{ "cells": [ { "cell_type": "markdown", "id": "005aa705-29f4-463b-9b5a-e39f615c0654", "metadata": {}, "source": [ "\\[_In case you’re unable to see the atoti visualizations in GitHub, try viewing the notebook in [nbviewer](https://nbviewer.org/github/atoti/notebooks/blob/master/notebooks/burritos/main.ipynb)._]" ] }, { "cell_type": "code", "execution_count": 1, "id": "f443131b-51a9-4d8b-bc83-063a645df312", "metadata": {}, "outputs": [], "source": [ "# import relevant libraries\n", "import re\n", "\n", "import atoti as tt\n", "import numpy as np\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "id": "83e8778f-664c-4e2a-87a7-e8637e047407", "metadata": {}, "outputs": [], "source": [ "# load in data\n", "df = pd.read_csv(\"./data/burritos_01022018.csv\")" ] }, { "cell_type": "code", "execution_count": 3, "id": "a1c3c63e-c78e-4002-849c-930566a6c94c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['Location', 'Burrito', 'Date', 'Neighborhood', 'Address', 'URL', 'Yelp',\n", " 'Google', 'Chips', 'Cost', 'Hunger', 'Mass (g)', 'Density (g/mL)',\n", " 'Length', 'Circum', 'Volume', 'Tortilla', 'Temp', 'Meat', 'Fillings',\n", " 'Meat:filling', 'Uniformity', 'Salsa', 'Synergy', 'Wrap', 'overall',\n", " 'Rec', 'Reviewer', 'Notes', 'Unreliable', 'NonSD', 'Beef', 'Pico',\n", " 'Guac', 'Cheese', 'Fries', 'Sour cream', 'Pork', 'Chicken', 'Shrimp',\n", " 'Fish', 'Rice', 'Beans', 'Lettuce', 'Tomato', 'Bell peper', 'Carrots',\n", " 'Cabbage', 'Sauce', 'Salsa.1', 'Cilantro', 'Onion', 'Taquito',\n", " 'Pineapple', 'Ham', 'Chile relleno', 'Nopales', 'Lobster', 'Queso',\n", " 'Egg', 'Mushroom', 'Bacon', 'Sushi', 'Avocado', 'Corn', 'Zucchini'],\n", " dtype='object')" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# explore column headers\n", "df.columns" ] }, { "cell_type": "code", "execution_count": 4, "id": "70cd32d9-9e67-446b-8c99-0581729a413c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Location | \n", "Burrito | \n", "Date | \n", "Neighborhood | \n", "Address | \n", "URL | \n", "Yelp | \n", "Chips | \n", "Cost | \n", "... | \n", "Nopales | \n", "Lobster | \n", "Queso | \n", "Egg | \n", "Mushroom | \n", "Bacon | \n", "Sushi | \n", "Avocado | \n", "Corn | \n", "Zucchini | \n", "|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "Donato's taco shop | \n", "California | \n", "1/18/2016 | \n", "Miramar | \n", "6780 Miramar Rd | \n", "http://donatostacoshop.net/ | \n", "3.5 | \n", "4.2 | \n", "NaN | \n", "6.49 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
1 | \n", "Oscar's Mexican food | \n", "California | \n", "1/24/2016 | \n", "San Marcos | \n", "225 S Rancho Santa Fe Rd | \n", "http://www.yelp.com/biz/oscars-mexican-food-sa... | \n", "3.5 | \n", "3.3 | \n", "NaN | \n", "5.45 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2 | \n", "Oscar's Mexican food | \n", "Carnitas | \n", "1/24/2016 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "4.85 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
3 | \n", "Oscar's Mexican food | \n", "Carne asada | \n", "1/24/2016 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "5.25 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
4 | \n", "Pollos Maria | \n", "California | \n", "1/27/2016 | \n", "Carlsbad | \n", "3055 Harding St | \n", "http://pollosmaria.com/ | \n", "4.0 | \n", "3.8 | \n", "x | \n", "6.59 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
5 rows × 66 columns
\n", "\n", " | Yelp | \n", "Cost | \n", "Hunger | \n", "Mass (g) | \n", "Density (g/mL) | \n", "Length | \n", "Circum | \n", "Volume | \n", "Tortilla | \n", "Temp | \n", "Meat | \n", "Fillings | \n", "Meat:filling | \n", "Uniformity | \n", "Salsa | \n", "Synergy | \n", "Wrap | \n", "overall | \n", "Queso | \n", "|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
count | \n", "82.000000 | \n", "82.000000 | \n", "378.000000 | \n", "382.000000 | \n", "22.000000 | \n", "22.000000 | \n", "251.000000 | \n", "249.000000 | \n", "249.000000 | \n", "385.000000 | \n", "365.000000 | \n", "373.000000 | \n", "383.000000 | \n", "377.000000 | \n", "383.000000 | \n", "363.000000 | \n", "383.000000 | \n", "383.000000 | \n", "383.000000 | \n", "0.0 | \n", "
mean | \n", "3.898780 | \n", "4.174390 | \n", "7.048280 | \n", "3.499895 | \n", "546.181818 | \n", "0.675277 | \n", "20.072988 | \n", "22.098996 | \n", "0.785462 | \n", "3.486104 | \n", "3.741096 | \n", "3.596247 | \n", "3.527546 | \n", "3.564403 | \n", "3.422324 | \n", "3.348485 | \n", "3.576371 | \n", "3.995561 | \n", "3.604813 | \n", "NaN | \n", "
std | \n", "0.470748 | \n", "0.377389 | \n", "1.517983 | \n", "0.808791 | \n", "144.445619 | \n", "0.080468 | \n", "2.060584 | \n", "1.795010 | \n", "0.153465 | \n", "0.787282 | \n", "0.975079 | \n", "0.835896 | \n", "0.812342 | \n", "0.987858 | \n", "1.061032 | \n", "0.927714 | \n", "0.896275 | \n", "1.107876 | \n", "0.761901 | \n", "NaN | \n", "
min | \n", "2.500000 | \n", "2.900000 | \n", "2.990000 | \n", "0.500000 | \n", "350.000000 | \n", "0.560000 | \n", "15.000000 | \n", "17.000000 | \n", "0.400000 | \n", "1.000000 | \n", "1.000000 | \n", "1.000000 | \n", "1.000000 | \n", "0.500000 | \n", "0.000000 | \n", "0.000000 | \n", "1.000000 | \n", "0.000000 | \n", "1.000000 | \n", "NaN | \n", "
25% | \n", "3.500000 | \n", "4.000000 | \n", "6.250000 | \n", "3.000000 | \n", "450.000000 | \n", "0.619485 | \n", "18.500000 | \n", "21.000000 | \n", "0.680000 | \n", "3.000000 | \n", "3.000000 | \n", "3.000000 | \n", "3.000000 | \n", "3.000000 | \n", "2.500000 | \n", "3.000000 | \n", "3.000000 | \n", "3.500000 | \n", "3.000000 | \n", "NaN | \n", "
50% | \n", "4.000000 | \n", "4.200000 | \n", "6.950000 | \n", "3.500000 | \n", "540.000000 | \n", "0.658099 | \n", "20.000000 | \n", "22.000000 | \n", "0.770000 | \n", "3.500000 | \n", "4.000000 | \n", "3.750000 | \n", "3.500000 | \n", "4.000000 | \n", "3.500000 | \n", "3.500000 | \n", "3.800000 | \n", "4.000000 | \n", "3.750000 | \n", "NaN | \n", "
75% | \n", "4.000000 | \n", "4.400000 | \n", "7.750000 | \n", "4.000000 | \n", "595.000000 | \n", "0.721726 | \n", "21.500000 | \n", "23.000000 | \n", "0.880000 | \n", "4.000000 | \n", "4.500000 | \n", "4.000000 | \n", "4.000000 | \n", "4.000000 | \n", "4.000000 | \n", "4.000000 | \n", "4.000000 | \n", "5.000000 | \n", "4.100000 | \n", "NaN | \n", "
max | \n", "4.500000 | \n", "5.000000 | \n", "25.000000 | \n", "5.000000 | \n", "925.000000 | \n", "0.865672 | \n", "26.000000 | \n", "29.000000 | \n", "1.540000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "5.000000 | \n", "NaN | \n", "
\n", " | Location | \n", "Burrito | \n", "variable | \n", "value | \n", "
---|---|---|---|---|
0 | \n", "Donato's taco shop | \n", "California | \n", "Circum_norm | \n", "NaN | \n", "
1 | \n", "Oscar's Mexican food | \n", "California | \n", "Circum_norm | \n", "NaN | \n", "
2 | \n", "Oscar's Mexican food | \n", "Carnitas | \n", "Circum_norm | \n", "NaN | \n", "
3 | \n", "Oscar's Mexican food | \n", "Carne asada | \n", "Circum_norm | \n", "NaN | \n", "
4 | \n", "Pollos Maria | \n", "California | \n", "Circum_norm | \n", "NaN | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
1920 | \n", "Rigoberto's Taco Shop | \n", "California | \n", "Cost_norm | \n", "1.753748 | \n", "
1921 | \n", "Rigoberto's Taco Shop | \n", "California | \n", "Cost_norm | \n", "1.753748 | \n", "
1922 | \n", "Burrito Box | \n", "Steak with guacamole | \n", "Cost_norm | \n", "3.866424 | \n", "
1923 | \n", "Taco Stand | \n", "California | \n", "Cost_norm | \n", "2.226261 | \n", "
1924 | \n", "Taco Stand | \n", "California | \n", "Cost_norm | \n", "2.226261 | \n", "
1925 rows × 4 columns
\n", "\n", " | Location | \n", "Burrito | \n", "Date | \n", "Neighborhood | \n", "Address | \n", "URL | \n", "Yelp | \n", "Chips | \n", "Cost | \n", "... | \n", "Bacon | \n", "Sushi | \n", "Avocado | \n", "Corn | \n", "Zucchini | \n", "Circum_norm | \n", "Volume_norm | \n", "Length_norm | \n", "Mass_norm | \n", "Cost_norm | \n", "|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "Donato's taco shop | \n", "California | \n", "1/18/2016 | \n", "Miramar | \n", "6780 Miramar Rd | \n", "http://donatostacoshop.net/ | \n", "3.5 | \n", "4.2 | \n", "N/A | \n", "6.49 | \n", "... | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "1.590186 | \n", "
1 | \n", "Nico's Taco Shop | \n", "Carnitas | \n", "1/30/2016 | \n", "N/A | \n", "N/A | \n", "N/A | \n", "NaN | \n", "NaN | \n", "N/A | \n", "6.99 | \n", "... | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "1.817356 | \n", "
2 | \n", "Taco stand | \n", "California | \n", "5/6/2016 | \n", "N/A | \n", "N/A | \n", "N/A | \n", "NaN | \n", "NaN | \n", "N/A | \n", "7.49 | \n", "... | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "4.166667 | \n", "2.894737 | \n", "3.636364 | \n", "NaN | \n", "2.044525 | \n", "
3 | \n", "Lolita's taco shop | \n", "2 in 1 | \n", "5/12/2016 | \n", "N/A | \n", "N/A | \n", "N/A | \n", "NaN | \n", "NaN | \n", "N/A | \n", "8.75 | \n", "... | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "4.354167 | \n", "2.631579 | \n", "2.527273 | \n", "NaN | \n", "2.616992 | \n", "
4 | \n", "Rigoberto's Taco Shop | \n", "Carnitas | \n", "5/13/2016 | \n", "N/A | \n", "N/A | \n", "N/A | \n", "NaN | \n", "NaN | \n", "N/A | \n", "7.50 | \n", "... | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "N/A | \n", "4.583333 | \n", "4.824561 | \n", "7.727273 | \n", "NaN | \n", "2.049069 | \n", "
5 rows × 71 columns
\n", "