{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data scraping, data wrangling, data analytics, exploratory data analysis, advaced plotting and clustering with love."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In this final tutorial we address clustering and advanced plotting. \n",
"\n",
"Unsupervised learning or clustering consists in finding hidden structures in unlabelled data. We are going to use k-means clustering [1], which is included with **scipy** [2]. \n",
"\n",
"As we already have seen, the dataset is labelled. Nevertheless, we are going to compare the solution obtained with k-means clustering and the labelled data.\n",
"\n",
"Finally, we are going to do advanced plotting using **matplotlib** [3] and **seaborn** [4]."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"#import json\n",
"#import seaborn as sns"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's use **pandas** [5] to load the csv file and use column 0 in the dataset as the row labels of the created `DataFrame`,\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#shot_df = pd.read_csv('test.csv')\n",
"#shot_df = pd.read_csv(filepath_or_buffer='test.csv')\n",
"shot_df = pd.read_csv(filepath_or_buffer='test.csv',index_col=0)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To display the information in `shot_df` (we only display the first 4 rows),"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"
\n",
" \n",
" \n",
" | \n",
" GRID_TYPE | \n",
" GAME_ID | \n",
" GAME_EVENT_ID | \n",
" PLAYER_ID | \n",
" PLAYER_NAME | \n",
" TEAM_ID | \n",
" TEAM_NAME | \n",
" PERIOD | \n",
" MINUTES_REMAINING | \n",
" SECONDS_REMAINING | \n",
" ... | \n",
" ACTION_TYPE | \n",
" SHOT_TYPE | \n",
" SHOT_ZONE_BASIC | \n",
" SHOT_ZONE_AREA | \n",
" SHOT_ZONE_RANGE | \n",
" SHOT_DISTANCE | \n",
" LOC_X | \n",
" LOC_Y | \n",
" SHOT_ATTEMPTED_FLAG | \n",
" SHOT_MADE_FLAG | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Shot Chart Detail | \n",
" 21400018 | \n",
" 4 | \n",
" 2544 | \n",
" LeBron James | \n",
" 1610612739 | \n",
" Cleveland Cavaliers | \n",
" 1 | \n",
" 11 | \n",
" 20 | \n",
" ... | \n",
" Jump Shot | \n",
" 2PT Field Goal | \n",
" Mid-Range | \n",
" Right Side Center(RC) | \n",
" 16-24 ft. | \n",
" 18 | \n",
" 114 | \n",
" 148 | \n",
" 1 | \n",
" 0 | \n",
"
\n",
" \n",
" 1 | \n",
" Shot Chart Detail | \n",
" 21400018 | \n",
" 33 | \n",
" 2544 | \n",
" LeBron James | \n",
" 1610612739 | \n",
" Cleveland Cavaliers | \n",
" 1 | \n",
" 6 | \n",
" 30 | \n",
" ... | \n",
" Layup Shot | \n",
" 2PT Field Goal | \n",
" Restricted Area | \n",
" Center(C) | \n",
" Less Than 8 ft. | \n",
" 0 | \n",
" -7 | \n",
" 0 | \n",
" 1 | \n",
" 1 | \n",
"
\n",
" \n",
" 2 | \n",
" Shot Chart Detail | \n",
" 21400018 | \n",
" 53 | \n",
" 2544 | \n",
" LeBron James | \n",
" 1610612739 | \n",
" Cleveland Cavaliers | \n",
" 1 | \n",
" 4 | \n",
" 45 | \n",
" ... | \n",
" Fadeaway Jump Shot | \n",
" 2PT Field Goal | \n",
" Mid-Range | \n",
" Left Side(L) | \n",
" 8-16 ft. | \n",
" 12 | \n",
" -105 | \n",
" 63 | \n",
" 1 | \n",
" 0 | \n",
"
\n",
" \n",
" 3 | \n",
" Shot Chart Detail | \n",
" 21400018 | \n",
" 77 | \n",
" 2544 | \n",
" LeBron James | \n",
" 1610612739 | \n",
" Cleveland Cavaliers | \n",
" 1 | \n",
" 2 | \n",
" 31 | \n",
" ... | \n",
" Jump Shot | \n",
" 3PT Field Goal | \n",
" Right Corner 3 | \n",
" Right Side(R) | \n",
" 24+ ft. | \n",
" 22 | \n",
" 227 | \n",
" -16 | \n",
" 1 | \n",
" 0 | \n",
"
\n",
" \n",
"
\n",
"
4 rows × 21 columns
\n",
"
"
],
"text/plain": [
" GRID_TYPE GAME_ID GAME_EVENT_ID PLAYER_ID PLAYER_NAME \\\n",
"0 Shot Chart Detail 21400018 4 2544 LeBron James \n",
"1 Shot Chart Detail 21400018 33 2544 LeBron James \n",
"2 Shot Chart Detail 21400018 53 2544 LeBron James \n",
"3 Shot Chart Detail 21400018 77 2544 LeBron James \n",
"\n",
" TEAM_ID TEAM_NAME PERIOD MINUTES_REMAINING \\\n",
"0 1610612739 Cleveland Cavaliers 1 11 \n",
"1 1610612739 Cleveland Cavaliers 1 6 \n",
"2 1610612739 Cleveland Cavaliers 1 4 \n",
"3 1610612739 Cleveland Cavaliers 1 2 \n",
"\n",
" SECONDS_REMAINING ... ACTION_TYPE SHOT_TYPE \\\n",
"0 20 ... Jump Shot 2PT Field Goal \n",
"1 30 ... Layup Shot 2PT Field Goal \n",
"2 45 ... Fadeaway Jump Shot 2PT Field Goal \n",
"3 31 ... Jump Shot 3PT Field Goal \n",
"\n",
" SHOT_ZONE_BASIC SHOT_ZONE_AREA SHOT_ZONE_RANGE SHOT_DISTANCE \\\n",
"0 Mid-Range Right Side Center(RC) 16-24 ft. 18 \n",
"1 Restricted Area Center(C) Less Than 8 ft. 0 \n",
"2 Mid-Range Left Side(L) 8-16 ft. 12 \n",
"3 Right Corner 3 Right Side(R) 24+ ft. 22 \n",
"\n",
" LOC_X LOC_Y SHOT_ATTEMPTED_FLAG SHOT_MADE_FLAG \n",
"0 114 148 1 0 \n",
"1 -7 0 1 1 \n",
"2 -105 63 1 0 \n",
"3 227 -16 1 0 \n",
"\n",
"[4 rows x 21 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shot_df.head(4)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To force **pandas** to display all the columns, you can proceed as follows,"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#uncomment this line to display all the columns\n",
"#pd.set_option('display.max_columns', None)\n",
"\n",
"#shot_df.head(4)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These are the **scipy** modules we need to do clustering. We are going to use the `rand` function of **numpy** to generate random points."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#from numpy import vstack,array\n",
"from numpy.random import rand\n",
"from scipy.cluster.vq import kmeans,vq,whiten\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's illustrate clustering by using a simple illustrative example. First we are going to create two datasets and then we are going to use k-means clustering."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# data generation\n",
"data1 = rand(50,2) + np.array([.5,.5])\n",
"data2 = rand(50,2) + np.array([0,-.2])\n",
"\n",
"#data1 = rand(200,2) + np.array([.5,.5])\n",
"#data2 = rand(200,2) + np.array([0,-.2])\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we plot the two datasets using **matplotlib**,"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEACAYAAAC08h1NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nxpiU+f/BN5/7n80KowAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(data1[:,0],data1[:,1],'ob',markersize=4, alpha=0.6)\n",
"plt.plot(data2[:,0],data2[:,1],'or',markersize=4, alpha=0.6)\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"To do clustering, we need one single dataset. To join the datasets we can use the `concatenate` function,"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"jdata1=np.concatenate((data1,data2))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"or we can use the `vstack` function,"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"jdata2=np.vstack((data1,data2))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To check the dimension of the newly created datasets,"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(100, 2)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata1.shape"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(100, 2)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata2.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To check the object type of the newly created datasets,"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"numpy.ndarray"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(jdata1)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"numpy.ndarray"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(jdata2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To check the data type of the **numpy** arrays,"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"dtype('float64')"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata1.dtype"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"dtype('float64')"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata2.dtype"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And to check that the two arrays are equal,"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.array_equal(jdata1,jdata2)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"or in the long way,"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#uncomment this line to compare the arrays\n",
"#jdata1==jdata2\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As with a **pandas** `DataFrame`, we can also do indexing and slicing with a **numpy** array.\n",
"\n",
"To display the first row of an array,"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 10.17426978, 1.08181619])"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata1[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To display the first two rows of the array,"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 10.17426978, 1.08181619],\n",
" [ 10.66345049, 1.07132164]])"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata1[0:2]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To display the first column of the first five rows of the array,"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 10.17426978, 10.66345049, 10.20683049, 10.97340282, 10.71436518])"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata1[0:5,0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To display the second column of the first five rows of the array,"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1.08181619, 1.07132164, 1.91494455, 1.47372759, 1.48677703])"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"jdata1[0:5,1]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To plot the joined dataset using **matplotlib**,"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEACAYAAAC08h1NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# some plotting using numpy's logical indexing\n",
"plt.plot(jdata1[:,0],jdata1[:,1],'ob',markersize=4, alpha=0.6)\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To compute the clusters using K-means we proceed as follows. \n",
"\n",
"First we need to compute the centroids, in this case the centroids are choosen randomly. Alternatively, the user have the option to give the inital position of the centroids. \n",
"\n",
"In this case we want to use 2 centroids on the dataset `jdata1` and the centroid position is saved in the array `centroids`,"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# computing K-Means with K = 2 (2 clusters)\n",
"centroids,_ = kmeans(jdata1,2)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To print the information in the array `centroids`,"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 0.48544814 0.34605385]\n",
" [ 1.06113769 0.95313386]]\n"
]
}
],
"source": [
"#from pprint import pprint\n",
"#pprint(centroids)\n",
"\n",
"#centroids\n",
"\n",
"print(centroids)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we proceed to label the data using the array `centroids`, for this we use the function `vq`. \n",
"\n",
"This function assigns a label to each observation. Each observation in the input array is compared with the centroids in the label vector and assigned the label of the closest centroid."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# assign each sample to a cluster\n",
"idx,_ = vq(jdata1,centroids)\n",
"\n",
"#whiten is used to normalize a group of observations on a per feature basis.\n",
"#whitened = whiten(jdata1)\n",
"#idx,_ = vq(whitened,centroids)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Tp print the information in the array idx,"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0\n",
" 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]\n"
]
}
],
"source": [
"print(idx)\n",
"\n",
"#print(idx[0:4])\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's plot the clusters and the centroid information."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEACAYAAAC08h1NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMVbxG2NMi7GK3xhjWsz/BwW3mUti/JtcAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# some plotting using numpy's logical indexing\n",
"plt.plot(jdata1[idx==0,0],jdata1[idx==0,1],'ob',markersize=4, alpha=1)\n",
"plt.plot(jdata1[idx==1,0],jdata1[idx==1,1],'or',markersize=4, alpha=1)\n",
"\n",
"plt.plot(centroids[:,0],centroids[:,1],'sk',markersize=6)\n",
"\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's group the arrays `jdata1` and `idx` in a `DataFrame`. First we need to create an empty `DataFrame`,"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cluster1=pd.DataFrame()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can copy the arrays into the `DataFrame cluster1` as follows,"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cluster1['X']=jdata1[:,0]\n",
"cluster1['Y']=jdata1[:,1]\n",
"cluster1['LABEL']=idx\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To display the information in `cluster1` (we display the first 10 rows),"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" X | \n",
" Y | \n",
" LABEL | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 1.084007 | \n",
" 1.067920 | \n",
" 1 | \n",
"
\n",
" \n",
" 1 | \n",
" 1.118422 | \n",
" 0.787775 | \n",
" 1 | \n",
"
\n",
" \n",
" 2 | \n",
" 1.393798 | \n",
" 0.560966 | \n",
" 1 | \n",
"
\n",
" \n",
" 3 | \n",
" 0.665576 | \n",
" 0.508579 | \n",
" 0 | \n",
"
\n",
" \n",
" 4 | \n",
" 1.013516 | \n",
" 0.743290 | \n",
" 1 | \n",
"
\n",
" \n",
" 5 | \n",
" 1.348927 | \n",
" 0.891368 | \n",
" 1 | \n",
"
\n",
" \n",
" 6 | \n",
" 1.417622 | \n",
" 1.194459 | \n",
" 1 | \n",
"
\n",
" \n",
" 7 | \n",
" 1.285903 | \n",
" 1.223910 | \n",
" 1 | \n",
"
\n",
" \n",
" 8 | \n",
" 1.000396 | \n",
" 0.650109 | \n",
" 1 | \n",
"
\n",
" \n",
" 9 | \n",
" 1.194782 | \n",
" 0.538871 | \n",
" 1 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" X Y LABEL\n",
"0 1.084007 1.067920 1\n",
"1 1.118422 0.787775 1\n",
"2 1.393798 0.560966 1\n",
"3 0.665576 0.508579 0\n",
"4 1.013516 0.743290 1\n",
"5 1.348927 0.891368 1\n",
"6 1.417622 1.194459 1\n",
"7 1.285903 1.223910 1\n",
"8 1.000396 0.650109 1\n",
"9 1.194782 0.538871 1"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cluster1.head(10)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To display the last 5 rows in `cluster1`,"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" X | \n",
" Y | \n",
" LABEL | \n",
"
\n",
" \n",
" \n",
" \n",
" 95 | \n",
" 0.022988 | \n",
" 0.236782 | \n",
" 0 | \n",
"
\n",
" \n",
" 96 | \n",
" 0.624744 | \n",
" 0.722844 | \n",
" 0 | \n",
"
\n",
" \n",
" 97 | \n",
" 0.434906 | \n",
" 0.025984 | \n",
" 0 | \n",
"
\n",
" \n",
" 98 | \n",
" 0.501344 | \n",
" 0.169842 | \n",
" 0 | \n",
"
\n",
" \n",
" 99 | \n",
" 0.088473 | \n",
" 0.799280 | \n",
" 0 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" X Y LABEL\n",
"95 0.022988 0.236782 0\n",
"96 0.624744 0.722844 0\n",
"97 0.434906 0.025984 0\n",
"98 0.501344 0.169842 0\n",
"99 0.088473 0.799280 0"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cluster1.tail()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"At this point we have created the `DataFrame cluster1`, which you can use to do some plotting or conduct some data analytics as we have done in the previous tutorials."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's complicate things a little bit more. In this example we are going to generate a bigger dataset with a different structure."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# data generation\n",
"data1 = rand(200,2) + np.array([10,1])\n",
"data2 = rand(200,2) + np.array([9,0.5])\n",
"data3 = rand(200,2) + np.array([9.5,0])\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To pot the original datasets,"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEACAYAAAC9Gb03AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# some plotting using numpy's logical indexing\n",
"plt.plot(data1[:,0],data1[:,1],'ob',markersize=4, alpha=0.6)\n",
"plt.plot(data2[:,0],data2[:,1],'or',markersize=4, alpha=0.6)\n",
"plt.plot(data3[:,0],data3[:,1],'og',markersize=4, alpha=0.6)\n",
"\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Remember, to do the clustering we need one single dataset, to concatenate the arrays we proceed as follows,"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"jdata1=np.concatenate((data1,data2,data3))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can compute the clusters. Notice that we are using 3 centroids."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# computing K-Means with K = 2 (2 clusters)\n",
"centroids,_ = kmeans(jdata1,3)\n",
"# assign each sample to a cluster\n",
"idx,_ = vq(jdata1,centroids)\n",
"#vq(data,centroids)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's create a `DataFrame`,\n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cluster2=pd.DataFrame()\n",
"cluster2['X']=jdata1[:,0]\n",
"cluster2['Y']=jdata1[:,1]\n",
"cluster2['LABEL']=idx\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's plot the clusters and the centroid information."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEACAYAAAC9Gb03AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n0ZuZtZwnejOzlvNEb2bWcp7ozcxa7n+rSCRlxKgkawAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(jdata1[idx==0,0],jdata1[idx==0,1],'ob',markersize=4, alpha=1)\n",
"plt.plot(jdata1[idx==1,0],jdata1[idx==1,1],'or',markersize=4, alpha=1)\n",
"plt.plot(jdata1[idx==2,0],jdata1[idx==2,1],'og',markersize=4, alpha=1)\n",
"\n",
"plt.plot(centroids[:,0],centroids[:,1],'sk',markersize=6)\n",
"\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To compare the original data and the computed clusters using `subplot` in **matplotlib**,"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAlkAAAEKCAYAAAAhCkCDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMzPrwD8yAnzUcFnN3QAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#fig = plt.figure()\n",
"plt.figure(figsize=(10, 4))\n",
"\n",
"ax = plt.subplot(121)\n",
"ax.set_title(\"Original data or training data\")\n",
"ax.plot(data1[:,0],data1[:,1],'ob',markersize=4, alpha=1)\n",
"ax.plot(data2[:,0],data2[:,1],'or',markersize=4, alpha=1)\n",
"ax.plot(data3[:,0],data3[:,1],'og',markersize=4, alpha=1)\n",
"ax.grid()\n",
"\n",
"ax = plt.subplot(122)\n",
"ax.set_title(\"Clusters or test data\")\n",
"#ax.plot(jdata1[idx==0,0],jdata1[idx==0,1],'ob',markersize=4, alpha=1)\n",
"#ax.plot(jdata1[idx==1,0],jdata1[idx==1,1],'or',markersize=4, alpha=1)\n",
"#ax.plot(jdata1[idx==2,0],jdata1[idx==2,1],'og',markersize=4, alpha=1)\n",
"ax.plot(cluster2.X[cluster2.LABEL == 0],cluster2.Y[cluster2.LABEL == 0],'ob',markersize=4, alpha=1)\n",
"ax.plot(cluster2.X[cluster2.LABEL == 1],cluster2.Y[cluster2.LABEL == 1],'or',markersize=4, alpha=1)\n",
"ax.plot(cluster2.X[cluster2.LABEL == 2],cluster2.Y[cluster2.LABEL == 2],'og',markersize=4, alpha=1)\n",
"ax.grid()\n",
"\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To add reusability and automation to the plotting, let's add a loop when plotting the data. Let's use 10 centroids to illustrate the advantage of using a loop at plot time,"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAlkAAAJPCAYAAABPd8HBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.cm as cm\n",
"\n",
"plt.figure(figsize=(10,10))\n",
"\n",
"#number of centroids\n",
"cd=10\n",
"\n",
"centroids,_ = kmeans(jdata1,cd)\n",
"\n",
"idx,_ = vq(jdata1,centroids)\n",
"\n",
"#colors = cm.rainbow(np.linspace(0, 1, cd))\n",
"colors=iter(cm.rainbow(np.linspace(0,1,cd)))\n",
"\n",
"for tt in range(cd):\n",
" \n",
" c=next(colors)\n",
" \n",
" #plot(data_s1[idx== tt,0],data_s1[idx== tt,1],'o')\n",
" plt.plot(jdata1[idx== tt,0],jdata1[idx== tt,1],'o', c=c)\n",
" \n",
"\n",
"plt.plot(centroids[:,0],centroids[:,1],'sk',markersize=8)\n",
"\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we introduced the basic notions of clustering using **scipy**, let's compute the clusters for the data `shot_df` or Lebron James shot chart.\n",
"\n",
"The first thing to do is to create a `DataFrame` where we are going to put the information of **LOC_X** and **LOC_Y**."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"stmp=pd.DataFrame()\n",
"stmp['LOC_X']=shot_df.LOC_X\n",
"stmp['LOC_Y']=shot_df.LOC_Y\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To print a concise summary of the `DataFrame shot_df`,"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Int64Index: 1279 entries, 0 to 1278\n",
"Data columns (total 21 columns):\n",
"GRID_TYPE 1279 non-null object\n",
"GAME_ID 1279 non-null int64\n",
"GAME_EVENT_ID 1279 non-null int64\n",
"PLAYER_ID 1279 non-null int64\n",
"PLAYER_NAME 1279 non-null object\n",
"TEAM_ID 1279 non-null int64\n",
"TEAM_NAME 1279 non-null object\n",
"PERIOD 1279 non-null int64\n",
"MINUTES_REMAINING 1279 non-null int64\n",
"SECONDS_REMAINING 1279 non-null int64\n",
"EVENT_TYPE 1279 non-null object\n",
"ACTION_TYPE 1279 non-null object\n",
"SHOT_TYPE 1279 non-null object\n",
"SHOT_ZONE_BASIC 1279 non-null object\n",
"SHOT_ZONE_AREA 1279 non-null object\n",
"SHOT_ZONE_RANGE 1279 non-null object\n",
"SHOT_DISTANCE 1279 non-null int64\n",
"LOC_X 1279 non-null int64\n",
"LOC_Y 1279 non-null int64\n",
"SHOT_ATTEMPTED_FLAG 1279 non-null int64\n",
"SHOT_MADE_FLAG 1279 non-null int64\n",
"dtypes: int64(12), object(9)\n",
"memory usage: 219.8+ KB\n"
]
}
],
"source": [
"shot_df.info()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To print a concise summary of the `DataFrame stmp`,"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Int64Index: 1279 entries, 0 to 1278\n",
"Data columns (total 2 columns):\n",
"LOC_X 1279 non-null int64\n",
"LOC_Y 1279 non-null int64\n",
"dtypes: int64(2)\n",
"memory usage: 30.0 KB\n"
]
}
],
"source": [
"stmp.info()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To display the first 5 rows of `stmp`,"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" LOC_X | \n",
" LOC_Y | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 114 | \n",
" 148 | \n",
"
\n",
" \n",
" 1 | \n",
" -7 | \n",
" 0 | \n",
"
\n",
" \n",
" 2 | \n",
" -105 | \n",
" 63 | \n",
"
\n",
" \n",
" 3 | \n",
" 227 | \n",
" -16 | \n",
"
\n",
" \n",
" 4 | \n",
" 91 | \n",
" 246 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" LOC_X LOC_Y\n",
"0 114 148\n",
"1 -7 0\n",
"2 -105 63\n",
"3 227 -16\n",
"4 91 246"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stmp.head()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To use k-means with **scipy** we need to convert the **pandas** `DataFrame` into a **numpy** array."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"stmp1=stmp.as_matrix(columns=None)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To know the type of `stmp1`,"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"numpy.ndarray"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(stmp1)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"which have a data type,"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"dtype('int64')"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stmp1.dtype\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"However, k-means in **scipy** only supports `float` or `double` data type. To convert a `int64` to `float`, we proceed as follows,"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"dtype('float64')"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#type other than float or double not supported\n",
"data_s1=stmp1.astype(float)\n",
"data_s1.dtype\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To print the **numpy** array `data_s1`,"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 114. 148.]\n",
" [ -7. 0.]\n",
" [-105. 63.]\n",
" ..., \n",
" [-116. 168.]\n",
" [ -48. 61.]\n",
" [-199. 77.]]\n"
]
}
],
"source": [
"print(data_s1)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can compute the clusters (centroids and data labelling). \n",
"\n",
"Notice that we are using 6 centroids."
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#centroids,_ = kmeans(stmp1,10)\n",
"centroids,_ = kmeans(data_s1,6)\n",
"idx,_ = vq(data_s1,centroids)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To plot the positions of the centroids,"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAEACAYAAABRQBpkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAFMVJREFUeJzt3G+MZuV53/HvD2PkuE4zRW6Xv8ogGYRXSjS21XXVpNqh\nsfHGbQFLrbGlRIxNI1VIsS21rpdYLa2qYuxI6Taq6Bs7nY1VSFZ1g0hTMAtiaPoiIDdsQ7xsAIlp\nvSS7NIm3cdREAXP1xZzZfRgGdtl7ljPn3u9HGnHO/fyZ++dn/Vxz7uuck6pCknR+u2DsCUiSxmcx\nkCRZDCRJFgNJEhYDSRIWA0kSW1AMkqwm+Z0kTyZ5Yhi7OMnBJM8keSjJ3Mzzb0/ybJIjSa5v/f2S\npHZbcWRQwGJVva+qdg1je4GDVXUN8MiwT5KdwM3ATmAPcHcSj04kaWRb9UWcDfs3APuH7f3ATcP2\njcC9VfVSVa0CzwG7kCSNaquODB5O8q0kPzOM7aiq48P2cWDHsH0ZcHTmtUeBy7dgDpKkBhduwXv8\nWFX9QZK/ChxMcmT2waqqJG90zwvvhyFJI2suBlX1B8N//0+SX2Nt2ed4kkuq6liSS4EXh6e/AFw5\n8/IrhrFXOU3xkCS9jqrauGx/RpqWiZK8M8kPDtt/CbgeeAq4H7hleNotwH3D9v3AJ5JclOQq4Grg\nic3eu6q6/bnjjjtGn4PZzGe+/n5atB4Z7AB+Lcn6e/3HqnooybeAA0luBVaBjwNU1eEkB4DDwMvA\nbdWaYIJWV1fHnsI503M2MN/U9Z6vRVMxqKrngYVNxv8Y+NDrvOZO4M6W3ytJ2lqe4z+CpaWlsadw\nzvScDcw3db3na5HtuEqT5HxcPZKkJkmoMRrIOjsrKytjT+Gc6TkbmG/qes/XwmIgSXKZSJJ64TKR\nJKmJxWAEPa9b9pwNzDd1vedrYTGQJNkzkKRe2DOQJDWxGIyg53XLnrOB+aau93wtLAaSJHsGktQL\newaSpCYWgxH0vG7ZczYw39T1nq+FxUCSZM9Aknphz0CS1MRiMIKe1y17zgbmm7re87WwGEiS7BlI\nUi/sGUiSmlgMRtDzumXP2cB8U9d7vhYWA0mSPQNJ6oU9A0lSE4vBCHpet+w5G5hv6nrP18JiIEna\nmp5BkrcB3wKOVtXfS3Ix8KvADwOrwMer6sTw3NuBTwPfBz5TVQ9t8n72DCTpTdoOPYPPAoeB9W/w\nvcDBqroGeGTYJ8lO4GZgJ7AHuDuJRyeSNLLmL+IkVwAfBb4KrFekG4D9w/Z+4KZh+0bg3qp6qapW\ngeeAXa1zmJqe1y17zgbmm7re87XYir/K/w3weeCVmbEdVXV82D4O7Bi2LwOOzjzvKHD5FsxBktSg\nqRgk+bvAi1X1JKeOCl5lWPx/owbAedccWFxcHHsK50zP2cB8U9d7vhYXNr7+bwI3JPko8A7gLyf5\nOnA8ySVVdSzJpcCLw/NfAK6cef0Vw9hrLC0tMT8/D8Dc3BwLCwsnP8j1Qz333Xff/fN5f2VlheXl\nZYCT35dna8uuQE6yG/gnw9lEXwH+qKq+nGQvMFdVe4cG8j2s9QkuBx4G3rPx1KHezyZaWVk5+cH2\npudsYL6p6z1fy9lErUcGG61/g98FHEhyK8OppQBVdTjJAdbOPHoZuK3rb31JmgjvTSRJndgO1xlI\nkibMYjCC9QZQj3rOBuabut7ztbAYSJLsGUhSL+wZSJKaWAxG0PO6Zc/ZwHxT13u+FhYDSZI9A0nq\nhT0DSVITi8EIel637DkbmG/qes/XwmIgSbJnIEm9sGcgSWpiMRhBz+uWPWcD801d7/laWAwkSfYM\nJKkX9gwkSU0sBiPoed2y52xgvqnrPV8Li4EkyZ6BJPXCnoEkqYnFYAQ9r1v2nA3MN3W952thMZAk\n2TOQpF7YM5AkNbEYjKDndcues4H5pq73fC0sBpIkewaS1At7BpKkJk3FIMk7kjye5FCSw0m+NIxf\nnORgkmeSPJRkbuY1tyd5NsmRJNe3Bpiintcte84G5pu63vO1aCoGVfXnwHVVtQD8KHBdkh8H9gIH\nq+oa4JFhnyQ7gZuBncAe4O4kHp1I0si2rGeQ5J3AY8AS8A1gd1UdT3IJsFJV1ya5HXilqr48vOZB\n4F9U1W9teC97BpL0Jo3aM0hyQZJDwHHg0ar6NrCjqo4PTzkO7Bi2LwOOzrz8KHB56xwkSW0ubH2D\nqnoFWEjyQ8A3k1y34fFK8kZ/5m/62NLSEvPz8wDMzc2xsLDA4uIicGrdb6r7+/bt6yrP7P7smux2\nmI/5zNdzvpWVFZaXlwFOfl+erS09tTTJPwP+DPiHwGJVHUtyKWtHDNcm2QtQVXcNz38QuKOqHt/w\nPl0vE62srJz8YHvTczYw39T1nq9lmaipGCR5N/ByVZ1I8gPAN4F/CXwE+KOq+vJQAOaqau/QQL4H\n2MXa8tDDwHs2fvP3Xgwk6VxoKQaty0SXAvuHM4IuAL5eVY8keRI4kORWYBX4OEBVHU5yADgMvAzc\n5re+JI2v9dTSp6rq/VW1UFU/WlU/P4z/cVV9qKquqarrq+rEzGvurKr3VNW1VfXN1gBTNLtu2Zue\ns4H5pq73fC08x1+S5L2JJKkX3ptIktTEYjCCntcte84G5pu63vO1sBhIkuwZSFIv7BlIkppYDEbQ\n87plz9nAfFPXe74WFgNJkj0DSeqFPQNJUhOLwQh6XrfsORuYb+p6z9fCYiBJsmcgSb2wZyBJamIx\nGEHP65Y9ZwPzTV3v+VpYDCRJ9gwkqRf2DCRJTSwGI+h53bLnbGC+qes9XwuLgSTJnoEEsPS5JVZP\nrL5qbH5unuV9y6PMRzobLT2DC7d6MtIUrZ5Y5bGrHnv14PPjzEUag8tEI+h53bLnbGC+qes9XwuL\ngSTJnoEEsLi0+Jplot3P72ZleWWcCUlnwZ6B1Gh+bv41PYL5ufkxpjI5Nt/7YDEYwcrKCouLi2NP\n45yYarYz/eKaar4zdTb5ptR87/3za9HUM0hyZZJHk3w7ye8m+cwwfnGSg0meSfJQkrmZ19ye5Nkk\nR5Jc3xpAktSuqWeQ5BLgkqo6lORdwP8AbgI+BfxhVX0lyReAv1JVe5PsBO4B/jpwOfAwcE1VvbLh\nfe0ZSBNhv2X7GO3eRFV1rKoODdt/CjzN2pf8DcD+4Wn7WSsQADcC91bVS1W1CjwH7GqZgySp3Zad\nWppkHngf8Diwo6qODw8dB3YM25cBR2dedpS14nFe6flc556zgfk2Mz83z+7nd7/qZ7s233v//Fps\nSQN5WCL6BvDZqvpecuoopaoqyRut+Wz62NLSEvPz8wDMzc2xsLBwsvGz/oFOdf/QoUPbaj7uu9+y\nv3TT0qaPrxt7fj3vr6yssLy8DHDy+/JsNV9nkOTtwH8BHqiqfcPYEWCxqo4luRR4tKquTbIXoKru\nGp73IHBHVT2+4T3tGWwxT/+T+jfadQZZOwT4GnB4vRAM7gduAb48/Pe+mfF7kvwCa8tDVwNPtMxB\nZ2ZKp/9Jeuu19gx+DPgp4LokTw4/e4C7gA8neQb428M+VXUYOAAcBh4AbjsfDwE2Hkb3pOdsYL6p\n6z1fi6Yjg6r677x+QfnQ67zmTuDOlt8rSdpa3pvoPOG54FL/vDeRTst770h6Ix4ZjGCl4/uj9JwN\nzDd1vecb7QpkSVIfPDKQpE54ZCBJamIxGEHP5zr3nA3MN3W952thMZAk2TOQpF7YM5AkNbEYjKDn\ndcues4H5pq73fC0sBpIkewaS1At7BpKkJhaDEfS8btlzNjDf1PWer4XFQJJkz0CSemHPQJLUxGIw\ngp7XLXvOBuabut7ztbAYSJLsGUhSL+wZSJKaWAxG0PO6Zc/ZwHxT13u+FhYDSZI9A0nqhT0DSVIT\ni8EIel637DkbmG/qes/XwmIgSWrvGST5JeDvAC9W1Y8MYxcDvwr8MLAKfLyqTgyP3Q58Gvg+8Jmq\nemiT97RnIElv0tg9g/8A7Nkwthc4WFXXAI8M+yTZCdwM7Bxec3cSj04kaWTNX8RV9ZvAdzcM3wDs\nH7b3AzcN2zcC91bVS1W1CjwH7Gqdw9T0vG7ZczYw39T1nq/FufqrfEdVHR+2jwM7hu3LgKMzzzsK\nXH6O5iBJOkMXnutfUFWV5I0aAJs+trS0xPz8PABzc3MsLCywuLgInKruU91fH9su89nK/cXFxW01\nH/OZr+d8KysrLC8vA5z8vjxbW3LRWZJ54NdnGshHgMWqOpbkUuDRqro2yV6AqrpreN6DwB1V9fiG\n97OBLElv0tgN5M3cD9wybN8C3Dcz/okkFyW5CrgaeOIczWHbWq/sPeo5G5hv6nrP16J5mSjJvcBu\n4N1JvgP8c+Au4ECSWxlOLQWoqsNJDgCHgZeB2zwEkKTxeW8iSerEdlwmkiRNiMVgBD2vW/acDcw3\ndb3na2ExkCTZM5CkXtgzkCQ1sRiMoOd1y56zgfmmrvd8Lc757Sgk6UwtfW6J1ROrrxqbn5tned/y\nKPM5n9gzkLRtLC4t8thVj71qbPfzu1lZXhlnQhNjz0CS1MRiMIKe1y17zgbmm7re87WwGEiS7BlI\n2j5sILdp6RlYDCSpEzaQJ6bndcues4H5pq73fC0sBpIkl4l65vqrdH5pWSbyCuSOrZ5Yfc0FPDw/\nzlwkbW8uE42g53XLnrOB+aau93wtLAaSJHsGPfM+L9L5xZ6BNjU/N/+aHsH83PwYU5G0zXlkMIKV\nlRUWFxfHnsY50XM2MN/U9Z7Pi84kSU08MpCkTnhkIElqYjEYQc/nOveabelzSywuLbKwZ4HFpUUW\nlxZZ+tzS2NPacr1+fut6z9fCs4mkM/Cqq7mvGga9mlsdsWcgnQGv2dAUTK5nkGRPkiNJnk3yhTHm\nIEk65S0vBkneBvw7YA+wE/hkkve+1fMYU8/rlj1nA7pfGur98+s9X4sxega7gOeqahUgya8ANwJP\njzAX6YysX8194tgJ5pg7NSZ14i3vGST5+8BHqupnhv2fAj5YVT878xx7BpL0Jk2tZ+C3vCRtM2Ms\nE70AXDmzfyVwdOOTlpaWmJ+fB2Bubo6FhYWT9xRZX/eb6v6+ffu6yjO7P7smux3mYz7z9ZxvZWWF\n5eVlgJPfl2drjGWiC4HfA34C+H3gCeCTVfX0zHO6XiZa6fhmWT1nA/NNXe/5WpaJRrnOIMlPAvuA\ntwFfq6ovbXi862IgSefC5IrB6VgMJOnNm1oD+bw3u27Zm56zgfmmrvd8LSwGkiSXiSSpFy4TSZKa\nWAxG0PO6Zc/ZwHxT13u+FhYDSZI9A0nqhT0DSVITi8EIel637DkbmG/qes/XwmIgSbJnIEm9sGcg\nSWpiMRhBz+uWPWcD801d7/laWAwkSfYMJKkX9gwkSU0sBiPoed2y52xgvqnrPV8Li4EkyZ6BJPXC\nnoEkqYnFYAQ9r1v2nA3MN3W952thMZAk2TOQpF7YM5AkNbEYjKDndcues4H5pq73fC0sBpIkewaS\n1At7BpKkJmddDJL8gyTfTvL9JO/f8NjtSZ5NciTJ9TPjH0jy1PDYv22Z+JT1vG7ZczYw39T1nq9F\ny5HBU8DHgP82O5hkJ3AzsBPYA9ydZP2w5d8Dt1bV1cDVSfY0/P7JOnTo0NhTOGd6zgbmm7re87U4\n62JQVUeq6plNHroRuLeqXqqqVeA54INJLgV+sKqeGJ73y8BNZ/v7p+zEiRNjT+Gc6TkbmG/qes/X\n4lz0DC4Djs7sHwUu32T8hWFckjSyC9/owSQHgUs2eejnqurXz82U+re6ujr2FM6ZnrOB+aau93wt\nmk8tTfIo8I+r6reH/b0AVXXXsP8gcAfwv4BHq+q9w/gngd1V9Y82eU/PK5Wks3C2p5a+4ZHBmzD7\ny+8H7knyC6wtA10NPFFVleRPknwQeAL4aeAXN3uzsw0jSTo7LaeWfizJd4C/AfxGkgcAquowcAA4\nDDwA3DZzBdltwFeBZ4HnqurBlslLkrbGtrwCWZL01hr1CuQk/yrJ/0xyKMkjSa6ceWzyF64l+fkk\nTw8Z/3OSH5p5rId859WFh0n2DHmeTfKFsefzZiX5pSTHkzw1M3ZxkoNJnknyUJK5mcc2/Qy3qyRX\nJnl0+Df5u0k+M4x3kTHJO5I8PnxfHk7ypWF8a/JV1Wg/rF13sL79s8BXh+2dwCHg7cA8a9cqrB/F\nPAHsGrb/K7BnzAynyfdh4IJh+y7grs7yXQtcAzwKvH9mvIt8G7K+bcgxP+Q6BLx37Hm9yQx/C3gf\n8NTM2FeAfzpsf+E0/0YvGDvDafJdAiwM2+8Cfg94b2cZ3zn890Lgt4Af36p8ox4ZVNX3ZnbfBfzh\nsN3FhWtVdbCqXhl2HweuGLZ7yXc+XXi4i7U+12pVvQT8Cms5J6OqfhP47obhG4D9w/Z+Tn0em32G\nu96KeZ6tqjpWVYeG7T8FnmbtJJaeMv6/YfMi1v5A+S5blG/0G9Ul+ddJ/jewBHxpGO7xwrVPs/aX\nMPSZb1aP+S4HvjOzv55p6nZU1fFh+ziwY9h+vc9wEpLMs3YU9DgdZUxyQZJDrOV4tKq+zRbl26pT\nS1/X6S5cq6ovAl8crk/YB3zqXM9pK53JhXlJvgj8RVXd85ZObgt44eFJ3Z9pUVV1mmt8JvG/QZJ3\nAd8APltV3zt1a7TpZxxWGhaG/uM3k1y34fGzznfOi0FVffgMn3oPp/5yfgG4cuaxK1irai9waqll\nffyF1jm2OF2+JEvAR4GfmBnuJt/rmEy+N2Fjpit59V9dU3U8ySVVdWxYxntxGN/sM9z2n1WSt7NW\nCL5eVfcNw11lBKiq/5vkN4APsEX5xj6b6OqZ3RuBJ4ft+4FPJLkoyVWcunDtGPAnST6YtXL/08B9\nbFNZuyvr54Ebq+rPZx7qIt8GGy887C3ft1i70+58kotYuzPv/SPPaSvcD9wybN/Cqc9j089whPmd\nseHf1NeAw1W1b+ahLjImeff6mUJJfoC1E1SeZKvyjdwZ/0+s3Qr7EGvV/K/NPPZzrDU8jgAfmRn/\nwPCa54BfHHP+Z5DvWdZuw/Hk8HN3Z/k+xto6+p8Bx4AHesq3Sd6fZO0MleeA28eez1nM/17g94G/\nGD63TwEXAw8DzwAPAXOn+wy36w9rZ9a8MnyfrP9/bk8vGYEfAX57yPc7wOeH8S3J50VnkqTxzyaS\nJI3PYiBJshhIkiwGkiQsBpIkLAaSJCwGkiQsBpIk4P8DLPMjhjDZPu0AAAAASUVORK5CYII=\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(centroids[:,0],centroids[:,1],'sg',markersize=5)\n",
"\n",
"plt.xlim(-300,300)\n",
"plt.ylim(-100,500)\n",
"\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can plot the clusters. \n",
"\n",
"Have in mind that you can change the number of clusters with the variable `cd`, in this case we are using 6 clusters."
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAmIAAAJPCAYAAADfZLgOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.cm as cm\n",
"\n",
"plt.figure(figsize=(10,10))\n",
"\n",
"cd=6\n",
"\n",
"centroids,_ = kmeans(data_s1,cd)\n",
"\n",
"idx,_ = vq(data_s1,centroids)\n",
"\n",
"#colors = cm.rainbow(np.linspace(0, 1, cd))\n",
"colors=iter(cm.rainbow(np.linspace(0,1,cd)))\n",
"\n",
"for tt in range(cd):\n",
" \n",
" c=next(colors)\n",
" \n",
" #plot(data_s1[idx== tt,0],data_s1[idx== tt,1],'o')\n",
" plt.plot(data_s1[idx== tt,0],data_s1[idx== tt,1],'o', c=c)\n",
" \n",
"\n",
"plt.plot(centroids[:,0],centroids[:,1],'sk',markersize=8)\n",
"\n",
"plt.xlim(-300,300)\n",
"plt.ylim(-100,500)\n",
"\n",
"plt.grid()\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"At this point, we labelled the data using k-means clustering (unsupervised training). \n",
"\n",
"Notice that the algorithm did a pretty good job, as the zones labelled are very similar to those used in the nba to classify the shot zone area or `shot_df.SHOT_ZONE_AREA` in our dataset."
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"SHOT_ZONE_AREA\n",
"Back Court(BC) 3\n",
"Center(C) 670\n",
"Left Side Center(LC) 177\n",
"Left Side(L) 181\n",
"Right Side Center(RC) 149\n",
"Right Side(R) 99\n",
"Name: GRID_TYPE, dtype: int64"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shot_df.groupby('SHOT_ZONE_AREA').count().GRID_TYPE\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For completeness, let's plot the original labelled data."
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAmIAAAJPCAYAAADfZLgOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nqCtQAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.cm as cm\n",
"\n",
"plt.figure(figsize=(10,10))\n",
"\n",
"#To plot in the por man's way\n",
"\n",
"#plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == \"Back Court(BC)\"],shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == \"Back Court(BC)\"],'o',color='b')\n",
"#plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == \"Center(C)\"], shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == \"Center(C)\"],'o',color='g')\n",
"#plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == \"Left Side Center(LC)\"], shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == \"Left Side Center(LC)\"],'o',color='c')\n",
"#plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == \"Left Side(L)\"], shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == \"Left Side(L)\"],'o',color='m')\n",
"#plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == \"Right Side Center(RC)\"], shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == \"Right Side Center(RC)\"],'o',color='k')\n",
"#plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == \"Right Side(R)\"], shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == \"Right Side(R)\"],'o',color='y')\n",
"\n",
"#plt.scatter(missed.LOC_X, missed.LOC_Y, color='red',label='missed',s=20,marker='o',alpha=0.5)\n",
"\n",
"\n",
"#To plot in the lazy way (smart)\n",
"\n",
"li = ['Back Court(BC)','Center(C)','Left Side Center(LC)','Left Side(L)','Right Side Center(RC)','Right Side(R)']\n",
"\n",
"sets=6\n",
"\n",
"colors=iter(cm.rainbow(np.linspace(0,1,sets)))\n",
"\n",
"#for s in li:\n",
"for s,c in zip(li,colors):\n",
" \n",
" plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == s],shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == s],'o',color=c)\n",
"\n",
"#plt.legend()\n",
"\n",
"plt.xlim(-300,300)\n",
"plt.ylim(-100,500)\n",
"\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"and let's use subplots to compare both figure,"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA1EAAAGOCAYAAAB2col5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwU6UJEmSJI3wP6BnzRLBTG8CAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#fig = plt.figure()\n",
"plt.figure(figsize=(14, 6))\n",
"\n",
"\n",
"\n",
"plt.subplot(121)\n",
"\n",
"cd=6\n",
"centroids,_ = kmeans(data_s1,cd)\n",
"idx,_ = vq(data_s1,centroids)\n",
"\n",
"colors=iter(cm.rainbow(np.linspace(0,1,cd)))\n",
"\n",
"for tt in range(cd):\n",
" c=next(colors)\n",
" plt.plot(data_s1[idx== tt,0],data_s1[idx== tt,1],'o', c=c)\n",
" \n",
"#plt.plot(centroids[:,0],centroids[:,1],'sk',markersize=5)\n",
"\n",
"plt.xlim(-300,300)\n",
"plt.ylim(-100,500)\n",
"\n",
"plt.xlabel('LOC_X')\n",
"plt.ylabel('LOC_Y')\n",
"\n",
"plt.grid()\n",
"plt.title('Cluster data',fontsize=18)\n",
"\n",
"\n",
"\n",
"#second plot\n",
"plt.subplot(122)\n",
"\n",
"li = ['Back Court(BC)','Center(C)','Left Side Center(LC)','Left Side(L)','Right Side Center(RC)','Right Side(R)']\n",
"\n",
"sets=6\n",
"colors=iter(cm.rainbow(np.linspace(0,1,sets)))\n",
"\n",
"for s,c in zip(li,colors):\n",
" plt.plot(shot_df.LOC_X[shot_df.SHOT_ZONE_AREA == s],shot_df.LOC_Y[shot_df.SHOT_ZONE_AREA == s],'o',color=c)\n",
"\n",
"plt.xlim(-300,300)\n",
"plt.ylim(-100,500)\n",
"\n",
"plt.xlabel('LOC_X')\n",
"#plt.ylabel('LOC_Y')\n",
"\n",
"plt.grid()\n",
"plt.title('Original data',fontsize=18)\n",
"#plt.subplot(122).set_title(\"ax3\")\n",
"\n",
"plt.show()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"### The main take away of this tutorial, is that if your data is not labelled you can use clustering techniques to find hidden structures.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Finally, I hope you enjoyed this series of tutorials on sport analytics, data scraping, data wrangling, data analysis, exploratory data analysis, advaced plotting and clustering."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# References\n",
"\n",
"[1] https://en.wikipedia.org/wiki/K-means_clustering\n",
"\n",
"[2] http://www.scipy.org/\n",
" \n",
"[3] http://matplotlib.org/\n",
"\n",
"[4] http://stanford.edu/~mwaskom/software/seaborn/\n",
"\n",
"[5] http://pandas.pydata.org/"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#import sys\n",
"#print('Python version:', sys.version_info)\n",
"\n",
"#import IPython\n",
"#print('IPython version:', IPython.__version__)\n",
"\n",
"#print('Requests version', requests.__version__)\n",
"#print('Pandas version:', pd.__version__)\n",
"#print('json version:', json.__version__)\n",
"\n",
"#import matplotlib\n",
"#print('matplotlib version:', matplotlib.__version__)\n",
"\n",
"#print('seaborn version:', sns.__version__)\n",
"\n",
"#import scipy\n",
"#print('scipy version:', scipy.__version__)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 0
}