn9z7v3mKtrcmNuuA0blgjMAlIvucgpTjBvLpLeoAng0Is6sog+lypabzhRwSUTMb5EojS1RptZTov8H+CElgjkzMzPbcXVkAUQzadoSOLWVfB2xgGy0CQBJQ9PmYrJpxUKgtLbo+jFK5BvMllHBpcBoSfunfbtLOrCaDkXEOmC9pDEpKT89Oh+YJGmXVO+BkvZI+0YivO9GAAAgAElEQVRKGiipDjgDWJLS3y/kbytJB+TengD8rD31mJmZWffVkWDuFrLA5Umgf436U+xSYHhaTLAKuCilTymkA1OBc8qUvwPolfJdBSwDiIjXgInArLRvKfDZNvTrXGBaWgCRHzW8B1gFPJNuI3IXW0YiG1NfVwKrgYdTej3Q1NoCiDQt2wgcJGmNpPPSrqmSVqZjGA9c1oZjMDMzsx2AIrwAcltLo4dXRsTxnd0XanzN3L7fu5kNCxbWrD6A3uOPYu2d99asvv4XfblmdZmZWZdQ6nKrnVaXvc+cmZmZmVXW4RvrtoekacDoouTbI2J6Z/SnnFr1MyIagIYKbfUDHiux6+iIeL0t7ZmZmdnOo1OCuYi4uHKuzrc9+5kCtqEVM5qZmZnl+Jq5nY8/cDMz6+58zVyOr5kzMzMz68Y6ZZrVOte6h+bWrK6+p5zApudW1qw+gJ6fG8xbCxfXrL5eRx0BwG+/eWPN6tznhm/UrC4zM7OO8MicmZmZWTfmYM7MzMysG3MwZ2ZmZtaNOZgzMzMz68YczJmZmZl1YztVMCepQdLwGtc5QFK7l3NKuqaKPPdKerVcO5KulBSS+re3H2ZmZtY9ddlgTlKHbpvS0fKpjh4draMKFYM5YAZwbKkdkv4IOAb47xr2yczMzLqJisFcGnl6UdLdkl6QtEBSz/wol6T+kprT9kRJj0iaJ2m1pMmSLpf0rKSlkvZqpa0GSTdJWgRcJmlvSQ9Jeiq9Rqd8e6U2mlKdQ1L6FEn1khYAM1M/Z6d8c4CeubbGS2qU9IykByT1SunNkq6TtAQ4rUw/h0l6TlIjcHEuvYekm1NfmyRdmNLHSlos6WFJqyTdKalO0lSgp6QVku4vd14iYjHwRpndtwFX4Sc7mJmZ7ZSqHZk7AJgWEQcD64BTKuQfDJwFjARuBN6OiEOBRuDsCmX7RsSREXErcDtwW0SMSG3ek/JcDzwbEUPIRrZm5soPA06MiLOASantIakfwyALPoFrgXERcRiwHLg8V8c7ETEmImaX6eN04NKIGFWUfh6wPvV3BHC+pIFp30jgCuAQYD/g5Ii4GtgUEUMjYkKF87IVSScAv46I5yrku0DScknL6+vr29qMmZmZdWHVTkWujogVaftpYECF/I9HxAZgg6T1wLyU/jwwpELZObntccAg6aNHsO0pqTcwhhRQRsRCSf0k9Ul55kbEprR9BPDdlK9JUlNKPxwYBDyR6t6VLNAs1YcWUjt9I2JRSroPOC5tjweGSDo1ve9DFgi/ByyLiJdTHbPSMTxY4VyUJWl34BupzVZFRD1QiOKilk+AMDMzs85VbTD3bm77Q7Lpyg/YMrK3Wyv5N+feb66izY257TpgVC44A0C56C6nMM24sUx6iyqARyPizCr6UKpsuSlNAZdExPwWidLYEmU6Oi26HzAQeC6djn2BZySNjIjfdbBuMzMz6yY6sgCimTRtCZzaSr6OWABMLryRNDRtLgYmpLSxwNqIeLNE+Xy+wWwZFVwKjJa0f9q3u6QDq+lQRKwD1ksak5Ly06PzgUmSdkn1Hihpj7RvpKSBkuqAM4AlKf39Qv62iIjnI+IPImJARAwA1gCHOZAzMzPbuXQkmLuFLHB5EthWt8S4FBieFhOsAi5K6VMK6cBU4Jwy5e8AeqV8VwHLACLiNWAiMCvtWwp8tg39OheYlhZA5EcN7wFWkY2QrQTuYstIZGPq60pgNfBwSq8HmlpbAJGmZRuBgyStkXReG/pqZmZmOzBFeBHktpZGD6+MiOM7uy/U+Jq5vqecwKbn2n2bvZJ6fm4wby1cXLP6eh11BAC//eaNNatznxu+UbO6zMyszUpdbrXT6rL3mTMzMzOzyjp8Y932kDQNGF2UfHtETO+M/pRTq35GRAPQUKGtfsBjJXYdHRGvt6U9MzMz23l0SjAXERdXztX5tmc/U8A2tGJGMzMzsxxPs5qZmZl1Y14AsfPxB25mZt2dF0DkdMo0q3WuX3/l6zWr69P/9A9sbFxWs/oA9hg1kg0LFtasvt7jjwJg9amVniRXvYEPZk+Qe/PHj9aszj2PO6ZmdZmZ2c7D06xmZmZm24mkYyX9XNJLkq4usX+ipNckrUivv61Up0fmzMzMzLYDST2AacAxZE9uekrS3IhYVZR1TkRM3qqCMjwyZ2ZmZrZ9jAReioiXI+I9YDZwYkcrdTBnZmZmtn18GvhV7v2alFbslPQo0wcl/VGlSj3NamZmZtaKX4z5q6rvBHHgEwsuBC7IJdVHRH3aLrUKt7juecCsiHhX0kXAvwFHtdamgzkzMzOzGkmBW32Z3WuA/EjbvsBvisrnn/p0N/DtSm3uVNOskhokDa9xnQMktftJ85KuqSLPvZJeLW5H0hRJv86tePl8e/thZmZmZaiu+lfrngIOkDRQ0q7Al4C5LZqS9sm9PQF4sVKlXTaYk9ShUcOOlk919OhoHVWoGMwBM4Bjy+y7LSKGptePatctMzMzq6WI+ACYDMwnC9K+HxEvSPp7SSekbJdKekHSc8ClwMRK9VYMeCQNAH4MLAH+HPg12cqLHwNXRsRySf2B5RExQNJE4CSgBzAYuBXYFfgb4F3g8xHxRpm2GoAnyR5uP1fSTOBO4DMpy1ci4glJewH3An8CvA1cEBFNkqYAnwIGAGslnQdMBwaRnbSeubbGA9cDHwd+CZwbEW9Jak51jwe+R7bSpLifw1Ket9N5KaT3AKYCY1O90yLiLkljgb8HXgcOAhYD/xO4CegpaQXwQkRMKHVeImJx+hzMzMxse1PtHjiRBl5+VJR2XW7760Cb7u5f7cjcAWSBycHAOuCUCvkHA2eRLcG9EXg7Ig4FGoFKt+HvGxFHRsStwO1kI08jUpv3pDzXA89GxBCyka2ZufLDgBMj4ixgUmp7SOrHMIAUfF4LjIuIw4DlwOW5Ot6JiDERsVUgl0wHLo2IUUXp5wHrU39HAOdLGpj2jQSuAA4B9gNOjoirgU1pVK1kIFeFyWnFy72SPlEqg6QLJC2XtLy+vtw0vpmZmZWiOlX96gzVTkWujogVaftpspGv1jweERuADZLWk63MAHgeGFKh7Jzc9jhgkLZExHtK6g2MIQWUEbFQUj9JfVKeuRGxKW0fAXw35WuS1JTSDycbrXsi1b0rWaBZqg8tpHb6RsSilHQfcFzaHg8MkXRqet+HLBB+D1gWES+nOmalY3iwwrmo5A7gBrKVMDeQjYJ+uThT0cWYUcvHeZmZmVnnqjaYeze3/SHZdOUHbBnZ262V/Jtz7zdX0ebG3HYdMCoXnAEglRzvLCzt3VgmvUUVwKMRcWYVfShVttwSZQGXRMT8FonZNGtxmQ4/8D4iXsm1cTfwg47WaWZmZkUqL2zoVB3pXTNp2hI4tZV8HbGA7EJBACQNTZuLgQkpbSywNiLeLFE+n28wW0YFlwKjJe2f9u0u6cBqOhQR64D1ksakpPz06HxgkqRdUr0HStoj7RuZVq/UAWew5Vq79wv526poxcsXgXavqjUzM7PuqSPB3C1kgcuTQP8a9afYpcDwdE3YKuCilD6lkE624OCcMuXvAHqlfFcBywAi4jWy1SGz0r6lwGfb0K9zgWmSGoH8qOE9wCrgmXQbkbvYMhLZmPq6ElgNPJzS64EmSfeXayxNyzYCB0lakxZ2AHxH0vPpGP4S+GobjsHMzMyqIVX/6ozuRXR4ts8qSKOHV0bE8Z3dF2p8zdyn/+kf2Ni4rGb1AewxaiQbFiysWX29x2c3zl59aqW1N9Ub+GC25ubNHz9aszr3PO6YmtVlZraD265R00tHnVB1sLT/wrnbPaLzEyDMzMzMWtNJq1Sr1SnBnKRpZPeSy7s9IqZ3Rn/KqVU/I6IBaKjQVj/gsRK7ji56tIeZmZltR6XXXXYdnRLMRcTFndFuW23PfqaAbWjFjGZmZmY5nmY1MzMza01d1741iRdA7Hz8gZuZWXe3Xec9f/lXJ1f9u3O/+f/uBRC27f3uhu/UrK5PfvMq3vrJkzWrD6DXX/w56x+p3f2P+5yULSJu/tJWD8dotwGz7wXgl8fV7haL+/34QV6/Z2bljFXq97e1W71rZrZT8zVzZmZmZt1YFw/muvYksJmZmZm1yiNzZmZmZq1QF18A0bV7Z2ZmZmat8sicmZmZWWu6+MicgzkzMzOz1ngBRNchqUHS8BrXOUDSyg6Uv6aKPPdKerVUO5IukfRzSS9Iqt09R8zMzKxb6LLBnKQOjRp2tHyqo0dH66hCxWAOmAEcW5wo6S+BE4EhEXEwcEttu2ZmZmaSqn51horBXBp5elHS3Wn0Z4GknvlRLkn9JTWn7YmSHpE0T9JqSZMlXS7pWUlLJe3VSlsNkm6StAi4TNLekh6S9FR6jU759kptNKU6h6T0KZLqJS0AZqZ+zk755gA9c22Nl9Qo6RlJD0jqldKbJV0naQlwWpl+DpP0nKRG4OJceg9JN6e+Nkm6MKWPlbRY0sOSVkm6U1KdpKlAT0krJN1f7rxExGLgjRK7JgFTI+LdlO/VcnWYmZnZjqnakbkDgGlp9GcdcEqF/IOBs4CRwI3A2xFxKNAIVLotfd+IODIibgVuB26LiBGpzXtSnuuBZyNiCNnIVv62+cOAEyPiLLJg5+2U78a0D0n9gWuBcRFxGLAcuDxXxzsRMSYiZpfp43Tg0ogYVZR+HrA+9XcEcL6kgWnfSOAK4BBgP+DkiLga2BQRQyNiQoXzUsqBwF9I+qmkRZJGlMok6QJJyyUtr6+vb0czZmZmO7E6Vf/qBNVORa6OiBVp+2lgQIX8j0fEBmCDpPXAvJT+PDCkQtk5ue1xwKDcsOWeknoDY0gBZUQslNRPUp+UZ25EbErbRwDfTfmaJDWl9MOBQcATqe5dyQLNUn1oIbXTNyIWpaT7gOPS9nhgiKTCM576kAXC7wHLIuLlVMesdAwPVjgXlXwM+EQ6nhHA9yX9SRQ9cDci6oFCFBe1fJyXmZmZda5qg7l3c9sfkk1XfsCWkb3dWsm/Ofd+cxVtbsxt1wGjcsEZACo9KV0IYDaWSW9RBfBoRJxZRR9KlS33wF0Bl0TE/BaJ0tgSZWrxwPs1wL+n4G2ZpM1Af+C1GtRtZmZmAOqySwyAji2AaCZNWwK1e9p4SwuAyYU3koamzcXAhJQ2FlgbEW+WKJ/PN5gto4JLgdGS9k/7dpd0YDUdioh1wHpJY1JSfnp0PjBJ0i6p3gMl7ZH2jZQ0UFIdcAawJKW/X8jfDo8ARxXaIhthXNvOuszMzKyULj7N2pFg7haywOVJstGgbeFSYHhaTLAKuCilTymkA1OBc8qUvwPolfJdBSwDiIjXgInArLRvKfDZNvTrXGBaWgCRHzW8B1gFPKPsNiJ3sWUksjH1dSWwGng4pdcDTa0tgEjTso3AQZLWSDov7boX+JPU1mzgnOIpVjMzM9uxVZxmjYhmsgUNhff521/kr3+7Nu2fQXYrjUL+AbntFvtKtDW26P1aslGs4nxvkN2Sozh9StH7TcCXyrS1kOw6s+L0AVvn3irP08DncklTUvpmsgUZLW43kmaF346IUsfyNeBrFdorOR0cEe8Bf12pv2ZmZtZ+nXXLkWp17UlgMzMzM2tVpzzOS9I0YHRR8u0RMb0z+lNOrfoZEQ1AQ4W2+gGPldh1dES83pb2zMzMrIa6+AKITgnmIuLiyrk63/bsZwrYhlbMaGZmZttXJy1sqJZ8vfxOxx+4mZl1d9s1umr+0per/t05YPa92z3y65SROTMzM7PuQnWeZrUuZv2/z6ucqUp9Tv4CGzZsqFl9AL1796b59HNrVt+A72eXONbyyRef/OZVAKx74D9qVmff005k3UNza1ffKScAsP6RH9Sszj4nHV+zuszMrDYczJmZmZm1xrcmMTMzM+vGpOpfFavSsZJ+LuklSVe3ku9USSFpeKU6HcyZmZmZbQeSegDTgOOAQcCZkgaVyNeb7ClYP62mXgdzZmZmZq2pq6v+1bqRwEsR8XJ6itNsSjzRCrgB+A7wTlXda8uxmJmZmVm7fRr4Ve79mpT2EUmHAn8UEVWvXtupgjlJDdXMPbexzgHpQfftLX9NFXnulfRqcTuS5khakV7Nkla0tx9mZmZWmqS2vC6QtDz3uiBfVYnqI9dOHXAbcEVb+tdlV7NK+lhEfNBZ5VMdPSLiw47UUYVrgJsq5JkBfA+YmU+MiDMK25JuBdbXunNmZmZWvYioB+rL7F4D/FHu/b7Ab3LvewODgQZliyk+CcyVdEJELC/XZsWRuTTy9KKkuyW9IGmBpJ75US5J/SU1p+2Jkh6RNE/SakmTJV0u6VlJSyXt1UpbDZJukrQIuEzS3pIekvRUeo1O+fZKbTSlOoek9CmS6iUtAGamfs5O+eYAPXNtjZfUKOkZSQ9I6pXSmyVdJ2kJcFqZfg6T9JykRuDiXHoPSTenvjZJujClj5W0WNLDklZJulNSnaSpQM80snZ/ufMSEYuBN1o5bwJOB2aVy2NmZmbtVKfqX617CjhA0kBJuwJfAj66wWhErI+I/hExICIGAEuBVgM5qH6a9QBgWkQcDKwDTqmQfzBwFtmFfjcCb0fEoUAjcHaFsn0j4siIuBW4HbgtIkakNu9Jea4Hno2IIWQjW/kRq2HAiRFxFjAptT0k9WMYZMEncC0wLiIOA5YDl+fqeCcixkTE7DJ9nA5cGhGjitLPA9an/o4Azpc0MO0bSTZsegiwH3ByRFwNbIqIoRExocJ5ac1fAK9ExC9K7cwP+dbXl/tjwczMzEpSXfWvVqQZw8nAfOBF4PsR8YKkv5d0Qnu7V+006+qIKFyP9TQwoEL+xyNiA7BB0nqg8MiB54EhFcrOyW2PAwZpy31b9kzLdceQAsqIWCipn6Q+Kc/ciNiUto8AvpvyNUlqSumHky0JfiLVvStZoFmqDy2kdvpGxKKUdB/ZEmOA8cAQSaem933IAuH3gGUR8XKqY1Y6hgcrnItqnUkro3JFQ75RyydAmJmZWfUi4kfAj4rSriuTd2w1dVYbzL2b2/6QbLryA7aM7O3WSv7Nufebq2hzY267DhiVC86Aj6YVixUuINxYJr1FFcCjEXFmFX0oVbbcA3cFXBIR81skSmNLlKnJA+8lfQw4mTTqaGZmZjW2Az8BopktAcSpreTriAVkw5EASBqaNhcDE1LaWGBtRLxZonw+32C2jAouBUZL2j/t213SgdV0KCLWAesljUlJ+enR+cAkSbukeg+UtEfaNzLNkdcBZwBLUvr7hfztNA74WUSs6UAdZmZm1k11JJi7hSxweRLoX6P+FLsUGJ4WE6wCLkrpUwrpwFTgnDLl7wB6pXxXAcsAIuI1YCIwK+1bCny2Df06F5iWFkDkRw3vAVYBzyi7jchdbBmJbEx9XQmsBh5O6fVAU2sLINK0bCNwkKQ1ks7L7f4SXvhgZma2zahOVb86Q8Vp1ohoJlvQUHh/S253/vq3a9P+GWS30ijkH5DbbrGvRFtji96vJRvFKs73BiXumBwRU4rebyILdkq1tZBskUJx+oCtc2+V52ngc7mkKSl9M9mCjBb3jkuzwm/nbyWSq+trwNcqtFduOpiImFipv2ZmZtYBO/A0q5mZmZl1sk65abCkacDoouTbI2J6Z/SnnFr1MyIagIYKbfUDHiux6+iIeL0t7ZmZmVkNVX7maqfqlGAuIi6unKvzbc9+poBtaMWMZmZmZjld9nFeZmZmZl2BuvjInCJqcrsz6z78gZuZWXe3XVckrLn4yqp/d+477Zbtvlqia4eaZmZmZtYqT7PuhN78z1LrLNpnz2OPZsOGDTWrD6B3795sfOKnNatvj9F/BrBN6tz03Mqa1dnzc4N56ydP1qy+Xn/x5wBsePTxmtXZ+5i/3GZ1mpl1Wb41iZmZmZltKx6ZMzMzM2tNF18A0bV7Z2ZmZmat8sicmZmZWSvUxa+ZczBnZmZm1pouHsztVNOskhokDa9xnQMktXtJo6Rrqshzr6RXi9uRNFTSUkkrJC2XNLK9/TAzM7PuqcsGc5I6NGrY0fKpjh4draMKFYM5YAZwbIn07wDXR8RQ4Lr03szMzGqpTtW/OqN7lTKkkacXJd0t6QVJCyT1zI9ySeovqTltT5T0iKR5klZLmizpcknPplGkvVppq0HSTZIWAZdJ2lvSQ5KeSq/RKd9eqY2mVOeQlD5FUr2kBcDM1M/ZKd8coGeurfGSGiU9I+kBSb1SerOk6yQtAU4r089hkp6T1AhcnEvvIenm1NcmSRem9LGSFkt6WNIqSXdKqpM0FeiZRtbuL3deImIx8EapXcCeabsP8JtydZiZmdmOqdqRuQOAaRFxMLAOOKVC/sHAWcBI4Ebg7Yg4FGgEzq5Qtm9EHBkRtwK3A7dFxIjU5j0pz/XAsxExhGxka2au/DDgxIg4C5iU2h6S+jEMsuATuBYYFxGHAcuBy3N1vBMRYyJidpk+TgcujYhRRennAetTf0cA50samPaNBK4ADgH2A06OiKuBTRExNCImVDgvpXwFuFnSr4BbgK+XyiTpgjQNu7y+vr4dzZiZme3EVFf9qxNUOxW5OiJWpO2ngQEV8j8eERuADZLWA/NS+vPAkApl5+S2xwGDcqtI9pTUGxhDCigjYqGkfpL6pDxzI2JT2j4C+G7K1ySpKaUfDgwCnkh170oWaJbqQwupnb4RsSgl3Qccl7bHA0MknZre9yELhN8DlkXEy6mOWekYHqxwLiqZBHw1Ih6SdDrwr2TnrIWIqAcKUVzU8gkQZmZmOzp10vRptaoN5t7NbX9INl35AVtG9nZrJf/m3PvNVbS5MbddB4zKBWcAqPQa4cJDcDeWSW9RBfBoRJxZRR9KlS33wF0Bl0TE/BaJ0tgSZWrxwPtzgMvS9gNsGbk0MzOznURHxgObSdOWwKmt5OuIBcDkwhtJQ9PmYmBCShsLrI2IN0uUz+cbzJZRwaXAaEn7p327Szqwmg5FxDpgvaQxKSk/PTofmCRpl1TvgZL2SPtGShooqQ44A1iS0t8v5G+H3wBHpu2jgF+0sx4zMzMrp66u+ldndK8DZW8hC1yeBPrXqD/FLgWGp8UEq4CLUvqUQjowlWyEqpQ7gF4p31XAMoCIeA2YCMxK+5YCn21Dv84FpqUFEPlRw3uAVcAz6TYid7FlJLIx9XUlsBp4OKXXA02tLYBI07KNwEGS1kg6L+06H7hV0nPATcAFbTgGMzMz2wFUnGaNiGayBQ2F97fkduevf7s27Z9BdiuNQv4Bue0W+0q0Nbbo/VqyUazifG8AJ5ZIn1L0fhPwpTJtLSRbpFCcPmDr3FvleRr4XC5pSkrfTLYgo8XtRtKs8NsRUepYvgZ8rUJ7JaeDI2IJW0ZHzczMbFvo4jcN9hMgzMzMzFpR+lL9rqNTgjlJ04DRRcm3R8T0zuhPObXqZ0Q0AA0V2uoHlFpmenREvN6W9szMzGzn0SnBXERcXDlX59ue/UwB29CKGc3MzGz76qSFDdXq2r0zMzMzs1Ypoha3O7NuxB+4mZl1d9v1IrbfXvutqn937vOta7f7BXZeALETev2emZUzVanf357NWw1LKmdsg15jx7D+kR/UrL4+Jx0PwK+vuLZmdX761m8BsPrUSk+nq97AB2eyYcHCmtXXe/xRAPzymJNqVud+jz4CwPq5P6pZnX1O+DzvrHyxZvUB7Db4T2tan5lZV+ZgzszMzKw1Xs1qZmZm1n3JCyDMzMzMbFvxyJyZmZlZa7r4NKtH5szMzMy2E0nHSvq5pJckXV1i/0WSnpe0QtISSYMq1elgzszMzKw1dar+1QpJPYBpwHHAIODMEsHa/4mIQyJiKPAd4B8rdq99R9U9SWqQNLzGdQ6QtLID5a+pIs+9kl4tbkfS5yQ1pgh+nqQ929sPMzMzK0Oq/tW6kcBLEfFyRLwHzAZOzGeIiDdzb/egivvDdtlgTlKHrufraPlUR4//z979h1lVnvf+f3+GQERBKGA0UZMhikkQR5QflUKVVkqTnDaeGj1GbCM5HjUUxFRTtTnWYnvpl3zVWmypOpJqtVY4arDakxPwUoGiEEXAEaH5JpGJMUYjekACKCD394/1TGbNsH/BrGFm4PO6rn1lrWfd636evfd4cedZ+1mrozlqULWYA+4DPl+ifR5wXUScAiwE/rzAcZmZmdk+knSZpFW512W5w8cCP8vtv57a2ueYLuknZDNzM6v1WbWYSzNPGyTdI+kVSYsl9c3PckkaIqk5bU+V9FiaKdooaYakqyStkbRS0qAKfS2RdLOkpcCVko6S9KikF9JrfIoblPpoSjkbUvssSY2SFgP3p3HOT3ELgL65vianWa3Vkh6W1C+1N0u6QdJy4Pwy4xwl6SVJK4DpufZekm5JY22SdHlqnyhpmaSFktZLuktSnaTZQN90XfzBcp9LRCwD3i1x6DPAsrT9JPDlcjnMzMxs/6iuruZXRDRGxOjcqzGfqkT6vWbeImJuRJwAXAtUveN9rTNzw4C5EXEysJnqRcMIYArZdOJNwPaIOA1YAVS7Zf7AiDgrIm4D5gC3R8SY1Oe8FHMjsCYiGshmtvKPNBgFnBMRU4Bpqe+GNI5RkBWfZB/OpIg4HVgFXJXL8X5ETIiI+WXGeC8wMyLGtWu/BNiSxjsGuFTS0HRsLHA1cApwAnBuRFwH7IiIkRFxUZXPpZR1wJfS9vnA8aWC8v8vobGxsVSImZmZdb7Xaftv9XHAGxXi5wNVH+NT66XIjRGxNm2/CNRXiX8mIrYCWyVtAZ5I7S8DDVXOXZDbngQMV+s16CMl9QcmkArKiHha0mBJA1LM4xGxI22fCdyR4pokNaX2M8h+ePhsyt2HrNAsNYY2Uj8DI2JpanqA7IeMAJOBBknnpf0BZIXwTuD5iHg15XgovYdHqnwW1fx34A5JNwCPp372kv5fQUsVF0U+zsvMzOygp8J+lfYCMCxN9Ii0WsEAACAASURBVPwc+ArZ5FdrV9KwiPhR2v0vwI+ootZi7oPc9odklyt30zqzd1iF+D25/T019Lktt10HjMsVZwBIJX9h2DJNua1Me5sUwJMRcWENYyh1brkfIwq4IiIWtWmUJpY4p8MPvI+I/yQrIJF0EtmXbmZmZkWqskq1VhGxW9IMYBHQC/iniHhF0l8DqyLicWCGpEnALuD/AhdXHV4HxtRMumwJnFchriMWAzNadiSNTJvLgItS20RgU7vVH5SIG0HrrOBKYLykE9Oxw1MxVFVEbAa2SJqQmvKXRxcB0yT1TnlPknREOjZW0lBJdcAFQMvT6Xe1xO8rSR9L/1tHdtn4rv3JY2ZmZgdGRHwvIk6KiBMi4qbUdkMq5IiIKyPi5PQTrN+JiFeq5exIMXcrWeHyHDCkA3kqmQmMTosJ1gNfT+2zWtqB2ZSvWu8E+qW4a4DnASLibWAq8FA6thL47D6M62vA3LQAIj9rOA9YD6xOtxG5m9aZyBVprOuAjWSrTyG7/NlUaQFEuiy7AviMpNclXZIOXSjp/wP+k+ya+7378B7MzMysBpJqfnWFqpdZI6KZbEFDy/6tucP5379dn47fR3YrjZb4+tx2m2Ml+prYbn8T2SxW+7h3aXdfltQ+q93+DrLr0aX6eppskUL79vq9o/eKeRE4Ndc0K7XvIVuQ0eZ2I+nL3R4Rpd7LtWSrVSr1V/JycETMIVskYmZmZocoP5vVzMzMrJLiFkB0ii4p5iTNBca3a54TEd3qMmFR44yIJcCSKn0NBp4qcejsiHhnX/ozMzOzQ0eXFHMRMb16VNc7kONMBdvIqoFmZmZ2YBW0mrWz+DKrmZmZWSVdtLChVoro8O3OrGfxF25mZj3dAa2ufnnbP9T8b+fHrp5xwCs/z8wdgj740U8Ky/XRYSew6823CssH0PuYo9nx0rrC8vU9NVuMvX3VmsJyHj76NAA++OGPC8v50c+cyM7m1wrL16f+kwDsWPtyYTn7jjylU3LueuPNwvIB9P7EMZ3yN2RmhyZ188us3Xt5hpmZmZlV5Jk5MzMzs0p8axIzMzOzHqybL4BwMWdmZmZWiX8zZ2ZmZmadxTNzZmZmZhWornvPfXXv0R0gkpZIGl1wznpJ+31vBEnfqnL8eEnPSNog6RVJV+5vX2ZmZtZz9bhiTlKHZhM7en7K0aujOWpQsZgDdgNXR8TngDOA6ZKGd/6wzMzMDjGqq/3VBfa71zTztEHSPWlmaLGkvvlZLklDJDWn7amSHpP0hKSNkmZIukrSGkkrJQ2q0NcSSTdLWgpcKekoSY9KeiG9xqe4QamPppSzIbXPktQoaTFwfxrn/BS3AOib62uypBWSVkt6WFK/1N4s6QZJy4Hzy4xzlKSXJK0Apufae0m6JY21SdLlqX2ipGWSFkpaL+kuSXWSZgN9Ja2V9GCpviLiFxGxOm1vBTYAx9b05ZmZmVnt6lT7qyuG18HzhwFzI+JkYDPw5SrxI4ApwFjgJmB7RJwGrAC+WuXcgRFxVkTcBswBbo+IManPeSnmRmBNRDSQzWzdnzt/FHBOREwBpqW+G9I4RkFWfALXA5Mi4nRgFXBVLsf7ETEhIuaXGeO9wMyIGNeu/RJgSxrvGOBSSUPTsbHA1cApwAnAuRFxHbAjIkZGxEVVPhck1QOnAT8oc/wySaskrWpsbKyWzszMzHqQjl5y3BgRa9P2i0B9lfhn0izSVklbgCdS+8tAQ5VzF+S2JwHD1XrflyMl9QcmkArKiHha0mBJA1LM4xGxI22fCdyR4pokNaX2M4DhwLMpdx+yQrPUGNpI/QyMiKWp6QHgC2l7MtAg6by0P4CsEN4JPB8Rr6YcD6X38EiVzyLfbz/gUeAbEfFeqZiIaARaqrgo8nFeZmZmBzsd5PeZ+yC3/SHZ5crdtM74HVYhfk9uf08NY9mW264DxuWKMwBU+tNueTjutjLtbVIAT0bEhTWModS55R7EK+CKiFjUplGaWOKcmh/mK6k3WSH3YER8t9bzzMzM7ODRGb/UayZdtgTOqxDXEYuBGS07kkamzWXARaltIrCpzGxVPm4ErbOCK4Hxkk5Mxw6XdFItA4qIzcAWSRNSU/7y6CJgWiq+kHSSpCPSsbGShkqqAy4Alqf2XS3xpaTC9TvAhoj421rGaGZmZvtBqv3VBTqjmLuVrHB5DhjSCfkBZgKj02KC9cDXU/uslnZgNnBxmfPvBPqluGuA5wEi4m1gKvBQOrYS+Ow+jOtrwNy0ACI/azgPWA+sTrcruZvWmcgVaazrgI3AwtTeCDSVWwABjAf+BPjdtFBiraQv7sNYzczMrBZ1dbW/usB+X2aNiGayBQ0t+7fmDud//3Z9On4fcF8uvj633eZYib4mttvfRDaL1T7uXeCcEu2z2u3vAL5Spq+nyRYptG+v3zt6r5gXgVNzTbNS+x6yBRltbjeSrgpvj4hS7+Va4NoKfS0nu3xrZmZmhzA/AcLMzMyskoN8AUShJM0lu3yYNyci7u2K8ZRT1DgjYgmwpEpfg4GnShw6OyLe2Zf+zMzM7ODTrYq5iJheParrHchxpoJtZNVAMzMz6xTd/dYkiqj5Thh2cPAXbmZmPd0Bra7eve9fa/63c9DUKQe88utxz2Y1MzMzs1bd6jKrHRhv3XRr9aAaHf0/v8nWJ58pLB9A/9/7HX619NnC8vU7K/t54+t/enVhOY/7x9sA2PSP3yks55A/vYQ3/+b/LSzfMX95DQA//erXq0TW7lP33wXA9lVrCst5+OjT2PHSusLyAfQ9dQSvz/jzwvId9w+3AFDk01M+OuyEwnKZWSfr5pdZPTNnZmZm1oN5Zs7MzMyski66GXCtuvfozMzMzKwiz8yZmZmZVaC67v2bORdzZmZmZpV4AUT3IWmJpNEF56yXtN9L8SR9q8rx4yU9I2mDpFckXZk7NkjSk5J+lP73N/Z3HGZmZtb5JH1e0g8l/VjSdSWOXyVpvaQmSU9J+lS1nN22mJPUoVnDjp6fcvTqaI4aVCzmgN3A1RHxOeAMYLqk4enYdcBTETGM7JFfe/1RmJmZWQeprvZXpTRZXTEX+AIwHLgw9296izXA6IhoAB4Bqt6zqmoxl2aeNki6J80MLZbUNz/LJWmIpOa0PVXSY5KekLRR0oxUZa6RtFLSoAp9LZF0s6SlwJWSjpL0qKQX0mt8ihuU+mhKORtS+yxJjZIWA/encc5PcQuAvrm+JktaIWm1pIcl9UvtzZJukLQcOL/MOEdJeknSCmB6rr2XpFvSWJskXZ7aJ0paJmlhqrbvklQnaTbQV9JaSQ+W6isifhERq9P2VmADcGw6fA7wz2n7n4H/WvaLNDMzs642FvhxRLwaETuB+WT/lv9aRDwTEdvT7krguGpJa52ZGwbMjYiTgc3Al6vEjwCmpEHfBGyPiNOAFcBXq5w7MCLOiojbgDnA7RExJvU5L8XcCKxJVeu3gPtz548CzomIKcC01HdDGscoyIpP4HpgUkScDqwCrsrleD8iJkTE/DJjvBeYGRHj2rVfAmxJ4x0DXCppaDo2FrgaOAU4ATg3Iq4DdkTEyIi4qMrngqR64DTgB6np6Ij4BWRFH/CxMuddJmmVpFWNjY3VujEzM7Mc1anmVxXHAj/L7b9O6wRNKZcA/6da0lovRW6MiLVp+0Wgvkr8M2kWaaukLcATqf1loKHKuQty25OA4bkH3B4pqT8wgVRQRsTTkgZLGpBiHo+IHWn7TOCOFNckqSm1n0E2vflsyt2HrNAsNYY2Uj8DI2JpanqAbLoUYDLQIOm8tD+ArBDeCTwfEa+mHA+l9/BIlc8i328/4FHgGxHxXq3nAUREI9BSxUWRT4AwMzM76O3DAghJlwGX5Zoa07/DUPqZsiWf+yrpj4HRwFnV+qy1mPsgt/0h2eXK3bTO7B1WIX5Pbn9PDX1uy23XAeNyxRkAUslPteXD2FamvU0K4MmIuLCGMZQ6t9wDdwVcERGL2jRKE0ucU/NDeyX1JivkHoyI7+YOvSXp4xHxC0kfB35Za04zMzMrXrsJlPZeB47P7R8HvNE+SNIk4H8CZ0XEB+2Pt9eRBRDNpMuWwHkV4jpiMTCjZUfSyLS5DLgotU0ENpWZrcrHjaB1VnAlMF7SienY4ZJOqmVAEbEZ2CJpQmrKXx5dBExLxReSTpJ0RDo2VtJQSXXABcDy1L6rJb6UVLh+B9gQEX/b7vDjwMVp+2Lg32p5D2ZmZrYPCloAAbwADEv1QB/gK2T/lrd2JZ0G3A18KSJqmqTpSDF3K1nh8hwwpAN5KpkJjE6LCdYDLU8Mn9XSDsymtaBp706gX4q7BngeICLeBqYCD6VjK4HP7sO4vgbMTQsg8rOG84D1wGpltyu5m9aZyBVprOuAjcDC1N4INJVbAAGMB/4E+N20UGKtpC+mY7OB35P0I+D30r6ZmZl1QxGxm2ySahHZgsb/FRGvSPprSV9KYbcA/YCH07/5j5dJ92tVL7NGRDPZgoaW/fwPrvK/f7s+Hb8PuC8XX5/bbnOsRF8T2+1vIpvFah/3Lu1Wf6T2We32d5BVvaX6eppskUL79vq9o/eKeRE4Ndc0K7XvIVuQ0eZ2I+mq8PaIKPVergWurdDXckpfYyci3gHOrjZeMzMz64ACnwAREd8Dvteu7Ybc9qR9zeknQJiZmZlVUPqn+t1HlxRzkuaSXT7MmxMR93bFeMopapwRsQRYUqWvwWQ3/m3v7DQDZ2ZmZraXLinmImJ69aiudyDHmQq2kVUDzczM7MAq8DJrZ+i2j/MyMzMzs+oUUfPtzuzg4C/czMx6ugM6Vbbl8e/V/G/ngC998YBP43kBxCFo28pVheU64ozR7HrzrcLyAfQ+5mg++NFPCsv30WEnALBj9UuF5ex7eraYecfal4vLOfIUPvjJxsLyffSE7Ely732/1E8x98+Rn88WT+/86c+qRNauz6eOL/R9Q/bef/UfzxWWr99v/xYAu954s7CcvT9xDDteWldYPoC+p46oHmRmBx0Xc2ZmZmaVVL8ZcJdyMWdmZmZWQXe/NUn3LjXNzMzMrCLPzJmZmZlV4luTmJmZmVln8cycmZmZWSX+zVz3IWmJpNEF56yXtN/3F5D0rSrHj5f0jKQNkl6RdGXu2PmpbU/R78vMzMwS1dX+6gLdtpiT1KFZw46en3L06miOGlQs5oDdwNUR8TngDGC6pOHp2DrgXGBZJ47PzMzMurGqxVyaedog6Z40C7RYUt/8LJekIZKa0/ZUSY9JekLSRkkzJF0laY2klZIGVehriaSbJS0FrpR0lKRHJb2QXuNT3KDUR1PK2ZDaZ0lqlLQYuD+Nc36KWwD0zfU1WdIKSaslPSypX2pvlnSDpOXA+WXGOUrSS5JWANNz7b0k3ZLG2iTp8tQ+UdIySQslrZd0l6Q6SbOBvpLWSnqwVF8R8YuIWJ22twIbgGPT/oaI+GG179DMzMz2n+pU86sr1DozNwyYGxEnA5uBL1eJHwFMAcYCNwHbI+I0YAXw1SrnDoyIsyLiNmAOcHtEjEl9zksxNwJrIqKBbGbr/tz5o4BzImIKMC313ZDGMQqy4hO4HpgUEacDq4Crcjnej4gJETG/zBjvBWZGxLh27ZcAW9J4xwCXShqajo0FrgZOAU4Azo2I64AdETEyIi6q8rkgqR44DfhBtdh2510maZWkVY2NjftyqpmZmXVztV6K3BgRa9P2i0B9lfhn0izSVklbgCdS+8tAQ5VzF+S2JwHDczfrO1JSf2ACqaCMiKclDZY0IMU8HhE70vaZwB0prklSU2o/AxgOPJty9yErNEuNoY3Uz8CIWJqaHgC+kLYnAw2Szkv7A8gK4Z3A8xHxasrxUHoPj1T5LPL99gMeBb4REe/Veh5ARDQCLVVcFPk4LzMzs4NeN18AUWsx90Fu+0Oyy5W7aZ3ZO6xC/J7c/p4a+tyW264DxuWKMwBU+lbMLQ/B3VamvU0K4MmIuLCGMZQ6t9wDdwVcERGL2jRKE0ucU/NDeyX1JivkHoyI79Z6npmZmRWgrtsuMQA6tgCimXTZEjivQlxHLAZmtOxIGpk2lwEXpbaJwKYys1X5uBG0zgquBMZLOjEdO1zSSbUMKCI2A1skTUhN+cuji4BpqfhC0kmSjkjHxkoaKqkOuABYntp3tcSXkgrX7wAbIuJvaxmjmZmZHTo6UszdSla4PAcMKWg87c0ERqfFBOuBr6f2WS3twGzg4jLn3wn0S3HXAM8DRMTbwFTgoXRsJfDZfRjX14C5aQFEftZwHrAeWJ1uV3I3rTORK9JY1wEbgYWpvRFoKrcAAhgP/Anwu2mhxFpJXwSQ9EeSXgfGAf9b0qIyOczMzGw/Sar51RWqXmaNiGayBQ0t+7fmDud//3Z9On4fcF8uvj633eZYib4mttvfRDaL1T7uXeCcEu2z2u3vAL5Spq+nyRYptG+v3zt6r5gXgVNzTbNS+x6yBRltbjeSvtztEVHqvVwLXFuhr+Vkl29LHVtIa1FoZmZmhyA/AcLMzMyskm7+m7kuKeYkzSW7fJg3JyLu7YrxlFPUOCNiCbCkSl+DgadKHDo7It7Zl/7MzMzs0NElxVxETK8e1fUO5DhTwTayaqCZmZkdWAfJrUnMzMzMDk1d9GSHWimi5tud2cHBX7iZmfV0B7S6+tV/PFfzv539fvu3Dnjl55m5Q9Bbs28vLNfR1/0ZO15aV1g+gL6njuC9fy/uLitH/sHvA/DaxdMKy/nJf74TgDeu/avCcn7i2zfyTuN9heUbfNlUAH7y+WpP36vdCd9/FKDw72fbs/v0hLqqjhj/m7w5a3Zh+Y6ZdR0A728o7lHIh33uM/z8yusKywdw7JzZhY/RzCC7RWz31b1HZ2ZmZmYVeWbOzMzMrBIvgDAzMzPrwbr5AghfZjUzMzPrwTwzZ2ZmZlaJF0CYmZmZWWdxMZdIWiJpdME56yXt9307JH2ryvHDJD0v6SVJr0i6cX/7MjMzs9JUp5pfXaFHFnOSOnR5uKPnpxy9OpqjBhWLOeAD4Hcj4lSyR4F9XtIZnT8sMzOzQ4hU+6tqKn1e0g8l/VjSXjeblHSmpNWSdks6r5bhdaiYSzNPGyTdk2aGFkvqm5/lkjREUnPanirpMUlPSNooaYakqyStkbRS0qAKfS2RdLOkpcCVko6S9KikF9JrfIoblPpoSjkbUvssSY2SFgP3p3HOT3ELgL65viZLWpE+zIcl9UvtzZJukLQcOL/MOEelmbIVwPRcey9Jt6SxNkm6PLVPlLRM0kJJ6yXdJalO0mygr6S1kh4s1VdkfpV2e6eXn/BgZmbWDaWJoLnAF4DhwIWShrcLew2YCvxrrXmLmJkbBsyNiJOBzUC1282PAKYAY4GbgO0RcRqwAvhqlXMHRsRZEXEbMAe4PSLGpD7npZgbgTUR0UA2s3V/7vxRwDkRMQWYlvpuSOMYBVnxCVwPTIqI04FVwFW5HO9HxISImF9mjPcCMyNiXLv2S4AtabxjgEslDU3HxgJXA6cAJwDnRsR1wI6IGBkRF5X7QFKRuBb4JfBkROx1K31Jl0laJWlVY2NjuVRmZmZWSnEzc2OBH0fEqxGxE5gPnJMPiIjmiGgC9tQ6vCJWs26MiLVp+0Wgvkr8MxGxFdgqaQvwRGp/GWiocu6C3PYkYLhaP7gjJfUHJpAKyoh4WtJgSQNSzOMRsSNtnwnckeKaJDWl9jPIquVnU+4+ZIVmqTG0kfoZGBFLU9MDZNU3wGSgITdlOoCsEN4JPB8Rr6YcD6X38EiVz4I09g+BkZIGAgsljYiIde1iGoGWKi6KfJyXmZmZ1exY4Ge5/deB3+xo0iKKuQ9y2x+SXa7cTeus32EV4vfk9vfUMJ5tue06YFyuOANAKlkWt1x63FamvU0KshmuC2sYQ6lzy13mFHBFRLR5qKWkiSXO2edLpRGxWdIS4PNAsQ9LNTMzO4SprvYLmZIuAy7LNTWmSRXIaoH2OvzzqM5aANFMumwJ1PTjvf2wGJjRsiNpZNpcBlyU2iYCmyLivRLn5+NG0DoruBIYL+nEdOxwSSfVMqCI2AxskTQhNeUvjy4CpknqnfKeJOmIdGyspKHKnuR7AbA8te9qiS8l/W5wYNruSzZb+Z+1jNXMzMyKFxGNETE698r/vul14Pjc/nHAGx3ts7OKuVvJCpfngCGd1MdMYHRaTLAe+Hpqn9XSDswGLi5z/p1AvxR3DfA8QES8TfbDw4fSsZXAZ/dhXF8D5qYFEPlZw3nAemC1stuV3E3rTOSKNNZ1wEZgYWpvBJrKLYAAPg48k8b5AtmM4r/vw1jNzMysmrq62l+VvQAMSxM4fYCvAI93dHgduswaEc1kCxpa9m/NHc7//u36dPw+4L5cfH1uu82xEn1NbLe/iWwWq33cu7T7MWFqn9VufwfZh1iqr6fJFim0b6/fO3qvmBeBU3NNs1L7HrIFGW1uN5KuCm+PiFLv5Vrg2gp9NQGnVRuTmZmZdUANtxypRUTsljSD7GpdL+CfIuIVSX8NrIqIxyWNIZvU+Q3gDyXdmBaZluXHeZmZmZkdIBHxPeB77dpuyG2/QHb5tWbdrpiTNBcY3655TkTc2xXjKaeocUbEEmBJlb4GA0+VOHR2RLyzL/2ZmZnZPuqiJzvUqtsVcxExvXpU1zuQ40wF28iqgWZmZnbIUYQfGHCI8RduZmY93QGdKnt/3Yaa/+08bMTnDvg0XrebmTMzMzPrVgpaANFZXMwdgt74878sLNcnbvkbNv+vhdUD98HA//ZHbF38dGH5+k/+XQB+9NtfqBJZu2H/8X8A+OWtf19Yzo998wo2nlftiXa1G/pI9iS7H034/cJyDlue3fO66O+nyHwtOd+49q8Ky/eJb98IwI6Xirsfd99TR/DTKf+jsHwAn/rXeWx/YXVh+Q4fczoAr//p1YXlPO4fbyssl5llXMyZmZmZVdLNF0B01k2DzczMzOwA8MycmZmZWSX+zZyZmZlZz5U9Or376t6jMzMzM7OKXMwlkpZIGl1wznpJ+738TdK3qkeBpF6S1kj69/3ty8zMzMqoU+2vrhhel/TaQZI6dHm4o+enHL06mqMGNRVzwJXAhs4ciJmZmXVPHSrm0szTBkn3SHpF0mJJffOzXJKGSGpO21MlPSbpCUkbJc2QdFWaVVopaVCFvpZIulnSUuBKSUdJelTSC+k1PsUNSn00pZwNqX2WpEZJi4H70zjnp7gFQN9cX5MlrZC0WtLDkvql9mZJN0haDpxfZpyjJL0kaQUwPdfeS9ItaaxNki5P7RMlLZO0UNJ6SXdJqpM0G+graa2kByt8LscB/wWYV8NXZmZmZvuqrq72V1cMr4Acw4C5EXEysBn4cpX4EcAUYCxwE7A9Ik4DVgDV7pg6MCLOiojbgDnA7RExJvXZUszcCKyJiAayma37c+ePAs6JiCnAtNR3QxrHKMiKT+B6YFJEnA6sAq7K5Xg/IiZExPwyY7wXmBkR49q1XwJsSeMdA1wqaWg6Nha4GjgFOAE4NyKuA3ZExMiIuKjCZ/J3wDXAnnIBki6TtErSqsbGxgqpzMzMrD1JNb+6QhGrWTdGxNq0/SJQXyX+mYjYCmyVtAV4IrW/DDRUOXdBbnsSMDz3wR0pqT8wgVRQRsTTkgZLGpBiHo+IHWn7TOCOFNckqSm1nwEMB55NufuQFZqlxtBG6mdgRCxNTQ8ALY8dmAw0SDov7Q8gK4R3As9HxKspx0PpPTxS5bNA0h8Av4yIFyVNLBcXEY1ASxUXRT4BwszMzLpWEcXcB7ntD8kuV+6mddbvsArxe3L7e2oYz7bcdh0wLlecAaDSZXHLA3K3lWlvkwJ4MiIurGEMpc4t9zBeAVdExKI2jVkR1v6cWh/oOx74kqQvkn3OR0r6l4j44xrPNzMzs2q66PJprTprdM2ky5bAeRXiOmIxMKNlR9LItLkMuCi1TQQ2RcR7Jc7Px42gdVZwJTBe0onp2OGSTqplQBGxGdgiaUJqyl8eXQRMk9Q75T1J0hHp2FhJQ5XdyOYCYHlq39USX6a/v4iI4yKiHvgK8LQLOTMzs0NLZxVzt5IVLs8BQzqpj5nA6LSYYD3w9dQ+q6UdmA1cXOb8O4F+Ke4a4HmAiHgbmAo8lI6tBD67D+P6GjA3LYDIzxrOA9YDq9PtSu6mdSZyRRrrOmAj0PLk+kagqdICCDMzM+tkUu2vLtChy6wR0Uy2oKFl/9bc4fzv365Px+8D7svF1+e22xwr0dfEdvubyGax2se9C5xTon1Wu/0dZLNZpfp6mmyRQvv2+r2j94p5ETg11zQrte8hW5DR5nYj6arw9ogo9V6uBa6t1meKXQIsqSXWzMzMDh5+nJeZmZlZJX42676RNJfsh/15cyLi3q4YTzlFjbOWGTVJg4GnShw6OyLe2Zf+zMzMbN+oi57sUKtuV8xFxPTqUV3vQI4zFWwjqwaamZnZIafbFXNmZmZm3Yq6961JFFHrLc3sIOEv3MzMeroDet1z189/UfO/nb2P/fgBvybrmTkzMzOzSrwAwrqbrVu3Fparf//+heZrybnztdcLy9fnk8cBsOuNNwvL2fsTxwCw+623C8v5kaOPKvy7Adj15luF5ex9zNFZztd/XlzO447tlL+hzvi+d/70Z4Xl7POp49n99qbC8gF85KghnfI31Bn/PXbGOM06TTdfANG9LwKbmZmZWUWemTMzMzOrQN18AYSLOTMzM7NKfJnVzMzMzDqLZ+bMzMzMKthx2Edrju2K5TiemQMkLZE0uuCc9ZLWdeD8b9UQ0yzpZUlrJa3a377MzMys5+pxxZykDs0mdvT8lKNXR3PUoGoxl/xORIyMiEKLUTMzM+sZ9ruYSzNPGyTdI+kVSYsl9c3PckkaIqk5bU+V9JikJyRtlDRD0lWS1khaKWlQhb6WSLpZ0lLgSklHSXpU0gvpNT7FPzr1hAAAIABJREFUDUp9NKWcDal9lqRGSYuB+9M456e4BUDfXF+TJa2QtFrSw5L6pfZmSTdIWg6cX2acoyS9JGkFMD3X3kvSLWmsTZIuT+0TJS2TtFDSekl3SaqTNBvom2bcHtzf78jMzMwOfh2dmRsGzI2Ik4HNwJerxI8ApgBjgZuA7RFxGrAC+GqVcwdGxFkRcRswB7g9IsakPuelmBuBNRHRQDazdX/u/FHAORExBZiW+m5I4xgFWfEJXA9MiojTgVXAVbkc70fEhIiYX2aM9wIzI2Jcu/ZLgC1pvGOASyUNTcfGAlcDpwAnAOdGxHXAjjTjdlGFzySAxZJelHRZuSBJl0laJWlVY2NjhXRmZmbWmSR9XtIPJf1Y0nUljn9U0oJ0/AeS6qvl7Oglx40RsTZtvwhU6/CZiNgKbJW0BXgitb8MNFQ5d0FuexIwXK2P1zhSUn9gAqmgjIinJQ2WNCDFPB4RO9L2mcAdKa5JUlNqPwMYDjybcvchKzRLjaGN1M/AiFiamh4AvpC2JwMNks5L+wPICuGdwPMR8WrK8VB6D49U+SxajI+INyR9DHhS0n9GxLL2QRHRCLRUcVH03fbNzMysuvQzrbnA7wGvAy9Iejwi1ufCLgH+b0ScKOkrwLeBCyrl7Wgx90Fu+0Oyy5W7aZ3xO6xC/J7c/p4axrItt10HjMsVZwBIJR+e1vJw3G1l2tukAJ6MiAtrGEOpc8s9iFfAFRGxqE2jNLHEOTU/zDci3kj/+0tJC8lm+fYq5szMzKxbGAv8ODeJMx84B8gXc+cAs9L2I8A/SFJElK0POmMBRDPpsiVwXoW4jlgMzGjZkTQybS4DLkptE4FNEfFeifPzcSNonRVcCYyXdGI6drikk2oZUERsBrZImpCa8pdHFwHTJPVOeU+SdEQ6NlbSUGW3l74AWJ7ad7XElyLpiDQbSco1Gdjv1bNmZmbW6Y4F8g95fj21lYyJiN3AFmBwpaSdUczdSla4PAcM6YT8ADOB0WkxwXrg66l9Vks7MBu4uMz5dwL9Utw1wPMAEfE2MBV4KB1bCXx2H8b1NWBuWgCRnzWcR1Z1r1Z2u5K7aZ2JXJHGug7YCCxM7Y1AU4UFEEcDyyW9lMb/vyPi+/swVjMzMytY/nfq6ZX/TXulK4j7EtP2hAqzdtbJ0uzhNyPiDw5gt4X+Zq5///4U/Ru8/v37s/O11wvL1+eTxwGw6403C8vZ+xPHALD7rbcLy/mRo48q9LPs3z+7deWuN98qLGfvY47Ocr7+8+JyHndsp/wNdcb3vfOnP6sSWbs+nzqe3W9vKiwfwEeOGtIpf0Od8d9jZ4zTDind+/laZUgaB8yKiN9P+38BEBH/Ty5mUYpZoex2am8CRx3oy6xmZmZmtrcXgGHp51V9gK8Aj7eLeZzWK4vnAU9XKuSgmz3OS9JcYHy75jkRcW9XjKecosYZEUuAJVX6Ggw8VeLQ2RHxzr70Z2ZmZl0nInZLmkH2W/pewD9FxCuS/hpYFRGPA98BHpD0Y+BdsoKvom5VzEXE9OpRXe9AjjMVbCOrBpqZmVm3FxHfA77Xru2G3Pb7lHk4QTm+zGpmZmbWg3kBxKHHX7iZmfV0PXIBRGfpVpdZ7cDYvOC7heUaeMG5vPf9Uj/p239Hfv5sti1fWVi+IyacAcDPvv5nheU8/q7bAQof58+v+lZh+Y7925sB2PLYvxeWc8B/zRZeb1u5qrCcR5wxmg9+srGwfAAfPWEoW54o7k49A/7w8wDsfLW5sJx9Pl3PL7/9d4XlA/jYtd9gZ/NrheXrU/9JALZ894kqkbUbcO4fAvDmrNmF5Txm1nWdsiLarKfwZVYzMzOzHszFnJmZmVkP5mLOzMzMrAdzMWdmZmbWg7mYMzMzM+vBXMyZmZmZ9WAu5gBJSySNLjhnvaR1HTi/6j0qJA2U9Iik/5S0IT3A18zMzA4hPa6Yk9She+N19PyUo1dHc9SglhuOzQG+HxGfBU4FNnTukMzMzKy72e9iLs08bZB0j6RXJC2W1Dc/yyVpiKTmtD1V0mOSnpC0UdIMSVdJWiNppaRBFfpaIulmSUuBKyUdJelRSS+k1/gUNyj10ZRyNqT2WZIaJS0G7k/jnJ/iFgB9c31NlrRC0mpJD0vql9qbJd0gaTllnpkmaZSklyStAKbn2ntJuiWNtUnS5al9oqRlkhZKWi/pLkl1kmYDfSWtlfRgmb6OBM4keyAvEbEzIjbX9OWZmZnZQaOjM3PDgLkRcTKwGfhylfgRwBRgLHATsD0iTgNWAF+tcu7AiDgrIm4jm5G6PSLGpD7npZgbgTUR0UA2s3V/7vxRwDkRMQWYlvpuSOMYBVnxCVwPTIqI04FVwFW5HO9HxISImF9mjPcCMyOi/eXOS4AtabxjgEslDU3HxgJXA6cAJwDnRsR1wI6IGBkRF5Xp69PA28C9qSCeJ+mIUoGSLpO0StKqxsbGMunMzMysJ+roJceNEbE2bb8I1FeJfyYitgJbJW0BWp4R8zLQUOXcBbntScBw6dePZjtSUn9gAqmgjIinJQ2WNCDFPB4RO9L2mcAdKa5JUlNqPwMYDjybcvchKzRLjaGN1M/AiFiamh4AvpC2JwMNks5L+wPICuGdwPMR8WrK8VB6D49U+Swg++5OB66IiB9ImgNcB/xl+8CIaARaqrgo8nFeZmZm1rU6Wsx9kNv+kOxy5W5aZ/wOqxC/J7e/p4axbMtt1wHjcsUZAMpVdzktD5bfVqa9TQrgyYi4sIYxlDq33EPsRVZ0LWrTKE0scU65HO29DrweET9I+4+QFXNmZmZ2COmMBRDNpMuWwHkV4jpiMTCjZUfSyLS5DLgotU0ENkXEeyXOz8eNoHVWcCUwXtKJ6djhkk6qZUDp92pbJE1ITfnLo4uAaZJ6p7wn5S6JjpU0VFIdcAGwPLXvaokv09+bwM8kfSY1nQ2sr2WsZmZmdvDojGLuVrLC5TlgSCfkB5gJjE6LCdYDX0/ts1ragdnAxWXOvxPol+KuAZ4HiIi3ganAQ+nYSuCz+zCurwFz0wKI/KzhPLJCa3W6XcndtM5ErkhjXQdsBBam9kagqdwCiOQK4ME01pHAzfswVjMzMzsI7Pdl1ohoJlvQ0LJ/a+5w/vdv16fj9wH35eLrc9ttjpXoa2K7/U1ks1jt494FzinRPqvd/g7gK2X6eppskUL79vq9o/eKeZHsFiEtZqX2PWQLMtrcbiRdFd4eEaXey7XAtVX6WwsUen88MzMz61l63H3mzMzMzKxVh2+gWyRJc4Hx7ZrnRMS9XTGecooaZ0QsAZZU6Wsw8FSJQ2dHxDv70p+ZmZkdfLpVMRcR06tHdb0DOc5UsI2sGmhmZmaHJEXUeicMO0j4Czczs56u1K3IDln+zZyZmZlZD9atLrPagbH54X8rLNfA889hx0vrCssH0PfUEbz7T/9SWL5B//2PAXhr9u2F5Tz6uj8D4I1r/6qwnJ/49o1se/YH1QNrdMT43wTg1T8suXB7v3z6iexJdu803ldYzsGXTeWDn2wsLB/AR08Yyo8m/H5h+YYtz+73/f6GHxaW87DPfYZf3vr3heUD+Ng3r+iUv6Eix/mxb17RKTl3vtpcWD6APp+u51dLllcPrFG/iROqB5ntJ8/MmZmZmfVgLubMzMzMejAXc2ZmZmY9mIs5MzMzsx7MxZyZmZlZD+ZizszMzKwHczEHSFoiqdAH1kuql7Tf9+yQ9K0qxz8jaW3u9Z6kb+xvf2ZmZtYz9bhiTlKH7o3X0fNTjl4dzVGDisVcRPwwIkZGxEhgFLAdWHgAxmVmZmbdyH4Xc2nmaYOkeyS9ImmxpL75WS5JQyQ1p+2pkh6T9ISkjZJmSLpK0hpJKyUNqtDXEkk3S1oKXCnpKEmPSnohvcanuEGpj6aUsyG1z5LUKGkxcH8a5/wUtwDom+trsqQVklZLelhSv9TeLOkGScuB88uMc5SklyStAKbn2ntJuiWNtUnS5al9oqRlkhZKWi/pLkl1kmYDfdOM24M1fB1nAz+JiJ/WEGtmZmYHkY7OzA0D5kbEycBm4MtV4kcAU4CxwE3A9og4DVgBfLXKuQMj4qyIuA2YA9weEWNSn/NSzI3AmohoIJvZuj93/ijgnIiYAkxLfTekcYyCrPgErgcmRcTpwCrgqlyO9yNiQkTMLzPGe4GZETGuXfslwJY03jHApZKGpmNjgauBU4ATgHMj4jpgR5p5u6jK5wLwFeChcgclXSZplaRVjY2NNaQzMzOznqKjlxw3RsTatP0iUF8l/pmI2ApslbQFeCK1vww0VDl3QW57EjBc+vVzdo+U1B+YQCooI+JpSYMlDUgxj0fEjrR9JnBHimuS1JTazwCGA8+m3H3ICs1SY2gj9TMwIpampgeAL6TtyUCDpPPS/gCyQngn8HxEvJpyPJTewyNVPot8v32ALwF/US4mIhqBliouinycl5mZmXWtjhZzH+S2PyS7XLmb1hm/wyrE78nt76lhLNty23XAuFxxBoBy1V1OlDg/394mBfBkRFxYwxhKnVsqZ8uxKyJiUZtGaWKJc8rlKOcLwOqIeGsfzzMzM7ODQGcsgGgmXbYEzqsQ1xGLgRktO5JGps1lwEWpbSKwKSLeK3F+Pm4ErbOCK4Hxkk5Mxw6XdFItA4qIzcAWSS1PU85fHl0ETJPUO+U9SdIR6dhYSUMl1QEXAC1Pdt7VEl/FhVS4xGpmZmYHt84o5m4lK1yeA4Z0Qn6AmcDotJhgPfD11D6rpR2YDVxc5vw7gX4p7hrgeYCIeBuYCjyUjq0EPrsP4/oaMDctgMjPGs4D1gOr0+1K7qZ1JnJFGus6YCOtK1IbgaZKCyAkHQ78HvDdfRijmZmZHUT2+zJrRDSTLWho2b81dzj/+7fr0/H7gPty8fW57TbHSvQ1sd3+JrJZrPZx7wLnlGif1W5/B9migVJ9PU22SKF9e/3e0XvFvAicmmualdr3kC3IaHO7kXRVeHtElHov1wLXVulvOzC42rjMzMzs4NXj7jNnZmZmZq06fAPdIkmaC4xv1zwnIu7tivGUU9Q4I2IJsKRKX4OBp0ocOjsi3tmX/szMzOzg062KuYiYXj2q6x3IcaaCbWTVQDMzMzskKWJf74RhPZy/cDMz6+lK3YrskOXfzJmZmZn1YN3qMqsdGDteWldYrr6njmDr1q2F5QPo378/O1a/VFi+vqdnC4x3vtpcWM4+n64HYPfbmwrL+ZGjhrCz+bXC8vWp/yQAu37+i8Jy9j724wBsW76ysJxHTDijU/6Gdr72emH5+nzyOIBCx9m/f392v/V2YfkAPnL0UYWPETrnb2jXm8Xd57z3MUd3yt/QrjfeLCxf708cA9Ap/42beWbOzMzMrAdzMWdmZmbWg7mYMzMzM+vBXMyZmZmZ9WAu5szMzMx6MBdziaQlkkYXnLNe0n4vHZX0rRpi/kzSK5LWSXpI0mH725+ZmZn1PD2ymJPUoVuqdPT8lKNXR3PUoGIxJ+lYYCYwOiJGAL2ArxyAcZmZmVk30aFiLs08bZB0T5odWiypb36WS9IQSc1pe6qkxyQ9IWmjpBmSrpK0RtJKSYMq9LVE0s2SlgJXSjpK0qOSXkiv8SluUOqjKeVsSO2zJDVKWgzcn8Y5P8UtAPrm+posaYWk1ZIeltQvtTdLukHScuD8MuMcJeklSSuA6bn2XpJuSWNtknR5ap8oaZmkhZLWS7pLUp2k2UBfSWslPVjha/hIivsIcDjwRpWvzczMzA4iRczMDQPmRsTJwGbgy1XiRwBTgLHATcD2iDgNWAF8tcq5AyPirIi4DZgD3B4RY1Kf81LMjcCaiGggm9m6P3f+KOCciJgCTEt9N6RxjIKs+ASuByZFxOnAKuCqXI73I2JCRMwvM8Z7gZkRMa5d+yXAljTeMcClkoamY2OBq4FTgBOAcyPiOmBHRIyMiItKdRQRPwduBV4DfpHyL24fJ+kySaskrWpsbCwzbDMzM+uJingCxMaIWJu2XwTqq8Q/ExFbga2StgBPpPaXgYYq5y7IbU8Chku/fjzbkZL6AxNIBWVEPC1psKQBKebxiNiRts8E7khxTZKaUvsZwHDg2ZS7D1mhWWoMbaR+BkbE0tT0APCFtD0ZaJB0XtofQFYI7wSej4hXU46H0nt4pMpngaTfAM4BhpIV0g9L+uOI+Jd8XEQ0Ai1VXBT5BAgzMzPrWkUUcx/ktj8ku1y5m9ZZv/Y/yM/H78nt76lhPNty23XAuFxxBoBy1V1Oy8Plt5Vpb5MCeDIiLqxhDKXOLfcgewFXRMSiNo3SxBLnlMvR3iSyYvrtlOu7wG8B/1LxLDMzMztodNYCiGbSZUvgvApxHbEYmNGyI2lk2lwGXJTaJgKbIuK9Eufn40bQOiu4Ehgv6cR07HBJJ9UyoIjYDGyRNCE15S+PLgKmSeqd8p4k6Yh0bKykoZLqgAuA5al9V0t8Ga8BZ6QxCjgb2FDLWM3MzOzg0FnF3K1khctzwJBO6mMmMDotJlgPfD21z2ppB2YDF5c5/06gX4q7BngeIM1yTQUeSsdWAp/dh3F9DZibFkDkZw3nAeuB1el2JXfTOhO5Io11HbARWJjaG4GmcgsgIuIHZJdjV5Ndpq6j9XKqmZmZHQIUUesVPesMafbwmxHxBweoy0J/M9f31BFs3bq1sHwA/fv3Z8fqlwrL1/f0UwHY+WpzYTn7fLoegN1vbyos50eOGsLO5tcKy9en/pMA7Pr5LwrL2fvYjwOwbfnKwnIeMeGMTvkb2vna64Xl6/PJ4wAKHWf//v3Z/dbbheUD+MjRRxU+Ruicv6Fdb75VXM5jju6Uv6Fdb7xZWL7enzgGoFP+Gz9ElfpJ1SGrR95nzszMzMwyRSyAKJSkucD4ds1zIuLerhhPOUWNMyKWAEuq9DUYeKrEobMj4p196c/MzMwOLt2umIuI6dWjut6BHGcq2EZWDTQzM7NDji+zmpmZmfVgXgBx6PEXbmZmPZ0XQOR0u8us1vne+PO/LCzXJ275G3asfbmwfAB9R57C1qeWVg+sUf+zzwLgpxddWljOTz14DwCbH/63wnIOPP8cfvL5ak/Dq90J338UgE3/+J3Ccg7500uA4t/3lse/V1g+gAFf+iLvfW+vJ9vttyO/OBmAD37448JyfvQzJ/L2399dWD6Ao664vFNWS779d3cWlvOob0wD4GeXziws5/H33NEpq1nf/OtvF5bvmBuuBWDbiucLy3nEuLGFrtqG1pXb1rP4MquZmZlZD+ZizszMzKwHczFnZmZm1oO5mDMzMzPrwVzMmZmZmfVgLubMzMzMejAXc4CkJZJGF5yzXtJ+P9Fe0rdqiLlS0jpJr0j6xv72ZWZmZj1XjyvmJHXo3ngdPT/l6NXRHDWoWMxJGgFcCowFTgX+QNKwAzAuMzMz60b2u5hLM08bJN2TZoYWS+qbn+WSNERSc9qeKukxSU9I2ihphqSrJK2RtFLSoAp9LZF0s6SlwJWSjpL0qKQX0mt8ihuU+mhKORtS+yxJjZIWA/encc5PcQuAvrm+JktaIWm1pIcl9UvtzZJukLQcOL/MOEdJeknSCmB6rr2XpFvSWJskXZ7aJ0paJmmhpPWS7pJUJ2k20FfSWkkPlvlYPgesjIjtEbEbWAr8UQ1fnZmZmR1EOjozNwyYGxEnA5uBarevHwFMIZtNugnYHhGnASuAr1Y5d2BEnBURtwFzgNsjYkzqc16KuRFYExENZDNb9+fOHwWcExFTgGmp74Y0jlGQFZ/A9cCkiDgdWAVclcvxfkRMiIj5ZcZ4LzAzIsa1a78E2JLGOwa4VNLQdGwscDVwCnACcG5EXAfsiIiREXFRmb7WAWdKGizpcOCLwPGlAiVdJmmVpFWNjY1l0pmZmVlP1NFLjhsjYm3afhGorxL/TERsBbZK2gI8kdpfBhqqnLsgtz0JGC79+tFsR0rqD0wgFZQR8XQqdAakmMcjYkfaPhO4I8U1SWpK7WcAw4FnU+4+ZIVmqTG0kfoZGBEtz6F6APhC2p4MNEg6L+0PICuEdwLPR8SrKcdD6T08UuWzICI2SPo28CTwK+AlYHeZ2EagpYqLIh/nZWZmZl2ro8XcB7ntD8kuV+6mdcbvsArxe3L7e2oYy7bcdh0wLlecAaBcdZfT8mD5bWXa26QAnoyIC2sYQ6lzyz3EXsAVEbGoTaM0scQ55XLsJSK+A3wn5boZKPYhfWZmZtbtdcYCiGbSZUvgvApxHbEYmNGyI2lk2lwGXJTaJgKbIuK9Eufn40bQOiu4Ehgv6cR07HBJJ9UyoIjYDGyRNCE15S+PLgKmSeqd8p4k6Yh0bKykoZLqgAuA5al9V0t8OZI+9v+3d/ZRslXlnX5+oMjHRQREiR9AghhGERDQZAEKjqNjlhqjUeOMjqiJxAkTDC5X1IgBnayoM5iJGfHjBiWoEzCSCOgyGk0AlW+4V7l8mHFGQBzFgCiCElF4549zGqqLvnTVqb1v1dv796y1V9c5Vf2c3+7u3b37nPPu6j/uAbwIOH2SrMYYY4xZO9SYzJ1EN3G5EHh4BT/AscAhfTHBNcDr+v0nLu0H3gUctZnP/wCwrn/dHwKXAkTEzcCrgNP75y4G9p0i16uBk/sCiNGzhqcA1wAb+uVKPsR9ZyIv6rNeBVwHfKrfvx648gEKIAD+tu//p4FjIuIHU2Q1xhhjzBpg8GXWiLierqBhafukkadH7387vn/+r4C/Gnn9XiOPlz23wrGOHNu+he4s1vjrbgVesML+E8e27wRetplj/RNdkcL4/r3u/+r7veYKumVCljix338PXUHGsuVG+qvCP4mIlfryJuBNqxzvaatlMsYYY8zaJt06c8YYY4wx5j5mXkC3JJJOBg4b2/3eiDh1Hnk2R6mcEXEecN4qx9oV+McVnnpmRHx/muMZY4wxZu2xUJO5iDhm9VfNny2Zs5+wHbjqC40xxhjTJL7MaowxxhiTGEVMvKyZWRv4G26MMSY7K60r2yw+M2eMMcYYkxhP5owxxhhjEuPJnDHGGGNMYjyZM8YYY4xJjCdzxhhjjDGJ8WTOGGOMMSYxnswZY4wxxiTGkzljjDHGmMQs1Nt5tY6kdwM3RMT7++0TgdvpJt0vBR4CfCoiTuiffxvwcuBG4Bbgiog4aQ7RjTHGGDMnfGZusTgD+K2R7ZcCNwP7AE+le4/WgyU9XdIhwG8CTwZeBByyhbMaY4wxZgHwZG6BiIiNwCMkPUrSAcAPgP2BZwMbgQ3AvnSTu8OBsyPizoi4Hfj05rySjpZ0uaTL169fX70fxhhjjNly+DLr4nEm8GJgd7ozdXsB74yID42+SNJxkwojYj2wNIvze7MaY4wxawifmVs8zgBeRjehOxP4PPAaSesAJD1a0iOArwDPl7Rt/9xz5xXYGGOMMfPDZ+YWjIi4WtKOwP+LiO8C35X0b4CLJAHcAbwiIi6TdA7wNeAG4HLgtnnlNsYYY8x8UISvumVF0rqIuEPS9sCXgKMjYsMqn+ZvuDHGmOxo3gEWCZ+Zy816SU8AtgVOm2AiZ4wxxpg1hs/MtYe/4cYYY7LjM3MjuADCGGOMMSYxnswZY4wxxiTGkzljjDHGmMR4MtcemqRJ+t1JX7uWnBkyZnFmyOh+L7YzQ0b3e24+M4Inc2ZzHN2oM0PGLM4MGWs4M2TM4syQsYYzQ8YazhoZm8CTOWOMMcaYxHgyZ4wxxhiTGE/mzOZY36gzQ8YszgwZazgzZMzizJCxhjNDxhrOGhmbwIsGG2OMMcYkxmfmjDHGGGMS48mcMcYYY0xiPJkzxhhjjEnMg+YdwCw+kl4dEafOO0dWJD0iIv5l3jlWQ9KuEfH9eefIiKR9gUcDl0TEHSP7nxMRn5tfsrpIeioQEXGZpCcAzwG+HhGfLXiMj0bEKwu5DgeeClwVEf8w0PErwLUR8SNJ2wFvBg4CrgH+NCJuG+A8FvhURNw4JNMKvm2AlwHfiYgvSvqPwKHAtcD6iPjZQO/ewAuBxwI/B74BnD6kzyPON6yw+zbgioj46lBva/jMnJmEt0/7CZJ2kvQuSV+X9P2+Xdvve1jpgJL+fuDn7S7pA5JOlrSrpBMlbZL0N5J+YYBvl7G2K3CppJ0l7TIw43NGHu8k6cOSrpT015IeOdD5LkkP7x8fIumbwCWSbpB0xEDnBknH97/wZ6bPda6kj0t6rKQvSLpN0mWSnjzQuU7SOyRd3btulnSxpFfNkPNY4Gzg94GrJL1g5Ok/HeDLMnZOAP4C+ICkdwLvA9YBb5b01oHOc8bap4EXLW0P8F068vi1fcYdgRMkvXlIRuAjwE/6x+8FdgLe3e8b+k/vf6Ubf1+W9HuSdhvoWeJU4LnA6yV9DHgJcAnwFOCUIcL+5/yDwLa9Zzu6Sd1Fko6cIeshwOvo/hl6NN3CwUcCfynpD2fwtkVEuLkBXLmZtgn46QDf54E3AbuP7Nu93/eFgRkP2kw7GPjuQOfn6P4Iv7nv75uAPfp9Zw/w3QNcN9Z+1n/85sCMG0YenwL8CbAncBxw1kDnppHH5wJP6R8/Hrh8oPM64CTgW8Clfb5HzfAzeSnwa8B/AG4EXtzvfyZw0UDn2cCrgMcAbwDeBuwDnEZ3VmXQ1xJY1z/eC7gceH2/vXGAL8vY2QRsDWwP/Ah4aL9/O+DKoT/rwMfp/pgf0X/8bv/4iAG+jSOPLwN26x/vMDoGpnReO5p37LmvDnRupDu58mzgw8DN/e+mo4AdB/iu7D8+CPgesHW/rRm+N5tGPNsD5/WP9xjycz7i/fzS+Om31/V93w64Zqi3tTb3AG6L0foBfyDdJGG07UV3qn5a3z8PeW4V593AP9FNPsbbnQOdo7/svzX23NS/mIE39r+InjSy77oZvzcbNpdphj8eXwce1D++eOy5oX/kRnM+DXg/cFP//Tm68Pdm0B8P4Gtj25f1H7eiuzw4xHk8Y407AAAWLUlEQVTN2PbSH6M/G/gzlHHsbBx7bujP5VZ0/wR8ATiw3zfon6Cl7zewM7ArY/+kzPAz9Eng1f3jU4FD+sePX/p5GuAcnxQ+GPh14HTg5gG+q4Bt+r7fDuzS79+WkcnolM5NwEP6xzvTXQa993gzfI+uBbYZ2X7IUsah36MWm++ZM0t8hu6/o/vdoyDpvAG+G/pT5KdFxPd6zyPpzooMvS/kWuB3I+IbK2Qc6hy91eCjD/DcRETESZLOAP5Hn+kEYNbFHB/R31ci4KGSFP1vuiEZe04GPivpXcDnJP058Hd0Z71mvk8lIr4MfFnS7wPPAn6L6RcE/VdJz6a7jBWSfiMizuovA989MNqPJR0eEV+R9Hzg1j7vPZKGvnn3TZIOXBo7EXGHpOfRXY570gBflrFzl6TtI+IndGf4lnw70Z2hnpqIuIdu7Hyy//g9Zru3eyfgCrqxE5J2j4ibJK1j+Ju1/w7wXknHA7fQXWa8ke578zsDncuyRHdP2znAOf19edPyYbp/2LYG3gp8sr+V4leBMwZmPAW4TNLFwNPpLi3TXxK+daAT4K+BiyWd3W8/Hzhd0g509yGaSZj3bNItVwN2nvR1dIP963QD/Va6Pyjvpv8vccCxXwz88mae+42Bzncwcop/ZP/jgDNn/Fo9H7gYuGlGzwljbelS0e7AR2fwHgl8gu4Szybgs3T3qzx4oO+Mwj9rB9Bdgvl7YF+6+5N+CFwNHDbQuT/d5dsfAl8BHt/v3w04dqDzMYxcEh177rCRx2tt7DxkM/sfzvIz0xP1ezOu57LC5e9ZnP3nbw/84iw+unvvDqCbyD5yloxLP4eT/GxM4XwU/W0OwMP6n4GnzvJ1BJ7Ye/YtkXHkcw4GXg/8Af2ZTrfpmt8BwkyFpA0RcdC8c2Sh/69674i4at5ZzHxpdezU6HdpZ4aMNZyLklFdlfE+EXFqf6ZvXURcVzLXWsfVrGZahl6auE8gvbpEkAzOiLhzaSK3qBkzOjNkXOkQE79Q2lfSM/tLTaP7n7O5z5nCua6Uc9JDJ3BmyFjDOfeMfVX0m4C39LseTFcEY6bAkzkzLSVO5U691MkacWbImMWZIeM4E42dsaVOrp51qZMVnDMvnzIlNS7/lHZmyFjDuQgZX0hX7PFjgIj4Dt0lbDMFLoAwVZB05eaeAoaujbbwzgwZszgzZKzEa4GDoyuk2As4U9JeEfFehp9JqeE0pgR3RURI6tZOGTsbbSbDkzkzLZP+4n8k8O+BH6zw+RcOPHYGZ4aMWZwZMk7DpGNn6+jfRSIiru8XZD1T0p5TOLaEc1LmfilvDr4szkXI+DeSPgQ8rF/Y+TXAX5aPtbbxZVazjH618Afa98wJVUtLndww1q4HzhsYL4MzQ8YszgwZ76Xg2LlJ0oFLG/0k7Hn0VaID49VwAkX7Xc2ZIWMNZ4aMdMvYfBn4W7q1+v44Iv7ntLlax9WsZhnjlUiStqZbRPYJlY63c0SMnyVZ884MGbM4FyVjqbEj6THAzyPiphWeOywiLpg2Yw3nyOcX/51R2pkhYw1nkownAC+lW4LnDLolob43NF+r+MycAUDSWyTdDuwv6UeSbu+3/4Xuxula/GOjzgwZszjnmrH02ImIb6806eqfu2BIxhrOGr8zSjszZKzhzJBxiYh4e0Q8ETiGbm288yV9caivVXxmzixD0jsj4i2rv7LY8TZGxKA3Tc/szJAxi3NRMrY6dmr0u7QzQ8YazgwZR7y7Ay8BXkb3frT7lz7GWsYFEGacP5L0IuBwuhLzL0fEWRWPtwil8fNwZsiYxbkoGVsdOzX6XdqZIWMN58JnlPSf6d7ubzfgTOC1EeG38ZoST+bMOCfTvZXV6f326yQ9KyKOmWMmYzLQ6tip0e/SzgwZazgzZNwT+INY4X3BzeR4MmfGOQLYL/rr75JOo3vfzlosQmn8PJwZMmZxLkrGVsdOjX6XdmbIWMO58Bkj4s0z5jG4AMLcn38G9hjZfiywuYVWV0U5SuNbXRIghTNDxp4mxw6F+13JmSFjDWeGjKYAPjNnxtkVuFbSpf32U4CLJJ0DEBG/PqXviaMbfRn7wUvbEXHrgIwZnBkyZnFmyAjtjp3S/a7hzJCxhjNDRlMAT+bMOH9cQiLpLcAfAdtJ+hH3Xb65C1i/Vp0ZMmZxZsg4RlNjZ4Qi/a7szJCxhjNDRlOCiHBzW9bobkj9d/3j7ejKxIe63lkh38I7M2TM4syQccTb3Ngp3e9azgwZW+6322zN68yZZah7b7yjgV0iYm9J+wAfjIgh99IgScALKVgan8GZIWMWZ4aMvbPVsVO03zWcGTLWcGbIaMrgAggzzjHAYcCPACLiG8AjZvCdDLyOrtrpKroy9pNnzJjBmSFjFmeGjNDu2Cnd7xrODBlrODNkNAXwPXNmnJ9GxF3dP/Ag6UHMtjjpwpfGV3JmyJjFmSEjtDt2Sve7hjNDxhrODBlNAXxmzoxzvqSlG6WfBXwS+PQMviyl8a0uCZDBmSEjtDt2Sve7hjNDxhrODBlNAXzPnFmGpK2A3waeTVfx9nnglBj4gyLpfLrS9WVl7MBPYFgZewZnhoxZnBky9s5Wx07RftdwZshYw5khoymDJ3OmKpKOeKDnI+L8tejMkDGLM0PGGrTab2PM9HgyZwCQtIkHuO8hIvafwb0nsE9EfFHSdsCDIuL2ob4szgwZszgXOWOrY6dGv0s7M2Ss4cyQ0ZTFBRBmief1H5feLHnpLX5eTn8JZggaKWMH9gYeA3yQYW8blMaZIWMWZ4KMrY6dGv0u7cyQsYYzQ0ZTkliAxe7cFqcBF0yybwrfV4FtgI0j+zbNmHHhnRkyZnFmyNh/fqtjp2i/K30tFz5jy/12m725mtWMs4Okw5c2JB0K7DCD76cRcdeIr1hp/II7M2TM4syQEdodO6X7XcOZIWMNZ4aMpgC+zGrG+W3gI5J2ovslfxvwmhl842Xsv0f50vhFdGbImMWZISO0O3ZK97uGM0PGGs4MGU0BXABhVkTSQ+l+Pm4b239URJw2hSdFaXxpZ4aMWZwZMo65mxo7I+4i/a7pzJCxhjNDRjMbnsyZqZC0ISIOmncOY7LR6tip0e/SzgwZazgzZDST4cusZlo00YuSlMa3uiRABmeGjNMefqIXNdrvOTszZKzhzJDRTIAnc2ZaJj2Vm6U0vtUlATI4M2SchrU2dialxuWf0s4MGWs4M2Q0kzDvclq3XI2RJQ0mfH2K0vjSzgwZszgzZJzwmGty7JTu9zycGTK23G+31ZuXJjH3ImkrSS9d5WUXTKnNUhrf6pIAGZwLn7HVsVOj36WdGTLWcGbIaMrhAgizDElfioinF/QdDHwEWFbGHhEb1rIzQ8YszgwZe2erY6dov2s4M2Ss4cyQ0ZTBkzmzDElvA+4EPgH8eGl/RNw6ozdFaXyrSwJkcC56xlbHTo1+l3ZmyFjDmSGjKYMnc2YZkq5bYXdExC9VOl6K0vhWlwTI4FyUjK2OnRr9Lu3MkLGGM0NGUwZXs5plRMQvbuFDZimNb3VJgAzOhcjY6tip0e/SzgwZazgzZDRlcAGEWYak7SUdL2l9v72PpOet9nkzkKU0vtUlATI4FyJjq2OnRr9LOzNkrOHMkNGUwZM5M86pwF3Aof32t4E/qXi8hTi7MAdnhoxZnIuSsdWxU6PfpZ0ZMtZwZshoCuDJnBln74j4b8DPACLiTgb+0chSGt/qkgAZnBkyjtDc2Okp1u+KzgwZazgzZDQF8GTOjHOXpO3oL7dI2hv46RBRRNwD/JdVXvOAz2d0ZsiYxZkh4wjNjZ2eYv2u6MyQsYYzQ0ZTAFezmmVIehZwPPAE4B+Aw4BXRcR5A30pSuNbXRIggzNDxt7Z6tgp2u8azgwZazgzZDRl8GTO3A9JuwK/Snfq/OKIuGUGV4rS+FaXBMjgzJBxxNvc2Om9xfpdy5khYw1nhoxmdjyZMwBIesC1pWKGFeKNWcu0OnZq9Lu0M0PGGs4MGU1ZPJkzAEg6t3+4LXAI8DW6/7r2By6JiMM397mreLcH3gDsERFHS9oH+OWI+MwMWRfemSFjFueiZ2x17NTod2lnhow1nBkymrK4AMIAEBHPiIhnADcAB0XEIRFxMPBk4P/MoM5SGt/qkgAZnAudsdWxU6PfpZ0ZMtZwZshoyuLJnBln34jYtLQREVcBB87gy1Ia3+qSABmcGTJCu2OndL9rODNkrOHMkNEUwG/nZcb5uqRTgI/TlZ6/Arh2Bl+W0vhWlwTI4MyQEdodO6X7XcOZIWMNZ4aMpgQR4eZ2b6O7H+I44FN9Ow7Ydgbfs4DzgZuB/wVcDxw5Y8aFd2bImMWZIWPvbHXsFO13pa/lwmdsud9uszcXQJh7kbQ1cFpEvKKwN0VpfKtLAmRwLnrGVsdOjX6XdmbIWMOZIaMphy+zmnuJiLsl7SZpm4i4axbXCmXs3+0/7iFpjyhTGr9wzgwZszgzZFyixbEDZftdy5khYw1nhoymHJ7MmXGuBy6QdA7LV4j/syk97+k/rljGDgwpY8/gzJAxizNDxlGup62xs8T1lOl3TWeGjDWcGTKaAngyZ8b5Tt+2AnYcKomuhB1JZwBHR1/9JGk/4I1r1ZkhYxZnhoxjNDV2RijS78rODBlrODNkNAXwPXNmRSTtSPc2P3fM6PlqRBy42r615syQMYszQ8YxT1NjZ8RTpN81nRky1nBmyGhmw2fmzDL6/9Q/BuzSb98CvDIirh6ozFIa3+qSABmcGTI2O3Yq9Lu4M0PGGs4MGU0hYgFKat0WpwEXAs8Y2T4SuHAGX4rS+NLODBmzODNk7J2tjp2i/a70tVz4jC332232NvcAbovVgK9Nsm9C19bAxwvnW3hnhoxZnBkyjnibGzul+13LmSFjy/12m7357bzMON+U9DZJe/XteOC6IaKIuBvYTdI2pcJlcGbImMWZIeMIzY2dnmL9rujMkLGGM0NGUwDfM2fGeQ3wduDv+u0vAa+ewXc9OUrjSzszZMzizJAR2h07pftdw5khYw1nhoymAJ7MmWVExA+AYyWtizJVSllK41tdEiCDM0PGZsdOhX4Xd2bIWMOZIaMpxLyv87otVgMOBa4BvtVvHwC8v4B3R2Bd4awL78yQMYtz0TO2OnZq9Lu0M0PGlvvtNnubewC3xWp0q8E/Ftg4su+qGXz7ARuBG/p2BfDEGTMuvDNDxizODBl7Z6tjp2i/K30tFz5jy/12m73NPYDbYjXgkv7j6ECdpZoqRWl8aWeGjFmcGTL2jlbHTtF+V/paLnzGlvvtNnvzPXNmnBslHQpEX/V2LLMtKrpDRJy7tBER50naYcaMGZwZMmZxZsgI7Y6d0v2u4cyQsYYzQ0ZTAC9NYsZ5HXAM8Gjg28CB/fZQspTGt7okQAZnhozQ7tgp3e8azgwZazgzZDQlmPepQbfFaXSLih5X2Lkz8BfAhr79ObDzWndmyJjFmSRjk2OnUr+LOjNkbLnfbmWa+m+QMQBIOi8ijqzgLV7GnsGZIWMW56JnbHXs1Oh3aWeGjDWcGTKaMvgyqxnnAknvk/Q0SQcttaEySYdKuoaulB1JB0h6/ywBMzgzZMzizJCxp8mxQ+F+V3JmyFjDmSGjKYDPzJllSDp3hd0REf92oO8S4MXAORHx5H7fVRGx3wwZF96ZIWMWZ4aM/ee3OnaK9ruGM0PGGs4MGU0ZXM1qlhERz3ig5yUdFRGnTem8UdLorruHZMvmzJAxizNJxibHTqV+F3VmyFjDmSGjKYMvs5ppef2Ur19Wxi7pjRQujV9QZ4aMWZwZMk7CWh07qzFtv+fhzJCxhjNDRjMBnsyZadHqL1lGltL4VpcEyODMkHES1urYWY1p+z0PZ4aMNZwZMpoJ8GVWMy0T32QpaWvgP0XEy0sdPIMzQ8YszgwZp2DNjZ0JqXFjdmlnhow1nBkymgnwmTkzLRP/1xURdwMvKHnwDM4MGbM4M2ScgjU3diYkw9mfDBlrODNkNBPgM3NmWi6Y9vWS3gd8Avjx0s6I2DBLhgTODBmzODNknOiY076+0X7Pw5khYw1nhoxmArw0iVmGpIcBrwT2YmSyHxHHDvSlKI1vdUmADM4MGXtnq2OnaL9rODNkrOHMkNGUwWfmzDifBS4GNgH3zCrLUhrf6pIAGZwZMvY0OXYo3O9KzgwZazgzZDQF8Jk5swxJGyJii63mXeN4GZwZMmZxLkrGVsfOouTYkr4szgwZTRlcAGHG+Zik10r6BUm7LLWKx8tyA26rNx5ncC5KxlbHTo1+l3ZmyFjDmSGjKYAvs5px7gL+O/BW7isxD+CXKh0vS2l8q0sCZHAuSsZWx06Nfpd2ZshYw5khoymAJ3NmnDcAj4uIW7bQ8Rbl7MKWdmbImMW5KBlbHTs1+l3amSFjDWeGjKYAvsxqxrka+MkWPF6W0vhWlwTI4FyUjK2OnRr9Lu3MkLGGM0NGUwAXQJhlSPoU8ETgXOCnS/vXeml8q0sCZHBmyNg7Wx07Rftdw5khYw1nhoymDL7MasY5q2+lyFIa3+qSABmcGTJCu2OndL9rODNkrOHMkNEUwGfmTFWylMa3uiRABmeGjDVotd/GmOnxZM4sQ9J1rFDRFhGDKpUkHQfcAXyG5afkb50h48I7M2TM4syQsXe2OnaK9ruGM0PGGs4MGU0ZfJnVjHPIyONtgZcAs6whlKU0vtUlATI4M2SEdsdO6X7XcGbIWMOZIaMpgM/MmVWR9JWIOHzg5/5f4FdKlrFncGbImMWZIeMDHGfNj53NHGdwv7eUM0PGGs4MGc30+MycWYak0ftptqL7L2zHGZRZSuNbXRIggzNDxmbHToV+F3dmyFjDmSGjKYMnc2ac93Df5ZefA9fTnUYfyt3AVyWVLGPP4MyQMYszQ0Zod+yU7ncNZ4aMNZwZMpoC+DKrWYakbYHfZPk6VBER7xjoO2ql/RFx2qCASZwZMmZxZsjYO1sdO0X7XcOZIWMNZ4aMpgyezJllSPoc8ENgA91/8QBExHvmFsqYBLQ6dmr0u7QzQ8YazgwZTRk8mTPLkHRVROxX0JeiNL7VJQEyODNk7J2tjp2i/a7hzJCxhjNDRlMG3zNnxrlQ0pMiYlMhX5bS+FaXBMjgzJAR2h07pftdw5khYw1nhoymAD4zZ5Yh6RrgccB1dDdIi+5+iP0LHiNFaXyrSwJkcC5ixlbHTo1+l3ZmyFjDmSGjKYPPzJlxfq2kLEtpfKtLAmRwZsjY0+TYoXC/KzkzZKzhzJDRFMBn5kxV+iUQxsvYT4qI/72WnRkyZnFmyFiDVvttjJkeT+ZMVbKUxre6JEAGZ4aMNWi138aY6fFlVlObs7ivjP1fG3JmyJjFmSFjDVrttzFmSnxmzlQlS2l8q0sCZHBmyFiDVvttjJmereYdwKx5LpT0pAadGTJmcWbIWINW+22MmRKfmTNVyVIa3+qSABmcGTLWoNV+G2Omx5M5UxVJe660PyJuWMvODBmzODNkrEGr/TbGTI8nc8YYY4wxifE9c8YYY4wxifFkzhhjjDEmMZ7MGWOMMcYkxpM5Y4wxxpjEeDJnjDHGGJOY/w+bl+KVJJsxqAAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "num_dept_reorders = get_num_dept_reorders(merged_data) # Feature\n", "plot_correlations(num_dept_reorders,\"num_reorder_dept\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Again, we don't see much interesting information, other than we can probably drop some of the features due to correlated variables.\n", "\n", "## Correlation of number of departments purchased from, and department reorder rate." ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "feature_correlation(num_dept_purchases, dept_reorder_rate)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### The dark red diagonal line is what we're interested in. This implies that the \"reorder rate\" and \"number of times purchased from each department\" variables are highly correlated. So that implies that we can use just one of the two types of features. That'll reduce our feature space greatly (since each type of feature products a feature for each department). \n", "\n", "## Correlation of number of departments purchased from, and number of department reorders." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "feature_correlation(num_dept_purchases, num_dept_reorders)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### As expected, we see fairly high correlation values. \n", "\n", "## Average time betwen purchase per department" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "time_bw_dept_purchases = get_time_bw_dept_purchases(merged_data) # Feature #get time bw dept purcahses\n", "plot_correlations(time_bw_dept_purchases, \"avg_days_bw_dept\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can see that average time between department purchases could be useful. There's some correlation between departments.\n", "\n", "## Correlation between average time between department purchase and department reorder rate." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "feature_correlation(time_bw_dept_purchases, dept_reorder_rate)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We see a weaker correlation between avg time between department reorders and department reorder rate." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# User-based features" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "def get_time_bw_orders(data):\n", " avg_time_bw = data.groupby([\"user_id\"])[\"days_since_prior_order\"].aggregate(\"mean\").reset_index(name=\"avg_days_bw_order\")\n", " avg_time_bw[\"avg_days_bw_order\"] = round(avg_time_bw[\"avg_days_bw_order\"])\n", " return avg_time_bw\n", "\n", "def get_avg_tod(data):\n", " avg_tod = data.groupby([\"user_id\"])[\"order_hour_of_day\"].aggregate(\"mean\").reset_index(name=\"avg_tod\")\n", " avg_tod[\"avg_tod\"] = round(avg_tod[\"avg_tod\"],1)\n", " return avg_tod\n", " \n", "def get_avg_dow(data):\n", " avg_dow = final_order_data.groupby([\"user_id\"])[\"order_dow\"].aggregate(\"mean\").reset_index(name=\"avg_dow\")\n", " avg_dow[\"avg_dow\"] = round(avg_dow[\"avg_dow\"],1)\n", " return avg_dow\n", "\n", "# Add to cart order is a way to get the number of items in the basket\n", "# Max \"add_to_cart_order\" is the total number of items\n", "def get_num_items_basket(data):\n", " add_to_cart_info = data.groupby([\"user_id\", \"order_id\"])[\"add_to_cart_order\"].aggregate(\"max\").reset_index(name=\"num_items\")\n", " avg_order_size = add_to_cart_info.groupby([\"user_id\"])[\"num_items\"].aggregate(\"mean\").reset_index(name=\"avg_num_items\")\n", " avg_order_size[\"avg_num_items\"] = round(avg_order_size[\"avg_num_items\"],1)\n", " return avg_order_size\n", "\n", "def get_order_size_std(data):\n", " add_to_cart_info = data.groupby([\"user_id\", \"order_id\"])[\"add_to_cart_order\"].aggregate(\"max\").reset_index(name=\"num_items\")\n", " std_order_size = add_to_cart_info.groupby([\"user_id\"])[\"num_items\"].aggregate(\"std\").reset_index(name=\"std_num_items\")\n", " std_order_size[\"std_num_items\"] = round(std_order_size[\"std_num_items\"],1)\n", " return std_order_size\n", "\n", "def get_user_reorder_rate(data):\n", " user_reorder_rate = data.groupby([\"user_id\"])[\"reordered\"].aggregate(\"mean\").reset_index(name=\"user_reorder_rate\")\n", " user_reorder_rate[\"user_reorder_rate\"] = round(user_reorder_rate[\"user_reorder_rate\"],2)\n", " return user_reorder_rate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Average time between orders" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "avg_time_bw = get_time_bw_orders(merged_data)\n", "plot_group_proportions(avg_time_bw, final_order_data, \"avg_days_bw_order\", 0, False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can see that the distribution for vegetarians vs non-vegetarians differs." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Average time of day of user visit" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "avg_tod = get_avg_tod(merged_data)\n", "plot_group_proportions(avg_tod, final_order_data, \"avg_tod\", 12, True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Again, distribution differs largely between vegetarians and non/vegetarians, and slightly but less so between parents and non-parents." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Average day of week of visit" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "avg_dow = get_avg_dow(merged_data)\n", "plot_group_proportions(avg_dow, final_order_data, \"avg_dow\", 2, True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Again, slight different between the groups, but really not much." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Average order size - using add to cart order as the number of items- should check this assumption" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "avg_order_size = get_num_items_basket(merged_data)\n", "plot_group_proportions(avg_order_size, final_order_data, \"avg_num_items\", 12, True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### There's a fairly large difference between vegetarians and non-vegetarians." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Standard deviation of order size- we want to look at a shopper's order size variation. We _could_ create 2 features: max order size, and min order size, but standard deviation could capture what we're looking for." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "std_order_size = get_order_size_std(merged_data)\n", "plot_group_proportions(std_order_size, final_order_data, \"std_num_items\", 12, True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can't really tell too much about distribution differences between the groups.\n", "\n", "## User's individual reorder rate (across all departments) ie percentage of orders that are reorders" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "user_reorder_rate = get_user_reorder_rate(merged_data)\n", "plot_group_proportions(user_reorder_rate, final_order_data, \"user_reorder_rate\", 12, True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Looking at the figure above, you can see that user reorder rate distribution does vary depending on group." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Quick prototype of a vegetarian classification model\n", "### Features:\n", "\n", "1. num_dept_purchases\n", "2. num_unique_dept --> good\n", "3. dept_reorder_rate\n", "4. dept_num_reorders\n", "5. avg_time_bw\n", "6. avg_tod\n", "7. avg_dow\n", "8. avg_order_size\n", "9. std_order_size\n", "10. avg_time_bw_dept\n", "11. user_reorder_rate\n", "\n", "Let's use 1,2,5,6,7,8,9, 10, and 11. 1, 3, 4 are all showed some degree of correlation with each other. If I cared to put more effort into this, I would take more time into investigating the relationships between variables." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 1. Merge all the data into one dataframe, and take a look at the first few rows." ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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5 rows × 51 columns

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" ], "text/plain": [ " user_id dept_1 dept_10 dept_11 dept_12 dept_13 dept_14 dept_15 \\\n", "0 1 0.0 0.0 0.0 0.0 1.0 3.0 0.0 \n", "1 10 1.0 0.0 0.0 13.0 22.0 0.0 2.0 \n", "2 100 3.0 0.0 0.0 3.0 0.0 0.0 0.0 \n", "3 1000 5.0 0.0 0.0 0.0 1.0 0.0 4.0 \n", "4 10000 56.0 1.0 6.0 56.0 108.0 13.0 23.0 \n", "\n", " dept_16 dept_17 ... avg_days_bw_dept_21 avg_days_bw_dept_3 \\\n", "0 13.0 2.0 ... 0.0 0.0 \n", "1 16.0 0.0 ... 0.0 0.0 \n", "2 2.0 0.0 ... 0.0 28.0 \n", "3 32.0 0.0 ... 7.5 6.0 \n", "4 231.0 18.0 ... 0.0 4.9 \n", "\n", " avg_days_bw_dept_4 avg_days_bw_dept_5 avg_days_bw_dept_6 \\\n", "0 25.4 0.0 0.0 \n", "1 19.4 0.0 30.0 \n", "2 24.8 0.0 0.0 \n", "3 11.4 0.0 0.0 \n", "4 5.3 0.0 5.0 \n", "\n", " avg_days_bw_dept_7 avg_days_bw_dept_8 avg_days_bw_dept_9 \\\n", "0 18.3 0.0 0.0 \n", "1 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 \n", "3 13.4 0.0 0.0 \n", "4 4.1 0.0 5.3 \n", "\n", " user_reorder_rate veg \n", "0 0.69 1 \n", "1 0.34 0 \n", "2 0.26 0 \n", "3 0.69 1 \n", "4 0.77 0 \n", "\n", "[5 rows x 51 columns]" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "Index(['user_id', 'dept_1', 'dept_10', 'dept_11', 'dept_12', 'dept_13',\n", " 'dept_14', 'dept_15', 'dept_16', 'dept_17', 'dept_18', 'dept_19',\n", " 'dept_2', 'dept_20', 'dept_21', 'dept_3', 'dept_4', 'dept_5', 'dept_6',\n", " 'dept_7', 'dept_8', 'dept_9', 'num_departments_purchased_from',\n", " 'avg_days_bw_order', 'avg_tod', 'avg_dow', 'avg_num_items',\n", " 'std_num_items', 'avg_days_bw_dept_1', 'avg_days_bw_dept_10',\n", " 'avg_days_bw_dept_11', 'avg_days_bw_dept_12', 'avg_days_bw_dept_13',\n", " 'avg_days_bw_dept_14', 'avg_days_bw_dept_15', 'avg_days_bw_dept_16',\n", " 'avg_days_bw_dept_17', 'avg_days_bw_dept_18', 'avg_days_bw_dept_19',\n", " 'avg_days_bw_dept_2', 'avg_days_bw_dept_20', 'avg_days_bw_dept_21',\n", " 'avg_days_bw_dept_3', 'avg_days_bw_dept_4', 'avg_days_bw_dept_5',\n", " 'avg_days_bw_dept_6', 'avg_days_bw_dept_7', 'avg_days_bw_dept_8',\n", " 'avg_days_bw_dept_9', 'user_reorder_rate', 'veg'],\n", " dtype='object')" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Merge all the features into one dataframe\n", "model_data = num_dept_purchases.merge(\n", " num_unique_dept, on =\"user_id\").merge(\n", " avg_time_bw, on = \"user_id\").merge(\n", " avg_tod, on = \"user_id\").merge(\n", " avg_dow, on = \"user_id\").merge(\n", " avg_order_size, on = \"user_id\").merge(\n", " std_order_size, on = \"user_id\").merge(\n", " time_bw_dept_purchases, on = \"user_id\").merge(\n", " user_reorder_rate, on = \"user_id\")\n", "\n", "model_data = model_data.merge(\n", " final_order_data[[\"user_id\", \"veg\"]].drop_duplicates(), on = \"user_id\")\n", "\n", "# Take a look at the data\n", "model_data.head()\n", "model_data.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 2. Remove the \"meat seafood\" department (department 12) from the dataset. We remove it because we used this column to define if someone is a vegetarian or not. Leaving this column would result in the model learning this- it would learn that someone is a vegetarian if they have purchased from the meat seafood department. We want to uncover _other_ information in the data, so we'll remove any trace of this department." ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "model_data.drop(\"dept_12\", inplace=True, axis=1)\n", "model_data.drop(\"avg_days_bw_dept_12\", inplace=True, axis=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 3. Let's look at the distribution of data- do we have a balance dataset?" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "92318" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "113891" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "0.4476914198701318" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model_data[model_data.veg==1].user_id.nunique()\n", "model_data[model_data.veg==0].user_id.nunique()\n", "model_data[model_data.veg==1].user_id.nunique()/model_data.user_id.nunique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 44% of our shoppers are vegetarian (as defined by having _not_ bought from the meat/seafood category). This isn't horribly imbalanced, it's actually pretty fine. But to illustrate one way to rebalance an imbalanced dataset, let's pretend this is a horrible imbalance that we absolutely must fix.\n", "\n", "### Step 3. Fix the imbalance. We have a decent amount of shoppers who are not vegetarian, so let's undersample. We have 92318 shoppers who are vegetarian, so we'll get that many shoppers who are not vegetarian." ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['dept_1', 'dept_10', 'dept_11', 'dept_13', 'dept_14', 'dept_15',\n", " 'dept_16', 'dept_17', 'dept_18', 'dept_19', 'dept_2', 'dept_20',\n", " 'dept_21', 'dept_3', 'dept_4', 'dept_5', 'dept_6', 'dept_7', 'dept_8',\n", " 'dept_9', 'num_departments_purchased_from', 'avg_days_bw_order',\n", " 'avg_tod', 'avg_dow', 'avg_num_items', 'std_num_items',\n", " 'avg_days_bw_dept_1', 'avg_days_bw_dept_10', 'avg_days_bw_dept_11',\n", " 'avg_days_bw_dept_13', 'avg_days_bw_dept_14', 'avg_days_bw_dept_15',\n", " 'avg_days_bw_dept_16', 'avg_days_bw_dept_17', 'avg_days_bw_dept_18',\n", " 'avg_days_bw_dept_19', 'avg_days_bw_dept_2', 'avg_days_bw_dept_20',\n", " 'avg_days_bw_dept_21', 'avg_days_bw_dept_3', 'avg_days_bw_dept_4',\n", " 'avg_days_bw_dept_5', 'avg_days_bw_dept_6', 'avg_days_bw_dept_7',\n", " 'avg_days_bw_dept_8', 'avg_days_bw_dept_9', 'user_reorder_rate'],\n", " dtype='object')" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" }, { "name": "stdout", "output_type": "stream", "text": [ "We have 49 features.\n" ] } ], "source": [ "# Fix this cell\n", "num_veg = len(model_data[model_data['veg'] == 1])\n", "veg_indices = model_data[model_data.veg == 0].index #indices of non veg\n", "random_indices = np.random.choice(veg_indices, num_veg, replace=False) # get random indices of nonparents\n", "veg_indices = model_data[model_data.veg == 1].index # get indices of veg\n", "under_sample_indices = np.concatenate([veg_indices,random_indices])\n", "under_sample = model_data.loc[under_sample_indices]\n", "# New X and y\n", "features = model_data.columns\n", "X = under_sample[features.drop([\"user_id\",\"veg\"])]\n", "y = under_sample[[\"veg\"]]\n", "X.columns\n", "print(\"We have %s features.\" %len(features))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 4. Test-train split on the balanced dataset. We _should_ do cross validation (ie fit model to training set, tune parameters on cross validation set, then test on test set). " ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "We have 61777 shoppers who are not veg in the train set.\n", "We have 61929 shoppers who are veg in the train set.\n", "We have 30541 shoppers who are not veg in the test set.\n", "We have 30389 shoppers who are veg in the test set.\n" ] } ], "source": [ "from sklearn.model_selection import train_test_split\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)\n", "print(\"We have %s shoppers who are not veg in the train set.\" \n", " %y_train[y_train.veg==0].index.nunique())\n", "print(\"We have %s shoppers who are veg in the train set.\" \n", " %y_train[y_train.veg==1].index.nunique())\n", "print(\"We have %s shoppers who are not veg in the test set.\" \n", " %y_test[y_test.veg==0].index.nunique())\n", "print(\"We have %s shoppers who are veg in the test set.\" \n", " %y_test[y_test.veg==1].index.nunique())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 5. Do logistic regression. Or your model of choice." ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [], "source": [ "# Helper functions\n", "def inspect_df(predictions, y_test):\n", " true_vs_pred = np.hstack((predictions, y_test))\n", " true_df = pd.DataFrame(true_vs_pred)\n", " true_df.columns = [\"Predicted\", \"Actual\"]\n", " return true_df\n", "\n", "def accuracy_stats(df):\n", " fn = len(true_vs_pred[(true_vs_pred.Predicted==0)&(true_vs_pred.Actual==1)])\n", " tn = len(true_vs_pred[(true_vs_pred.Predicted==0)&(true_vs_pred.Actual==0)])\n", " fp = len(true_vs_pred[(true_vs_pred.Predicted==1)&(true_vs_pred.Actual==0)])\n", " tp = len(true_vs_pred[(true_vs_pred.Predicted==1)&(true_vs_pred.Actual==1)])\n", " print(\"There are %s false positives.\"%fp)\n", " print(\"There are %s false negatives.\"%fn)\n", " print(\"There are %s true positives.\"%tp)\n", " print(\"There are %s true negatives.\"%tn)\n", " return fp, fn, tp, tn" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n", " intercept_scaling=1, max_iter=100, multi_class='warn',\n", " n_jobs=None, penalty='l2', random_state=None, solver='warn',\n", " tol=0.0001, verbose=0, warm_start=False)" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/html": [ "
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" ], "text/plain": [ " Predicted Actual\n", "0 0 1\n", "1 0 1\n", "2 0 0\n", "3 1 1\n", "4 1 1\n", "5 0 0\n", "6 0 0\n", "7 0 0\n", "8 1 0\n", "9 0 1" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.linear_model import LogisticRegression\n", "# Fit the out of the box model- we won't be doing any parameter tuning since it's a POC\n", "lr = LogisticRegression()\n", "lr.fit(X_train, y_train)\n", "score = lr.score(X_test, y_test)\n", "# Get predictions on the test set from the trained model\n", "preds = pd.DataFrame(lr.predict(X_test),index=y_test.index)\n", "preds.columns = [\"prediction\"]\n", "# Inspect results\n", "true_vs_pred = inspect_df(preds,y_test)\n", "true_vs_pred.head(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Our model has been trained and we've made some predictions. It looks ok- 4 out of the 10 examples above are misclassified. That's not _sooo_ bad. What we're aiming for in this first attempt is a model that is better than random guessing.\n", "#### Let's look at the number of true positives, true negatives, false positives, and true positives." ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "There are 6276 false positives.\n", "There are 7219 false negatives.\n", "There are 23170 true positives.\n", "There are 24265 true negatives.\n" ] } ], "source": [ "fp, fn, tp, tn = accuracy_stats(true_vs_pred)" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total missclassified: 13495\n", "Total correct: 47435\n", "So 0.78 percent are correct.\n" ] } ], "source": [ "print(\"Total missclassified: \" + str(fp + fn))\n", "print(\"Total correct: \" + str(tp + tn))\n", "print(\"So %s percent are correct.\"%round(score,2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### The results are good, actually. 78% of our vegetarian/non-vegetarian shoppers in the test set are classified correctly. Considering we removed any data that indicates a purchase from the meat department, these results are good. This means that there are other details, we could call them \"latencies\" in the data, that indicate that someone is a vegetarian. Maybe the deli department contains mostly meat products?\n", "\n", "## Let's look at feature importance for all examples.\n", "#### A typical way to look at feature importance for logistic regression models is to consider the coefficient values, coefficient standard error, and coefficient Z scores for each input variable or feature. Let's break down what these things mean.\n", "1. Coefficient value: We'll explain this by example. Let's use the feature \"number of times purchased from the bulk food department.\" Let's assume the coefficient (which is learned by the model during training) is 0.05. If this was linear regression, we would say that the mean change in the response variable (vegetarian or not) is 0.05, for each unit change in \"number of times purchased from the bulk food department.\" In logistic regression, we would compute e^0.05 = 1.05, so that means that for each increase in number of times purchased from the bulk food department, the odds of someone being a parent is 1.05 times as large. A positive coefficient value means the feature is indicative of the positive (in this case, vegetarian) class, while a negative coefficient is indicative of the negative (not vegetarian) class.\n", "2. Standard error: An estimate of the variation of the coefficient value. The coefficient value is an estimate, and can vary across different cases during training. It's like a measure of the precision of the estimate of the coefficient value. We want the coefficient value to be large (meaning it's important) relative to its standard error (meaning the estimate is fairly precise).\n", "3. Z score: Coefficient divided by its standard error. A non-significant Z-score implies that the feature can be dropped from the model. Essentially looking at Z-score is a \"Wald test\" where we test the null hypothesis that the coefficient in question is zero, while all others are not. A Z-score of greater than approximately |2| is significant at the 5% level. So we'll look for parameters with Z-scores greater than |2|- those are the ones that will be important." ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Optimization terminated successfully.\n", " Current function value: 0.519442\n", " Iterations 6\n", " Logit Regression Results \n", "==============================================================================\n", "Dep. Variable: veg No. Observations: 123706\n", "Model: Logit Df Residuals: 123659\n", "Method: MLE Df Model: 46\n", "Date: Thu, 29 Nov 2018 Pseudo R-squ.: 0.2506\n", "Time: 15:03:44 Log-Likelihood: -64258.\n", "converged: True LL-Null: -85746.\n", " LLR p-value: 0.000\n", "==================================================================================================\n", " coef std err z P>|z| [0.025 0.975]\n", "--------------------------------------------------------------------------------------------------\n", "dept_1 -0.0044 0.001 -7.875 0.000 -0.006 -0.003\n", "dept_10 0.0663 0.007 9.936 0.000 0.053 0.079\n", "dept_11 0.0196 0.002 11.385 0.000 0.016 0.023\n", "dept_13 -0.0030 0.001 -3.193 0.001 -0.005 -0.001\n", "dept_14 0.0144 0.001 11.372 0.000 0.012 0.017\n", "dept_15 -0.0059 0.001 -4.870 0.000 -0.008 -0.004\n", "dept_16 -0.0014 0.000 -4.287 0.000 -0.002 -0.001\n", "dept_17 0.0034 0.001 3.243 0.001 0.001 0.006\n", "dept_18 0.0005 0.001 0.525 0.600 -0.001 0.002\n", "dept_19 0.0066 0.000 15.271 0.000 0.006 0.007\n", "dept_2 0.0605 0.008 7.122 0.000 0.044 0.077\n", "dept_20 0.0020 0.001 1.989 0.047 2.9e-05 0.004\n", "dept_21 0.0633 0.006 10.492 0.000 0.052 0.075\n", "dept_3 -0.0061 0.001 -5.891 0.000 -0.008 -0.004\n", "dept_4 -0.0036 0.000 -18.099 0.000 -0.004 -0.003\n", "dept_5 0.0069 0.001 5.131 0.000 0.004 0.010\n", "dept_6 0.0392 0.003 13.485 0.000 0.033 0.045\n", "dept_7 0.0040 0.000 9.814 0.000 0.003 0.005\n", "dept_8 -0.0008 0.002 -0.424 0.671 -0.004 0.003\n", "dept_9 -0.0211 0.002 -13.467 0.000 -0.024 -0.018\n", "num_departments_purchased_from -0.4109 0.004 -105.153 0.000 -0.419 -0.403\n", "avg_days_bw_order -0.0285 0.005 -6.032 0.000 -0.038 -0.019\n", "avg_tod 0.1772 0.003 66.030 0.000 0.172 0.182\n", "avg_dow 0.2088 0.006 32.349 0.000 0.196 0.221\n", "avg_num_items 0.0323 0.004 7.557 0.000 0.024 0.041\n", "std_num_items 0.0216 0.002 11.742 0.000 0.018 0.025\n", "avg_days_bw_dept_1 -0.0028 0.001 -3.234 0.001 -0.005 -0.001\n", "avg_days_bw_dept_10 0.0235 0.002 11.223 0.000 0.019 0.028\n", "avg_days_bw_dept_11 0.0178 0.001 21.174 0.000 0.016 0.019\n", "avg_days_bw_dept_13 0.0012 0.001 1.379 0.168 -0.001 0.003\n", "avg_days_bw_dept_14 0.0136 0.001 17.142 0.000 0.012 0.015\n", "avg_days_bw_dept_15 -0.0020 0.001 -2.436 0.015 -0.004 -0.000\n", "avg_days_bw_dept_16 -0.0031 0.001 -2.416 0.016 -0.006 -0.001\n", "avg_days_bw_dept_17 0.0151 0.001 18.740 0.000 0.014 0.017\n", "avg_days_bw_dept_18 0.0163 0.001 13.047 0.000 0.014 0.019\n", "avg_days_bw_dept_19 0.0122 0.001 13.471 0.000 0.010 0.014\n", "avg_days_bw_dept_2 0.0179 0.002 9.986 0.000 0.014 0.021\n", "avg_days_bw_dept_20 0.0009 0.001 1.104 0.270 -0.001 0.002\n", "avg_days_bw_dept_21 0.0147 0.001 10.041 0.000 0.012 0.018\n", "avg_days_bw_dept_3 0.0039 0.001 4.815 0.000 0.002 0.006\n", "avg_days_bw_dept_4 -0.0114 0.001 -8.044 0.000 -0.014 -0.009\n", "avg_days_bw_dept_5 0.0226 0.002 12.682 0.000 0.019 0.026\n", "avg_days_bw_dept_6 0.0059 0.001 6.411 0.000 0.004 0.008\n", "avg_days_bw_dept_7 0.0104 0.001 11.955 0.000 0.009 0.012\n", "avg_days_bw_dept_8 0.0129 0.002 7.524 0.000 0.010 0.016\n", "avg_days_bw_dept_9 -0.0003 0.001 -0.318 0.751 -0.002 0.001\n", "user_reorder_rate 1.5783 0.041 38.654 0.000 1.498 1.658\n", "==================================================================================================\n" ] } ], "source": [ "# Scikit learn doesn't allow error estimate for inference.\n", "# Let's use Statsmodel instead\n", "import statsmodels.api as sm\n", "lr_sm = sm.Logit(y_train, X_train).fit()\n", "print(lr_sm.summary())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can see that the important features are the ones with Z-scores of approximately greater than |2| are dept_1, dept_10, dept_11... etc. There are a few features that we can actually throw out. If we were building a real model (one that isn't just a proof of concept), we'd want to do some sort of variable selection.\n", "\n", "## Let's look into feature importance for a few examples to make things a bit more concrete.\n", "\n", "#### The LIME package (Local Interpretable Model-Agnostic Explanations) gives a local (i.e. single classification) explanation of feature importance. Similar to how what is important to one person's identity may be irrelevant to someone else's, a feature may be more important to the classification of one shopper, while for another shopper, it's a different feature that is the most important. LIME helps us look at feature importance on a case by case basis." ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [], "source": [ "import lime # Local Interpretable Model-Agnostic Explanations\n", "import lime.lime_tabular # Since we're using dataframes" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "# Input our data as arrays\n", "predictors = list(X_train.columns)\n", "train_array = X_train.as_matrix()\n", "test_array = X_test.as_matrix()\n", "# Create the explainer from training data\n", "explainer = lime.lime_tabular.LimeTabularExplainer(train_array, feature_names=predictors, class_names=[0,1])" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": [ "# Explain instances in the test data\n", "def explain_prediction(index, num_features):\n", " explain_lr = explainer.explain_instance(test_array[index], lr.predict_proba, num_features = num_features) \n", " explain_lr.show_in_notebook()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Let's look at index 0, which was predicted to not be a vegetarian and is in fact a vegetarian. This is a false negative. Let's start with looking at the feature importance for all features." ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "explain_prediction(0, len(predictors))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Looking at the middle chart, you can see that the majority of the features are not important for classification. Let's instead look at the 10 most important features." ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "explain_prediction(0, 10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Now it's much easier to digest! We can see what our most important features are in determining who is a vegetarian or not. For example, the most important feature for this instance is the number of departments purchased from- this had a Z-score of -105.153 in the analysis we did above. This feature was the leading factor in classifying the person as not vegetarian. The second most important feature the model used was average days between orders, with the feature this time pushing the classification more towards a postive vegetarian classification.\n", "\n", "#### Let's look at index 4, since the shopper at index 9 is predicted to be vegetarian, and actually is. So this is a true positive." ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", "
\n", " \n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "explain_prediction(4, 10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We see again that number of departments purchased from is now an indication of the shopper being a vegetarian. This shopper's specific average days between orders is in this case indicative of them not being a vegetarian." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Conclusion\n", "\n", "\n", "### Recall our initial question: Given a shopper's entire purchase history, can we predict if they are a vegetarian? Can we do this while explicitly excluding meat purchases? The answer? Yes, we can train a classifier to determine if someone is a vegetarian or not, using their entire shopping history, and excluding purchases from the meat department.\n", "\n", "## Improvements for the future:\n", "1. I could always improve my plotting.\n", "2. I made a lot of assumptions. By selecting shoppers who have never purchased from the meat/seafood department, I could be selecting shoppers who just purchase their meat somewhere else. Or I could be selecting shoppers who don't shop often enough to have meat/seafood purchases in this dataset. I didn't even check the minimum number of orders of each shopper, but had I done this, I may have seen that \"vegetarians\" have _somehow_ shopped far less than non-vegetarians!\n", "3. My variable naming could be improved.\n", "4. I could use an algorithm that includes feature selection. I could try different algorithms, too. (Actually, I tried XGBoost as well and it gave me a 3% increase in accuracy.\n", "5. Speaking of accuracy, is this the best method? Do I want to penalize false negatives or false positives? If this was a recommendation system, would vegetarians be offended by being recommended meat, or would meat eaters be offended by _not_ being recommended it? " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }