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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img src=\"http://imgur.com/1ZcRyrc.png\" style=\"float: left; margin: 20px; height: 55px\">\n",
"\n",
"## Homework: Intro to Pandas\n",
"\n",
"_Author: Kevin Coyle (L.A.)_\n",
"\n",
"---\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Welcome!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Pandas: Intro Practice Problems\n",
"\n",
"In this homework, you're going to write code for a few problems. \n",
"\n",
"You'll be practicing these programming concepts we've covered in class:\n",
"* Reading data sets into Pandas.\n",
"* Filtering, manipulating, and sorting data sets.\n",
"* Basic exploratory data analysis with Pandas."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #1. Import Pandas with an alias of `pd`."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #2. Read in the NBA players `csv` into a variable called `nba_df`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is a data set of NBA players from 2015. The filename is `NBA_players_2015.csv`."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"nba_df = pd.read_csv(\"NBA_players_2015.csv\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #3. Look at the first five rows of the data set."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>season_end</th>\n",
" <th>player</th>\n",
" <th>pos</th>\n",
" <th>age</th>\n",
" <th>bref_team_id</th>\n",
" <th>g</th>\n",
" <th>gs</th>\n",
" <th>mp</th>\n",
" <th>fg</th>\n",
" <th>fga</th>\n",
" <th>...</th>\n",
" <th>TOV%</th>\n",
" <th>USG%</th>\n",
" <th>OWS</th>\n",
" <th>DWS</th>\n",
" <th>WS</th>\n",
" <th>WS/48</th>\n",
" <th>OBPM</th>\n",
" <th>DBPM</th>\n",
" <th>BPM</th>\n",
" <th>VORP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015</td>\n",
" <td>Quincy Acy</td>\n",
" <td>F</td>\n",
" <td>24</td>\n",
" <td>NYK</td>\n",
" <td>52</td>\n",
" <td>21</td>\n",
" <td>19.2</td>\n",
" <td>2.2</td>\n",
" <td>4.6</td>\n",
" <td>...</td>\n",
" <td>15.1</td>\n",
" <td>14.7</td>\n",
" <td>0.6</td>\n",
" <td>0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.050</td>\n",
" <td>-2.6</td>\n",
" <td>-0.7</td>\n",
" <td>-3.4</td>\n",
" <td>-0.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2015</td>\n",
" <td>Jordan Adams</td>\n",
" <td>G</td>\n",
" <td>20</td>\n",
" <td>MEM</td>\n",
" <td>18</td>\n",
" <td>0</td>\n",
" <td>7.3</td>\n",
" <td>1.0</td>\n",
" <td>2.1</td>\n",
" <td>...</td>\n",
" <td>15.9</td>\n",
" <td>17.7</td>\n",
" <td>0.0</td>\n",
" <td>0.2</td>\n",
" <td>0.2</td>\n",
" <td>0.076</td>\n",
" <td>-2.3</td>\n",
" <td>1.8</td>\n",
" <td>-0.5</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2015</td>\n",
" <td>Steven Adams</td>\n",
" <td>C</td>\n",
" <td>21</td>\n",
" <td>OKC</td>\n",
" <td>51</td>\n",
" <td>50</td>\n",
" <td>24.2</td>\n",
" <td>3.0</td>\n",
" <td>5.5</td>\n",
" <td>...</td>\n",
" <td>19.2</td>\n",
" <td>14.8</td>\n",
" <td>1.0</td>\n",
" <td>1.8</td>\n",
" <td>2.8</td>\n",
" <td>0.109</td>\n",
" <td>-2.0</td>\n",
" <td>2.0</td>\n",
" <td>-0.1</td>\n",
" <td>0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2015</td>\n",
" <td>Jeff Adrien</td>\n",
" <td>F</td>\n",
" <td>28</td>\n",
" <td>MIN</td>\n",
" <td>17</td>\n",
" <td>0</td>\n",
" <td>12.6</td>\n",
" <td>1.1</td>\n",
" <td>2.6</td>\n",
" <td>...</td>\n",
" <td>12.9</td>\n",
" <td>14.1</td>\n",
" <td>0.2</td>\n",
" <td>0.2</td>\n",
" <td>0.4</td>\n",
" <td>0.093</td>\n",
" <td>-2.6</td>\n",
" <td>0.8</td>\n",
" <td>-1.8</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015</td>\n",
" <td>Arron Afflalo</td>\n",
" <td>G</td>\n",
" <td>29</td>\n",
" <td>TOT</td>\n",
" <td>60</td>\n",
" <td>54</td>\n",
" <td>32.5</td>\n",
" <td>5.0</td>\n",
" <td>11.8</td>\n",
" <td>...</td>\n",
" <td>10.9</td>\n",
" <td>19.6</td>\n",
" <td>1.4</td>\n",
" <td>0.7</td>\n",
" <td>2.1</td>\n",
" <td>0.051</td>\n",
" <td>-0.2</td>\n",
" <td>-1.4</td>\n",
" <td>-1.6</td>\n",
" <td>0.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 49 columns</p>\n",
"</div>"
],
"text/plain": [
" season_end player pos age bref_team_id g gs mp fg fga \\\n",
"0 2015 Quincy Acy F 24 NYK 52 21 19.2 2.2 4.6 \n",
"1 2015 Jordan Adams G 20 MEM 18 0 7.3 1.0 2.1 \n",
"2 2015 Steven Adams C 21 OKC 51 50 24.2 3.0 5.5 \n",
"3 2015 Jeff Adrien F 28 MIN 17 0 12.6 1.1 2.6 \n",
"4 2015 Arron Afflalo G 29 TOT 60 54 32.5 5.0 11.8 \n",
"\n",
" ... TOV% USG% OWS DWS WS WS/48 OBPM DBPM BPM VORP \n",
"0 ... 15.1 14.7 0.6 0.5 1.0 0.050 -2.6 -0.7 -3.4 -0.3 \n",
"1 ... 15.9 17.7 0.0 0.2 0.2 0.076 -2.3 1.8 -0.5 0.0 \n",
"2 ... 19.2 14.8 1.0 1.8 2.8 0.109 -2.0 2.0 -0.1 0.6 \n",
"3 ... 12.9 14.1 0.2 0.2 0.4 0.093 -2.6 0.8 -1.8 0.0 \n",
"4 ... 10.9 19.6 1.4 0.7 2.1 0.051 -0.2 -1.4 -1.6 0.2 \n",
"\n",
"[5 rows x 49 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nba_df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #4. Check out the shape of the data set."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(478, 49)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nba_df.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #5. Run some summary stats on the data set with the `describe()` function."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>season_end</th>\n",
" <th>age</th>\n",
" <th>g</th>\n",
" <th>gs</th>\n",
" <th>mp</th>\n",
" <th>fg</th>\n",
" <th>fga</th>\n",
" <th>fg_</th>\n",
" <th>x3p</th>\n",
" <th>x3pa</th>\n",
" <th>...</th>\n",
" <th>TOV%</th>\n",
" <th>USG%</th>\n",
" <th>OWS</th>\n",
" <th>DWS</th>\n",
" <th>WS</th>\n",
" <th>WS/48</th>\n",
" <th>OBPM</th>\n",
" <th>DBPM</th>\n",
" <th>BPM</th>\n",
" <th>VORP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>478.0</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>...</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" <td>478.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>2015.0</td>\n",
" <td>26.573222</td>\n",
" <td>42.104603</td>\n",
" <td>19.874477</td>\n",
" <td>20.045607</td>\n",
" <td>3.018201</td>\n",
" <td>6.847699</td>\n",
" <td>0.429230</td>\n",
" <td>0.630544</td>\n",
" <td>1.855649</td>\n",
" <td>...</td>\n",
" <td>13.424268</td>\n",
" <td>18.915272</td>\n",
" <td>1.055858</td>\n",
" <td>0.971339</td>\n",
" <td>2.027197</td>\n",
" <td>0.073575</td>\n",
" <td>-1.396862</td>\n",
" <td>-0.495816</td>\n",
" <td>-1.892678</td>\n",
" <td>0.485983</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.0</td>\n",
" <td>4.219585</td>\n",
" <td>18.950602</td>\n",
" <td>22.170034</td>\n",
" <td>9.313441</td>\n",
" <td>2.052790</td>\n",
" <td>4.386828</td>\n",
" <td>0.111007</td>\n",
" <td>0.665808</td>\n",
" <td>1.790564</td>\n",
" <td>...</td>\n",
" <td>6.559989</td>\n",
" <td>5.493491</td>\n",
" <td>1.589667</td>\n",
" <td>0.876932</td>\n",
" <td>2.243138</td>\n",
" <td>0.133530</td>\n",
" <td>4.251216</td>\n",
" <td>2.299572</td>\n",
" <td>5.116001</td>\n",
" <td>1.013097</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>2015.0</td>\n",
" <td>19.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.700000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-2.100000</td>\n",
" <td>-0.100000</td>\n",
" <td>-0.800000</td>\n",
" <td>-1.059000</td>\n",
" <td>-36.800000</td>\n",
" <td>-13.500000</td>\n",
" <td>-50.300000</td>\n",
" <td>-1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>2015.0</td>\n",
" <td>23.000000</td>\n",
" <td>27.000000</td>\n",
" <td>0.000000</td>\n",
" <td>12.600000</td>\n",
" <td>1.425000</td>\n",
" <td>3.400000</td>\n",
" <td>0.391000</td>\n",
" <td>0.000000</td>\n",
" <td>0.100000</td>\n",
" <td>...</td>\n",
" <td>10.000000</td>\n",
" <td>14.800000</td>\n",
" <td>0.000000</td>\n",
" <td>0.200000</td>\n",
" <td>0.300000</td>\n",
" <td>0.040250</td>\n",
" <td>-2.800000</td>\n",
" <td>-1.600000</td>\n",
" <td>-3.300000</td>\n",
" <td>-0.100000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>2015.0</td>\n",
" <td>26.000000</td>\n",
" <td>47.000000</td>\n",
" <td>10.500000</td>\n",
" <td>19.850000</td>\n",
" <td>2.700000</td>\n",
" <td>5.900000</td>\n",
" <td>0.432000</td>\n",
" <td>0.450000</td>\n",
" <td>1.400000</td>\n",
" <td>...</td>\n",
" <td>12.900000</td>\n",
" <td>18.400000</td>\n",
" <td>0.600000</td>\n",
" <td>0.800000</td>\n",
" <td>1.400000</td>\n",
" <td>0.082500</td>\n",
" <td>-1.000000</td>\n",
" <td>-0.500000</td>\n",
" <td>-1.300000</td>\n",
" <td>0.100000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2015.0</td>\n",
" <td>29.000000</td>\n",
" <td>59.000000</td>\n",
" <td>39.000000</td>\n",
" <td>28.175000</td>\n",
" <td>4.275000</td>\n",
" <td>9.600000</td>\n",
" <td>0.481750</td>\n",
" <td>1.000000</td>\n",
" <td>3.075000</td>\n",
" <td>...</td>\n",
" <td>15.900000</td>\n",
" <td>21.900000</td>\n",
" <td>1.600000</td>\n",
" <td>1.500000</td>\n",
" <td>3.000000</td>\n",
" <td>0.123000</td>\n",
" <td>0.500000</td>\n",
" <td>0.875000</td>\n",
" <td>0.500000</td>\n",
" <td>0.700000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>2015.0</td>\n",
" <td>38.000000</td>\n",
" <td>66.000000</td>\n",
" <td>66.000000</td>\n",
" <td>38.900000</td>\n",
" <td>9.500000</td>\n",
" <td>21.400000</td>\n",
" <td>1.000000</td>\n",
" <td>3.400000</td>\n",
" <td>8.000000</td>\n",
" <td>...</td>\n",
" <td>100.000000</td>\n",
" <td>45.900000</td>\n",
" <td>9.500000</td>\n",
" <td>4.300000</td>\n",
" <td>13.000000</td>\n",
" <td>1.489000</td>\n",
" <td>28.300000</td>\n",
" <td>6.500000</td>\n",
" <td>15.100000</td>\n",
" <td>6.200000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>8 rows × 46 columns</p>\n",
"</div>"
],
"text/plain": [
" season_end age g gs mp fg \\\n",
"count 478.0 478.000000 478.000000 478.000000 478.000000 478.000000 \n",
"mean 2015.0 26.573222 42.104603 19.874477 20.045607 3.018201 \n",
"std 0.0 4.219585 18.950602 22.170034 9.313441 2.052790 \n",
"min 2015.0 19.000000 1.000000 0.000000 0.700000 0.000000 \n",
"25% 2015.0 23.000000 27.000000 0.000000 12.600000 1.425000 \n",
"50% 2015.0 26.000000 47.000000 10.500000 19.850000 2.700000 \n",
"75% 2015.0 29.000000 59.000000 39.000000 28.175000 4.275000 \n",
"max 2015.0 38.000000 66.000000 66.000000 38.900000 9.500000 \n",
"\n",
" fga fg_ x3p x3pa ... TOV% \\\n",
"count 478.000000 478.000000 478.000000 478.000000 ... 478.000000 \n",
"mean 6.847699 0.429230 0.630544 1.855649 ... 13.424268 \n",
"std 4.386828 0.111007 0.665808 1.790564 ... 6.559989 \n",
"min 0.000000 0.000000 0.000000 0.000000 ... 0.000000 \n",
"25% 3.400000 0.391000 0.000000 0.100000 ... 10.000000 \n",
"50% 5.900000 0.432000 0.450000 1.400000 ... 12.900000 \n",
"75% 9.600000 0.481750 1.000000 3.075000 ... 15.900000 \n",
"max 21.400000 1.000000 3.400000 8.000000 ... 100.000000 \n",
"\n",
" USG% OWS DWS WS WS/48 OBPM \\\n",
"count 478.000000 478.000000 478.000000 478.000000 478.000000 478.000000 \n",
"mean 18.915272 1.055858 0.971339 2.027197 0.073575 -1.396862 \n",
"std 5.493491 1.589667 0.876932 2.243138 0.133530 4.251216 \n",
"min 0.000000 -2.100000 -0.100000 -0.800000 -1.059000 -36.800000 \n",
"25% 14.800000 0.000000 0.200000 0.300000 0.040250 -2.800000 \n",
"50% 18.400000 0.600000 0.800000 1.400000 0.082500 -1.000000 \n",
"75% 21.900000 1.600000 1.500000 3.000000 0.123000 0.500000 \n",
"max 45.900000 9.500000 4.300000 13.000000 1.489000 28.300000 \n",
"\n",
" DBPM BPM VORP \n",
"count 478.000000 478.000000 478.000000 \n",
"mean -0.495816 -1.892678 0.485983 \n",
"std 2.299572 5.116001 1.013097 \n",
"min -13.500000 -50.300000 -1.000000 \n",
"25% -1.600000 -3.300000 -0.100000 \n",
"50% -0.500000 -1.300000 0.100000 \n",
"75% 0.875000 0.500000 0.700000 \n",
"max 6.500000 15.100000 6.200000 \n",
"\n",
"[8 rows x 46 columns]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nba_df.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #6. Sort the data set in on the `players` column in alphabetical order."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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" <th>g</th>\n",
" <th>gs</th>\n",
" <th>mp</th>\n",
" <th>fg</th>\n",
" <th>fga</th>\n",
" <th>...</th>\n",
" <th>TOV%</th>\n",
" <th>USG%</th>\n",
" <th>OWS</th>\n",
" <th>DWS</th>\n",
" <th>WS</th>\n",
" <th>WS/48</th>\n",
" <th>OBPM</th>\n",
" <th>DBPM</th>\n",
" <th>BPM</th>\n",
" <th>VORP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>359</th>\n",
" <td>2015</td>\n",
" <td>A.J. Price</td>\n",
" <td>G</td>\n",
" <td>28</td>\n",
" <td>TOT</td>\n",
" <td>21</td>\n",
" <td>0</td>\n",
" <td>13.3</td>\n",
" <td>2.3</td>\n",
" <td>5.9</td>\n",
" <td>...</td>\n",
" <td>8.9</td>\n",
" <td>23.6</td>\n",
" <td>0.2</td>\n",
" <td>0.2</td>\n",
" <td>0.4</td>\n",
" <td>0.072</td>\n",
" <td>0.5</td>\n",
" <td>-2.8</td>\n",
" <td>-2.4</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60</th>\n",
" <td>2015</td>\n",
" <td>Aaron Brooks</td>\n",
" <td>G</td>\n",
" <td>30</td>\n",
" <td>CHI</td>\n",
" <td>65</td>\n",
" <td>9</td>\n",
" <td>21.0</td>\n",
" <td>3.9</td>\n",
" <td>9.3</td>\n",
" <td>...</td>\n",
" <td>15.5</td>\n",
" <td>25.7</td>\n",
" <td>1.1</td>\n",
" <td>1.0</td>\n",
" <td>2.1</td>\n",
" <td>0.073</td>\n",
" <td>0.7</td>\n",
" <td>-2.8</td>\n",
" <td>-2.1</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166</th>\n",
" <td>2015</td>\n",
" <td>Aaron Gordon</td>\n",
" <td>F</td>\n",
" <td>19</td>\n",
" <td>ORL</td>\n",
" <td>30</td>\n",
" <td>6</td>\n",
" <td>15.2</td>\n",
" <td>1.9</td>\n",
" <td>3.8</td>\n",
" <td>...</td>\n",
" <td>17.0</td>\n",
" <td>15.9</td>\n",
" <td>0.3</td>\n",
" <td>0.3</td>\n",
" <td>0.6</td>\n",
" <td>0.066</td>\n",
" <td>-2.5</td>\n",
" <td>-0.5</td>\n",
" <td>-3.1</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>348</th>\n",
" <td>2015</td>\n",
" <td>Adreian Payne</td>\n",
" <td>F</td>\n",
" <td>23</td>\n",
" <td>TOT</td>\n",
" <td>12</td>\n",
" <td>3</td>\n",
" <td>19.7</td>\n",
" <td>2.3</td>\n",
" <td>6.1</td>\n",
" <td>...</td>\n",
" <td>13.6</td>\n",
" <td>17.7</td>\n",
" <td>-0.3</td>\n",
" <td>0.1</td>\n",
" <td>-0.1</td>\n",
" <td>-0.024</td>\n",
" <td>-5.8</td>\n",
" <td>-2.5</td>\n",
" <td>-8.3</td>\n",
" <td>-0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>212</th>\n",
" <td>2015</td>\n",
" <td>Al Horford</td>\n",
" <td>C</td>\n",
" <td>28</td>\n",
" <td>ATL</td>\n",
" <td>60</td>\n",
" <td>60</td>\n",
" <td>30.8</td>\n",
" <td>6.8</td>\n",
" <td>12.6</td>\n",
" <td>...</td>\n",
" <td>9.1</td>\n",
" <td>22.1</td>\n",
" <td>4.6</td>\n",
" <td>3.0</td>\n",
" <td>7.5</td>\n",
" <td>0.195</td>\n",
" <td>1.7</td>\n",
" <td>2.7</td>\n",
" <td>4.5</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>225</th>\n",
" <td>2015</td>\n",
" <td>Al Jefferson</td>\n",
" <td>C</td>\n",
" <td>30</td>\n",
" <td>CHO</td>\n",
" <td>53</td>\n",
" <td>49</td>\n",
" <td>31.4</td>\n",
" <td>7.8</td>\n",
" <td>16.0</td>\n",
" <td>...</td>\n",
" <td>5.4</td>\n",
" <td>26.4</td>\n",
" <td>1.5</td>\n",
" <td>2.9</td>\n",
" <td>4.5</td>\n",
" <td>0.129</td>\n",
" <td>-0.9</td>\n",
" <td>1.7</td>\n",
" <td>0.8</td>\n",
" <td>1.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2015</td>\n",
" <td>Al-Farouq Aminu</td>\n",
" <td>F</td>\n",
" <td>24</td>\n",
" <td>DAL</td>\n",
" <td>60</td>\n",
" <td>3</td>\n",
" <td>17.0</td>\n",
" <td>2.0</td>\n",
" <td>4.7</td>\n",
" <td>...</td>\n",
" <td>11.8</td>\n",
" <td>15.7</td>\n",
" <td>0.9</td>\n",
" <td>1.7</td>\n",
" <td>2.6</td>\n",
" <td>0.124</td>\n",
" <td>-0.6</td>\n",
" <td>3.0</td>\n",
" <td>2.3</td>\n",
" <td>1.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2015</td>\n",
" <td>Alan Anderson</td>\n",
" <td>G</td>\n",
" <td>32</td>\n",
" <td>BRK</td>\n",
" <td>62</td>\n",
" <td>19</td>\n",
" <td>23.8</td>\n",
" <td>2.5</td>\n",
" <td>5.7</td>\n",
" <td>...</td>\n",
" <td>11.8</td>\n",
" <td>13.7</td>\n",
" <td>1.3</td>\n",
" <td>0.9</td>\n",
" <td>2.1</td>\n",
" <td>0.070</td>\n",
" <td>-0.2</td>\n",
" <td>-0.3</td>\n",
" <td>-0.5</td>\n",
" <td>0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>68</th>\n",
" <td>2015</td>\n",
" <td>Alec Burks</td>\n",
" <td>G</td>\n",
" <td>23</td>\n",
" <td>UTA</td>\n",
" <td>27</td>\n",
" <td>27</td>\n",
" <td>33.3</td>\n",
" <td>4.5</td>\n",
" <td>11.1</td>\n",
" <td>...</td>\n",
" <td>12.7</td>\n",
" <td>20.9</td>\n",
" <td>1.1</td>\n",
" <td>0.5</td>\n",
" <td>1.5</td>\n",
" <td>0.082</td>\n",
" <td>-0.3</td>\n",
" <td>-1.3</td>\n",
" <td>-1.6</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>252</th>\n",
" <td>2015</td>\n",
" <td>Alex Kirk</td>\n",
" <td>C</td>\n",
" <td>23</td>\n",
" <td>CLE</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>2.8</td>\n",
" <td>0.2</td>\n",
" <td>0.8</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>15.7</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.060</td>\n",
" <td>-3.0</td>\n",
" <td>-4.3</td>\n",
" <td>-7.3</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>267</th>\n",
" <td>2015</td>\n",
" <td>Alex Len</td>\n",
" <td>C</td>\n",
" <td>21</td>\n",
" <td>PHO</td>\n",
" <td>61</td>\n",
" <td>36</td>\n",
" <td>21.7</td>\n",
" <td>2.7</td>\n",
" <td>5.0</td>\n",
" <td>...</td>\n",
" <td>15.4</td>\n",
" <td>13.7</td>\n",
" <td>1.5</td>\n",
" <td>1.8</td>\n",
" <td>3.3</td>\n",
" <td>0.119</td>\n",
" <td>-2.8</td>\n",
" <td>2.0</td>\n",
" <td>-0.8</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>394</th>\n",
" <td>2015</td>\n",
" <td>Alexey Shved</td>\n",
" <td>G</td>\n",
" <td>26</td>\n",
" <td>TOT</td>\n",
" <td>35</td>\n",
" <td>2</td>\n",
" <td>15.7</td>\n",
" <td>2.7</td>\n",
" <td>6.8</td>\n",
" <td>...</td>\n",
" <td>10.1</td>\n",
" <td>25.8</td>\n",
" <td>1.4</td>\n",
" <td>0.3</td>\n",
" <td>1.7</td>\n",
" <td>0.149</td>\n",
" <td>3.1</td>\n",
" <td>-3.3</td>\n",
" <td>-0.3</td>\n",
" <td>0.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2015</td>\n",
" <td>Alexis Ajinca</td>\n",
" <td>C</td>\n",
" <td>26</td>\n",
" <td>NOP</td>\n",
" <td>51</td>\n",
" <td>6</td>\n",
" <td>14.0</td>\n",
" <td>2.8</td>\n",
" <td>4.8</td>\n",
" <td>...</td>\n",
" <td>15.3</td>\n",
" <td>20.8</td>\n",
" <td>1.8</td>\n",
" <td>0.9</td>\n",
" <td>2.7</td>\n",
" <td>0.181</td>\n",
" <td>0.4</td>\n",
" <td>0.2</td>\n",
" <td>0.7</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>99</th>\n",
" <td>2015</td>\n",
" <td>Allen Crabbe</td>\n",
" <td>G</td>\n",
" <td>22</td>\n",
" <td>POR</td>\n",
" <td>38</td>\n",
" <td>7</td>\n",
" <td>12.4</td>\n",
" <td>1.1</td>\n",
" <td>2.5</td>\n",
" <td>...</td>\n",
" <td>9.3</td>\n",
" <td>10.2</td>\n",
" <td>0.5</td>\n",
" <td>0.6</td>\n",
" <td>1.1</td>\n",
" <td>0.109</td>\n",
" <td>-0.9</td>\n",
" <td>1.4</td>\n",
" <td>0.4</td>\n",
" <td>0.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160</th>\n",
" <td>2015</td>\n",
" <td>Alonzo Gee</td>\n",
" <td>F</td>\n",
" <td>27</td>\n",
" <td>TOT</td>\n",
" <td>43</td>\n",
" <td>0</td>\n",
" <td>12.4</td>\n",
" <td>1.6</td>\n",
" <td>3.3</td>\n",
" <td>...</td>\n",
" <td>14.0</td>\n",
" <td>16.3</td>\n",
" <td>0.6</td>\n",
" <td>0.5</td>\n",
" <td>1.1</td>\n",
" <td>0.100</td>\n",
" <td>-0.8</td>\n",
" <td>0.5</td>\n",
" <td>-0.3</td>\n",
" <td>0.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>413</th>\n",
" <td>2015</td>\n",
" <td>Amar'e Stoudemire</td>\n",
" <td>F</td>\n",
" <td>32</td>\n",
" <td>TOT</td>\n",
" <td>44</td>\n",
" <td>14</td>\n",
" <td>22.8</td>\n",
" <td>4.7</td>\n",
" <td>8.4</td>\n",
" <td>...</td>\n",
" <td>14.0</td>\n",
" <td>23.2</td>\n",
" <td>2.0</td>\n",
" <td>0.8</td>\n",
" <td>2.8</td>\n",
" <td>0.134</td>\n",
" <td>-0.2</td>\n",
" <td>-0.7</td>\n",
" <td>-0.9</td>\n",
" <td>0.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>232</th>\n",
" <td>2015</td>\n",
" <td>Amir Johnson</td>\n",
" <td>F</td>\n",
" <td>27</td>\n",
" <td>TOR</td>\n",
" <td>61</td>\n",
" <td>60</td>\n",
" <td>26.5</td>\n",
" <td>4.0</td>\n",
" <td>7.0</td>\n",
" <td>...</td>\n",
" <td>15.9</td>\n",
" <td>15.6</td>\n",
" <td>2.8</td>\n",
" <td>1.3</td>\n",
" <td>4.1</td>\n",
" <td>0.123</td>\n",
" <td>0.9</td>\n",
" <td>1.1</td>\n",
" <td>2.0</td>\n",
" <td>1.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>439</th>\n",
" <td>2015</td>\n",
" <td>Anderson Varejao</td>\n",
" <td>C</td>\n",
" <td>32</td>\n",
" <td>CLE</td>\n",
" <td>26</td>\n",
" <td>26</td>\n",
" <td>24.5</td>\n",
" <td>4.3</td>\n",
" <td>7.7</td>\n",
" <td>...</td>\n",
" <td>13.7</td>\n",
" <td>18.0</td>\n",
" <td>1.2</td>\n",
" <td>0.7</td>\n",
" <td>1.9</td>\n",
" <td>0.145</td>\n",
" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>112</th>\n",
" <td>2015</td>\n",
" <td>Andre Dawkins</td>\n",
" <td>G</td>\n",
" <td>23</td>\n",
" <td>MIA</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>5.5</td>\n",
" <td>0.3</td>\n",
" <td>1.5</td>\n",
" <td>...</td>\n",
" <td>14.3</td>\n",
" <td>15.1</td>\n",
" <td>-0.1</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>-0.177</td>\n",
" <td>-7.5</td>\n",
" <td>-4.1</td>\n",
" <td>-11.6</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>127</th>\n",
" <td>2015</td>\n",
" <td>Andre Drummond</td>\n",
" <td>C</td>\n",
" <td>21</td>\n",
" <td>DET</td>\n",
" <td>63</td>\n",
" <td>63</td>\n",
" <td>30.0</td>\n",
" <td>5.7</td>\n",
" <td>11.2</td>\n",
" <td>...</td>\n",
" <td>10.3</td>\n",
" <td>21.4</td>\n",
" <td>2.0</td>\n",
" <td>3.3</td>\n",
" <td>5.3</td>\n",
" <td>0.134</td>\n",
" <td>-1.9</td>\n",
" <td>1.2</td>\n",
" <td>-0.7</td>\n",
" <td>0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>217</th>\n",
" <td>2015</td>\n",
" <td>Andre Iguodala</td>\n",
" <td>G</td>\n",
" <td>31</td>\n",
" <td>GSW</td>\n",
" <td>59</td>\n",
" <td>0</td>\n",
" <td>27.1</td>\n",
" <td>2.8</td>\n",
" <td>6.1</td>\n",
" <td>...</td>\n",
" <td>14.8</td>\n",
" <td>12.7</td>\n",
" <td>1.5</td>\n",
" <td>2.3</td>\n",
" <td>3.8</td>\n",
" <td>0.114</td>\n",
" <td>-0.3</td>\n",
" <td>1.7</td>\n",
" <td>1.4</td>\n",
" <td>1.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>305</th>\n",
" <td>2015</td>\n",
" <td>Andre Miller</td>\n",
" <td>G</td>\n",
" <td>38</td>\n",
" <td>TOT</td>\n",
" <td>61</td>\n",
" <td>0</td>\n",
" <td>14.1</td>\n",
" <td>1.7</td>\n",
" <td>3.2</td>\n",
" <td>...</td>\n",
" <td>23.8</td>\n",
" <td>14.8</td>\n",
" <td>1.2</td>\n",
" <td>0.7</td>\n",
" <td>1.9</td>\n",
" <td>0.104</td>\n",
" <td>-1.0</td>\n",
" <td>-1.4</td>\n",
" <td>-2.5</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>372</th>\n",
" <td>2015</td>\n",
" <td>Andre Roberson</td>\n",
" <td>G</td>\n",
" <td>23</td>\n",
" <td>OKC</td>\n",
" <td>55</td>\n",
" <td>54</td>\n",
" <td>20.0</td>\n",
" <td>1.5</td>\n",
" <td>3.1</td>\n",
" <td>...</td>\n",
" <td>16.8</td>\n",
" <td>9.2</td>\n",
" <td>0.5</td>\n",
" <td>1.6</td>\n",
" <td>2.1</td>\n",
" <td>0.092</td>\n",
" <td>-1.8</td>\n",
" <td>2.4</td>\n",
" <td>0.6</td>\n",
" <td>0.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>2015</td>\n",
" <td>Andrea Bargnani</td>\n",
" <td>C</td>\n",
" <td>29</td>\n",
" <td>NYK</td>\n",
" <td>14</td>\n",
" <td>7</td>\n",
" <td>24.5</td>\n",
" <td>5.1</td>\n",
" <td>11.0</td>\n",
" <td>...</td>\n",
" <td>8.8</td>\n",
" <td>26.1</td>\n",
" <td>0.5</td>\n",
" <td>0.1</td>\n",
" <td>0.6</td>\n",
" <td>0.079</td>\n",
" <td>-0.7</td>\n",
" <td>-2.7</td>\n",
" <td>-3.5</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>251</th>\n",
" <td>2015</td>\n",
" <td>Andrei Kirilenko</td>\n",
" <td>F</td>\n",
" <td>33</td>\n",
" <td>BRK</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>5.1</td>\n",
" <td>0.0</td>\n",
" <td>0.7</td>\n",
" <td>...</td>\n",
" <td>12.9</td>\n",
" <td>9.9</td>\n",
" <td>-0.1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.057</td>\n",
" <td>-8.2</td>\n",
" <td>0.0</td>\n",
" <td>-8.3</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td>2015</td>\n",
" <td>Andrew Bogut</td>\n",
" <td>C</td>\n",
" <td>30</td>\n",
" <td>GSW</td>\n",
" <td>48</td>\n",
" <td>46</td>\n",
" <td>23.6</td>\n",
" <td>2.9</td>\n",
" <td>5.2</td>\n",
" <td>...</td>\n",
" <td>22.6</td>\n",
" <td>13.2</td>\n",
" <td>1.1</td>\n",
" <td>2.6</td>\n",
" <td>3.7</td>\n",
" <td>0.155</td>\n",
" <td>-2.0</td>\n",
" <td>5.5</td>\n",
" <td>3.5</td>\n",
" <td>1.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>329</th>\n",
" <td>2015</td>\n",
" <td>Andrew Nicholson</td>\n",
" <td>F</td>\n",
" <td>25</td>\n",
" <td>ORL</td>\n",
" <td>26</td>\n",
" <td>0</td>\n",
" <td>10.7</td>\n",
" <td>1.8</td>\n",
" <td>4.5</td>\n",
" <td>...</td>\n",
" <td>8.2</td>\n",
" <td>22.1</td>\n",
" <td>-0.3</td>\n",
" <td>0.2</td>\n",
" <td>-0.1</td>\n",
" <td>-0.026</td>\n",
" <td>-5.2</td>\n",
" <td>-2.4</td>\n",
" <td>-7.7</td>\n",
" <td>-0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>458</th>\n",
" <td>2015</td>\n",
" <td>Andrew Wiggins</td>\n",
" <td>G</td>\n",
" <td>19</td>\n",
" <td>MIN</td>\n",
" <td>62</td>\n",
" <td>62</td>\n",
" <td>35.0</td>\n",
" <td>5.9</td>\n",
" <td>13.6</td>\n",
" <td>...</td>\n",
" <td>11.1</td>\n",
" <td>21.9</td>\n",
" <td>1.1</td>\n",
" <td>0.4</td>\n",
" <td>1.5</td>\n",
" <td>0.032</td>\n",
" <td>-0.7</td>\n",
" <td>-1.4</td>\n",
" <td>-2.1</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>2015</td>\n",
" <td>Anthony Bennett</td>\n",
" <td>F</td>\n",
" <td>21</td>\n",
" <td>MIN</td>\n",
" <td>53</td>\n",
" <td>3</td>\n",
" <td>15.8</td>\n",
" <td>2.2</td>\n",
" <td>5.2</td>\n",
" <td>...</td>\n",
" <td>9.3</td>\n",
" <td>17.3</td>\n",
" <td>-0.1</td>\n",
" <td>0.4</td>\n",
" <td>0.4</td>\n",
" <td>0.022</td>\n",
" <td>-3.7</td>\n",
" <td>-0.9</td>\n",
" <td>-4.6</td>\n",
" <td>-0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>109</th>\n",
" <td>2015</td>\n",
" <td>Anthony Davis</td>\n",
" <td>F</td>\n",
" <td>21</td>\n",
" <td>NOP</td>\n",
" <td>53</td>\n",
" <td>53</td>\n",
" <td>35.6</td>\n",
" <td>9.5</td>\n",
" <td>17.5</td>\n",
" <td>...</td>\n",
" <td>6.5</td>\n",
" <td>27.8</td>\n",
" <td>8.1</td>\n",
" <td>3.0</td>\n",
" <td>11.1</td>\n",
" <td>0.282</td>\n",
" <td>4.4</td>\n",
" <td>2.3</td>\n",
" <td>6.7</td>\n",
" <td>4.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>452</th>\n",
" <td>2015</td>\n",
" <td>Travis Wear</td>\n",
" <td>F</td>\n",
" <td>24</td>\n",
" <td>NYK</td>\n",
" <td>45</td>\n",
" <td>1</td>\n",
" <td>12.4</td>\n",
" <td>1.6</td>\n",
" <td>4.0</td>\n",
" <td>...</td>\n",
" <td>14.6</td>\n",
" <td>18.2</td>\n",
" <td>-0.4</td>\n",
" <td>0.1</td>\n",
" <td>-0.3</td>\n",
" <td>-0.026</td>\n",
" <td>-4.5</td>\n",
" <td>-1.9</td>\n",
" <td>-6.4</td>\n",
" <td>-0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>2015</td>\n",
" <td>Trevor Ariza</td>\n",
" <td>F</td>\n",
" <td>29</td>\n",
" <td>HOU</td>\n",
" <td>63</td>\n",
" <td>63</td>\n",
" <td>35.6</td>\n",
" <td>4.4</td>\n",
" <td>11.3</td>\n",
" <td>...</td>\n",
" <td>12.0</td>\n",
" <td>16.7</td>\n",
" <td>1.6</td>\n",
" <td>3.1</td>\n",
" <td>4.7</td>\n",
" <td>0.100</td>\n",
" <td>0.2</td>\n",
" <td>1.3</td>\n",
" <td>1.5</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td>2015</td>\n",
" <td>Trevor Booker</td>\n",
" <td>F</td>\n",
" <td>27</td>\n",
" <td>UTA</td>\n",
" <td>61</td>\n",
" <td>1</td>\n",
" <td>18.6</td>\n",
" <td>2.8</td>\n",
" <td>5.6</td>\n",
" <td>...</td>\n",
" <td>16.2</td>\n",
" <td>18.6</td>\n",
" <td>0.9</td>\n",
" <td>1.1</td>\n",
" <td>2.0</td>\n",
" <td>0.087</td>\n",
" <td>-1.0</td>\n",
" <td>0.0</td>\n",
" <td>-1.0</td>\n",
" <td>0.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>67</th>\n",
" <td>2015</td>\n",
" <td>Trey Burke</td>\n",
" <td>G</td>\n",
" <td>22</td>\n",
" <td>UTA</td>\n",
" <td>62</td>\n",
" <td>42</td>\n",
" <td>30.9</td>\n",
" <td>4.9</td>\n",
" <td>13.2</td>\n",
" <td>...</td>\n",
" <td>10.5</td>\n",
" <td>23.2</td>\n",
" <td>0.8</td>\n",
" <td>0.9</td>\n",
" <td>1.7</td>\n",
" <td>0.043</td>\n",
" <td>0.1</td>\n",
" <td>-2.2</td>\n",
" <td>-2.1</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>429</th>\n",
" <td>2015</td>\n",
" <td>Tristan Thompson</td>\n",
" <td>F</td>\n",
" <td>23</td>\n",
" <td>CLE</td>\n",
" <td>66</td>\n",
" <td>12</td>\n",
" <td>27.5</td>\n",
" <td>3.4</td>\n",
" <td>6.2</td>\n",
" <td>...</td>\n",
" <td>12.3</td>\n",
" <td>14.2</td>\n",
" <td>4.0</td>\n",
" <td>1.7</td>\n",
" <td>5.7</td>\n",
" <td>0.150</td>\n",
" <td>0.0</td>\n",
" <td>-0.3</td>\n",
" <td>-0.3</td>\n",
" <td>0.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>106</th>\n",
" <td>2015</td>\n",
" <td>Troy Daniels</td>\n",
" <td>G</td>\n",
" <td>23</td>\n",
" <td>TOT</td>\n",
" <td>39</td>\n",
" <td>0</td>\n",
" <td>7.0</td>\n",
" <td>0.9</td>\n",
" <td>2.8</td>\n",
" <td>...</td>\n",
" <td>11.1</td>\n",
" <td>20.2</td>\n",
" <td>-0.2</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>-0.026</td>\n",
" <td>-1.9</td>\n",
" <td>-4.8</td>\n",
" <td>-6.7</td>\n",
" <td>-0.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>262</th>\n",
" <td>2015</td>\n",
" <td>Ty Lawson</td>\n",
" <td>G</td>\n",
" <td>27</td>\n",
" <td>DEN</td>\n",
" <td>61</td>\n",
" <td>61</td>\n",
" <td>35.9</td>\n",
" <td>5.6</td>\n",
" <td>12.6</td>\n",
" <td>...</td>\n",
" <td>14.2</td>\n",
" <td>21.0</td>\n",
" <td>5.5</td>\n",
" <td>1.0</td>\n",
" <td>6.5</td>\n",
" <td>0.142</td>\n",
" <td>3.5</td>\n",
" <td>-2.0</td>\n",
" <td>1.4</td>\n",
" <td>1.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>136</th>\n",
" <td>2015</td>\n",
" <td>Tyler Ennis</td>\n",
" <td>G</td>\n",
" <td>20</td>\n",
" <td>TOT</td>\n",
" <td>17</td>\n",
" <td>0</td>\n",
" <td>11.4</td>\n",
" <td>1.6</td>\n",
" <td>4.1</td>\n",
" <td>...</td>\n",
" <td>22.5</td>\n",
" <td>21.6</td>\n",
" <td>-0.3</td>\n",
" <td>0.2</td>\n",
" <td>-0.1</td>\n",
" <td>-0.031</td>\n",
" <td>-4.9</td>\n",
" <td>-1.6</td>\n",
" <td>-6.5</td>\n",
" <td>-0.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>185</th>\n",
" <td>2015</td>\n",
" <td>Tyler Hansbrough</td>\n",
" <td>F</td>\n",
" <td>29</td>\n",
" <td>TOR</td>\n",
" <td>56</td>\n",
" <td>1</td>\n",
" <td>12.4</td>\n",
" <td>0.9</td>\n",
" <td>1.9</td>\n",
" <td>...</td>\n",
" <td>9.4</td>\n",
" <td>10.3</td>\n",
" <td>1.3</td>\n",
" <td>0.6</td>\n",
" <td>1.9</td>\n",
" <td>0.131</td>\n",
" <td>-0.6</td>\n",
" <td>-0.3</td>\n",
" <td>-0.9</td>\n",
" <td>0.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>237</th>\n",
" <td>2015</td>\n",
" <td>Tyler Johnson</td>\n",
" <td>G</td>\n",
" <td>22</td>\n",
" <td>MIA</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>19.8</td>\n",
" <td>2.9</td>\n",
" <td>5.6</td>\n",
" <td>...</td>\n",
" <td>13.4</td>\n",
" <td>18.0</td>\n",
" <td>0.6</td>\n",
" <td>0.3</td>\n",
" <td>0.9</td>\n",
" <td>0.131</td>\n",
" <td>0.9</td>\n",
" <td>-0.4</td>\n",
" <td>0.6</td>\n",
" <td>0.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>477</th>\n",
" <td>2015</td>\n",
" <td>Tyler Zeller</td>\n",
" <td>C</td>\n",
" <td>25</td>\n",
" <td>BOS</td>\n",
" <td>62</td>\n",
" <td>39</td>\n",
" <td>20.8</td>\n",
" <td>3.9</td>\n",
" <td>7.1</td>\n",
" <td>...</td>\n",
" <td>10.5</td>\n",
" <td>19.1</td>\n",
" <td>3.2</td>\n",
" <td>1.3</td>\n",
" <td>4.5</td>\n",
" <td>0.167</td>\n",
" <td>0.2</td>\n",
" <td>0.4</td>\n",
" <td>0.7</td>\n",
" <td>0.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>2015</td>\n",
" <td>Tyreke Evans</td>\n",
" <td>F</td>\n",
" <td>25</td>\n",
" <td>NOP</td>\n",
" <td>63</td>\n",
" <td>60</td>\n",
" <td>34.6</td>\n",
" <td>6.6</td>\n",
" <td>15.1</td>\n",
" <td>...</td>\n",
" <td>15.5</td>\n",
" <td>26.1</td>\n",
" <td>1.8</td>\n",
" <td>1.5</td>\n",
" <td>3.3</td>\n",
" <td>0.073</td>\n",
" <td>1.5</td>\n",
" <td>-0.2</td>\n",
" <td>1.4</td>\n",
" <td>1.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>425</th>\n",
" <td>2015</td>\n",
" <td>Tyrus Thomas</td>\n",
" <td>F</td>\n",
" <td>28</td>\n",
" <td>MEM</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>3.5</td>\n",
" <td>0.5</td>\n",
" <td>0.5</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>12.3</td>\n",
" <td>0.1</td>\n",
" <td>0.0</td>\n",
" <td>0.1</td>\n",
" <td>0.475</td>\n",
" <td>6.9</td>\n",
" <td>-8.6</td>\n",
" <td>-1.7</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>83</th>\n",
" <td>2015</td>\n",
" <td>Tyson Chandler</td>\n",
" <td>C</td>\n",
" <td>32</td>\n",
" <td>DAL</td>\n",
" <td>60</td>\n",
" <td>60</td>\n",
" <td>30.7</td>\n",
" <td>4.0</td>\n",
" <td>5.9</td>\n",
" <td>...</td>\n",
" <td>16.0</td>\n",
" <td>12.8</td>\n",
" <td>6.1</td>\n",
" <td>2.6</td>\n",
" <td>8.7</td>\n",
" <td>0.226</td>\n",
" <td>2.1</td>\n",
" <td>2.4</td>\n",
" <td>4.4</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>193</th>\n",
" <td>2015</td>\n",
" <td>Udonis Haslem</td>\n",
" <td>F</td>\n",
" <td>34</td>\n",
" <td>MIA</td>\n",
" <td>46</td>\n",
" <td>11</td>\n",
" <td>14.0</td>\n",
" <td>1.4</td>\n",
" <td>3.3</td>\n",
" <td>...</td>\n",
" <td>10.8</td>\n",
" <td>14.3</td>\n",
" <td>0.3</td>\n",
" <td>0.5</td>\n",
" <td>0.9</td>\n",
" <td>0.065</td>\n",
" <td>-3.7</td>\n",
" <td>-0.6</td>\n",
" <td>-4.2</td>\n",
" <td>-0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>89</th>\n",
" <td>2015</td>\n",
" <td>Victor Claver</td>\n",
" <td>F</td>\n",
" <td>26</td>\n",
" <td>POR</td>\n",
" <td>10</td>\n",
" <td>0</td>\n",
" <td>7.6</td>\n",
" <td>0.9</td>\n",
" <td>2.0</td>\n",
" <td>...</td>\n",
" <td>16.7</td>\n",
" <td>14.1</td>\n",
" <td>0.0</td>\n",
" <td>0.1</td>\n",
" <td>0.1</td>\n",
" <td>0.092</td>\n",
" <td>-3.0</td>\n",
" <td>-1.1</td>\n",
" <td>-4.1</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>338</th>\n",
" <td>2015</td>\n",
" <td>Victor Oladipo</td>\n",
" <td>G</td>\n",
" <td>22</td>\n",
" <td>ORL</td>\n",
" <td>55</td>\n",
" <td>54</td>\n",
" <td>34.8</td>\n",
" <td>6.4</td>\n",
" <td>14.2</td>\n",
" <td>...</td>\n",
" <td>14.7</td>\n",
" <td>24.8</td>\n",
" <td>1.6</td>\n",
" <td>1.4</td>\n",
" <td>3.0</td>\n",
" <td>0.076</td>\n",
" <td>0.9</td>\n",
" <td>-0.5</td>\n",
" <td>0.4</td>\n",
" <td>1.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>79</th>\n",
" <td>2015</td>\n",
" <td>Vince Carter</td>\n",
" <td>G</td>\n",
" <td>38</td>\n",
" <td>MEM</td>\n",
" <td>47</td>\n",
" <td>0</td>\n",
" <td>16.1</td>\n",
" <td>2.1</td>\n",
" <td>6.4</td>\n",
" <td>...</td>\n",
" <td>9.2</td>\n",
" <td>21.2</td>\n",
" <td>-0.5</td>\n",
" <td>1.0</td>\n",
" <td>0.5</td>\n",
" <td>0.032</td>\n",
" <td>-1.1</td>\n",
" <td>-0.5</td>\n",
" <td>-1.6</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133</th>\n",
" <td>2015</td>\n",
" <td>Wayne Ellington</td>\n",
" <td>G</td>\n",
" <td>27</td>\n",
" <td>LAL</td>\n",
" <td>54</td>\n",
" <td>29</td>\n",
" <td>25.2</td>\n",
" <td>3.8</td>\n",
" <td>8.9</td>\n",
" <td>...</td>\n",
" <td>7.3</td>\n",
" <td>17.8</td>\n",
" <td>1.3</td>\n",
" <td>0.1</td>\n",
" <td>1.4</td>\n",
" <td>0.050</td>\n",
" <td>0.1</td>\n",
" <td>-2.3</td>\n",
" <td>-2.2</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>238</th>\n",
" <td>2015</td>\n",
" <td>Wesley Johnson</td>\n",
" <td>F</td>\n",
" <td>27</td>\n",
" <td>LAL</td>\n",
" <td>59</td>\n",
" <td>42</td>\n",
" <td>28.8</td>\n",
" <td>3.6</td>\n",
" <td>8.5</td>\n",
" <td>...</td>\n",
" <td>10.3</td>\n",
" <td>15.8</td>\n",
" <td>1.4</td>\n",
" <td>0.5</td>\n",
" <td>1.9</td>\n",
" <td>0.055</td>\n",
" <td>-0.1</td>\n",
" <td>-0.4</td>\n",
" <td>-0.6</td>\n",
" <td>0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>288</th>\n",
" <td>2015</td>\n",
" <td>Wesley Matthews</td>\n",
" <td>G</td>\n",
" <td>28</td>\n",
" <td>POR</td>\n",
" <td>60</td>\n",
" <td>60</td>\n",
" <td>33.7</td>\n",
" <td>5.6</td>\n",
" <td>12.6</td>\n",
" <td>...</td>\n",
" <td>9.0</td>\n",
" <td>19.8</td>\n",
" <td>4.0</td>\n",
" <td>2.5</td>\n",
" <td>6.4</td>\n",
" <td>0.153</td>\n",
" <td>3.7</td>\n",
" <td>0.3</td>\n",
" <td>4.0</td>\n",
" <td>3.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>2015</td>\n",
" <td>Will Barton</td>\n",
" <td>G</td>\n",
" <td>24</td>\n",
" <td>TOT</td>\n",
" <td>40</td>\n",
" <td>0</td>\n",
" <td>14.2</td>\n",
" <td>2.2</td>\n",
" <td>5.0</td>\n",
" <td>...</td>\n",
" <td>12.1</td>\n",
" <td>19.9</td>\n",
" <td>0.1</td>\n",
" <td>0.7</td>\n",
" <td>0.8</td>\n",
" <td>0.067</td>\n",
" <td>-2.0</td>\n",
" <td>0.6</td>\n",
" <td>-1.4</td>\n",
" <td>0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>85</th>\n",
" <td>2015</td>\n",
" <td>Will Cherry</td>\n",
" <td>G</td>\n",
" <td>23</td>\n",
" <td>CLE</td>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>8.6</td>\n",
" <td>0.6</td>\n",
" <td>2.4</td>\n",
" <td>...</td>\n",
" <td>15.6</td>\n",
" <td>16.7</td>\n",
" <td>-0.1</td>\n",
" <td>0.1</td>\n",
" <td>0.0</td>\n",
" <td>-0.022</td>\n",
" <td>-4.4</td>\n",
" <td>0.7</td>\n",
" <td>-3.7</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>179</th>\n",
" <td>2015</td>\n",
" <td>Willie Green</td>\n",
" <td>G</td>\n",
" <td>33</td>\n",
" <td>ORL</td>\n",
" <td>42</td>\n",
" <td>2</td>\n",
" <td>17.8</td>\n",
" <td>2.2</td>\n",
" <td>5.7</td>\n",
" <td>...</td>\n",
" <td>12.9</td>\n",
" <td>17.6</td>\n",
" <td>-0.3</td>\n",
" <td>0.3</td>\n",
" <td>0.0</td>\n",
" <td>-0.003</td>\n",
" <td>-2.8</td>\n",
" <td>-2.2</td>\n",
" <td>-5.0</td>\n",
" <td>-0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>84</th>\n",
" <td>2015</td>\n",
" <td>Wilson Chandler</td>\n",
" <td>F</td>\n",
" <td>27</td>\n",
" <td>DEN</td>\n",
" <td>61</td>\n",
" <td>58</td>\n",
" <td>31.5</td>\n",
" <td>5.4</td>\n",
" <td>12.7</td>\n",
" <td>...</td>\n",
" <td>10.0</td>\n",
" <td>20.4</td>\n",
" <td>1.2</td>\n",
" <td>1.3</td>\n",
" <td>2.5</td>\n",
" <td>0.062</td>\n",
" <td>0.2</td>\n",
" <td>-0.5</td>\n",
" <td>-0.2</td>\n",
" <td>0.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>199</th>\n",
" <td>2015</td>\n",
" <td>Xavier Henry</td>\n",
" <td>F</td>\n",
" <td>23</td>\n",
" <td>LAL</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>9.6</td>\n",
" <td>0.3</td>\n",
" <td>1.4</td>\n",
" <td>...</td>\n",
" <td>11.3</td>\n",
" <td>13.7</td>\n",
" <td>-0.1</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>-0.030</td>\n",
" <td>-5.3</td>\n",
" <td>-2.3</td>\n",
" <td>-7.6</td>\n",
" <td>-0.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>261</th>\n",
" <td>2015</td>\n",
" <td>Zach LaVine</td>\n",
" <td>G</td>\n",
" <td>19</td>\n",
" <td>MIN</td>\n",
" <td>57</td>\n",
" <td>23</td>\n",
" <td>20.4</td>\n",
" <td>2.9</td>\n",
" <td>6.9</td>\n",
" <td>...</td>\n",
" <td>21.3</td>\n",
" <td>20.6</td>\n",
" <td>-0.9</td>\n",
" <td>0.2</td>\n",
" <td>-0.7</td>\n",
" <td>-0.029</td>\n",
" <td>-2.9</td>\n",
" <td>-2.2</td>\n",
" <td>-5.0</td>\n",
" <td>-0.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>366</th>\n",
" <td>2015</td>\n",
" <td>Zach Randolph</td>\n",
" <td>F</td>\n",
" <td>33</td>\n",
" <td>MEM</td>\n",
" <td>53</td>\n",
" <td>53</td>\n",
" <td>32.6</td>\n",
" <td>6.6</td>\n",
" <td>13.4</td>\n",
" <td>...</td>\n",
" <td>12.4</td>\n",
" <td>24.5</td>\n",
" <td>2.6</td>\n",
" <td>2.9</td>\n",
" <td>5.5</td>\n",
" <td>0.153</td>\n",
" <td>0.2</td>\n",
" <td>0.8</td>\n",
" <td>1.0</td>\n",
" <td>1.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>340</th>\n",
" <td>2015</td>\n",
" <td>Zaza Pachulia</td>\n",
" <td>C</td>\n",
" <td>30</td>\n",
" <td>MIL</td>\n",
" <td>54</td>\n",
" <td>26</td>\n",
" <td>22.5</td>\n",
" <td>2.9</td>\n",
" <td>6.8</td>\n",
" <td>...</td>\n",
" <td>18.7</td>\n",
" <td>18.9</td>\n",
" <td>0.1</td>\n",
" <td>2.0</td>\n",
" <td>2.1</td>\n",
" <td>0.084</td>\n",
" <td>-2.2</td>\n",
" <td>2.0</td>\n",
" <td>-0.2</td>\n",
" <td>0.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>125</th>\n",
" <td>2015</td>\n",
" <td>Zoran Dragic</td>\n",
" <td>G</td>\n",
" <td>25</td>\n",
" <td>TOT</td>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>2.3</td>\n",
" <td>0.3</td>\n",
" <td>1.0</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>22.6</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.056</td>\n",
" <td>-1.9</td>\n",
" <td>-5.3</td>\n",
" <td>-7.2</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>478 rows × 49 columns</p>\n",
"</div>"
],
"text/plain": [
" season_end player pos age bref_team_id g gs mp fg \\\n",
"359 2015 A.J. Price G 28 TOT 21 0 13.3 2.3 \n",
"60 2015 Aaron Brooks G 30 CHI 65 9 21.0 3.9 \n",
"166 2015 Aaron Gordon F 19 ORL 30 6 15.2 1.9 \n",
"348 2015 Adreian Payne F 23 TOT 12 3 19.7 2.3 \n",
"212 2015 Al Horford C 28 ATL 60 60 30.8 6.8 \n",
"225 2015 Al Jefferson C 30 CHO 53 49 31.4 7.8 \n",
"11 2015 Al-Farouq Aminu F 24 DAL 60 3 17.0 2.0 \n",
"14 2015 Alan Anderson G 32 BRK 62 19 23.8 2.5 \n",
"68 2015 Alec Burks G 23 UTA 27 27 33.3 4.5 \n",
"252 2015 Alex Kirk C 23 CLE 5 0 2.8 0.2 \n",
"267 2015 Alex Len C 21 PHO 61 36 21.7 2.7 \n",
"394 2015 Alexey Shved G 26 TOT 35 2 15.7 2.7 \n",
"5 2015 Alexis Ajinca C 26 NOP 51 6 14.0 2.8 \n",
"99 2015 Allen Crabbe G 22 POR 38 7 12.4 1.1 \n",
"160 2015 Alonzo Gee F 27 TOT 43 0 12.4 1.6 \n",
"413 2015 Amar'e Stoudemire F 32 TOT 44 14 22.8 4.7 \n",
"232 2015 Amir Johnson F 27 TOR 61 60 26.5 4.0 \n",
"439 2015 Anderson Varejao C 32 CLE 26 26 24.5 4.3 \n",
"112 2015 Andre Dawkins G 23 MIA 4 0 5.5 0.3 \n",
"127 2015 Andre Drummond C 21 DET 63 63 30.0 5.7 \n",
"217 2015 Andre Iguodala G 31 GSW 59 0 27.1 2.8 \n",
"305 2015 Andre Miller G 38 TOT 61 0 14.1 1.7 \n",
"372 2015 Andre Roberson G 23 OKC 55 54 20.0 1.5 \n",
"30 2015 Andrea Bargnani C 29 NYK 14 7 24.5 5.1 \n",
"251 2015 Andrei Kirilenko F 33 BRK 7 0 5.1 0.0 \n",
"52 2015 Andrew Bogut C 30 GSW 48 46 23.6 2.9 \n",
"329 2015 Andrew Nicholson F 25 ORL 26 0 10.7 1.8 \n",
"458 2015 Andrew Wiggins G 19 MIN 62 62 35.0 5.9 \n",
"44 2015 Anthony Bennett F 21 MIN 53 3 15.8 2.2 \n",
"109 2015 Anthony Davis F 21 NOP 53 53 35.6 9.5 \n",
".. ... ... .. ... ... .. .. ... ... \n",
"452 2015 Travis Wear F 24 NYK 45 1 12.4 1.6 \n",
"21 2015 Trevor Ariza F 29 HOU 63 63 35.6 4.4 \n",
"54 2015 Trevor Booker F 27 UTA 61 1 18.6 2.8 \n",
"67 2015 Trey Burke G 22 UTA 62 42 30.9 4.9 \n",
"429 2015 Tristan Thompson F 23 CLE 66 12 27.5 3.4 \n",
"106 2015 Troy Daniels G 23 TOT 39 0 7.0 0.9 \n",
"262 2015 Ty Lawson G 27 DEN 61 61 35.9 5.6 \n",
"136 2015 Tyler Ennis G 20 TOT 17 0 11.4 1.6 \n",
"185 2015 Tyler Hansbrough F 29 TOR 56 1 12.4 0.9 \n",
"237 2015 Tyler Johnson G 22 MIA 16 1 19.8 2.9 \n",
"477 2015 Tyler Zeller C 25 BOS 62 39 20.8 3.9 \n",
"139 2015 Tyreke Evans F 25 NOP 63 60 34.6 6.6 \n",
"425 2015 Tyrus Thomas F 28 MEM 2 0 3.5 0.5 \n",
"83 2015 Tyson Chandler C 32 DAL 60 60 30.7 4.0 \n",
"193 2015 Udonis Haslem F 34 MIA 46 11 14.0 1.4 \n",
"89 2015 Victor Claver F 26 POR 10 0 7.6 0.9 \n",
"338 2015 Victor Oladipo G 22 ORL 55 54 34.8 6.4 \n",
"79 2015 Vince Carter G 38 MEM 47 0 16.1 2.1 \n",
"133 2015 Wayne Ellington G 27 LAL 54 29 25.2 3.8 \n",
"238 2015 Wesley Johnson F 27 LAL 59 42 28.8 3.6 \n",
"288 2015 Wesley Matthews G 28 POR 60 60 33.7 5.6 \n",
"34 2015 Will Barton G 24 TOT 40 0 14.2 2.2 \n",
"85 2015 Will Cherry G 23 CLE 8 0 8.6 0.6 \n",
"179 2015 Willie Green G 33 ORL 42 2 17.8 2.2 \n",
"84 2015 Wilson Chandler F 27 DEN 61 58 31.5 5.4 \n",
"199 2015 Xavier Henry F 23 LAL 9 0 9.6 0.3 \n",
"261 2015 Zach LaVine G 19 MIN 57 23 20.4 2.9 \n",
"366 2015 Zach Randolph F 33 MEM 53 53 32.6 6.6 \n",
"340 2015 Zaza Pachulia C 30 MIL 54 26 22.5 2.9 \n",
"125 2015 Zoran Dragic G 25 TOT 8 0 2.3 0.3 \n",
"\n",
" fga ... TOV% USG% OWS DWS WS WS/48 OBPM DBPM BPM VORP \n",
"359 5.9 ... 8.9 23.6 0.2 0.2 0.4 0.072 0.5 -2.8 -2.4 0.0 \n",
"60 9.3 ... 15.5 25.7 1.1 1.0 2.1 0.073 0.7 -2.8 -2.1 0.0 \n",
"166 3.8 ... 17.0 15.9 0.3 0.3 0.6 0.066 -2.5 -0.5 -3.1 -0.1 \n",
"348 6.1 ... 13.6 17.7 -0.3 0.1 -0.1 -0.024 -5.8 -2.5 -8.3 -0.4 \n",
"212 12.6 ... 9.1 22.1 4.6 3.0 7.5 0.195 1.7 2.7 4.5 3.0 \n",
"225 16.0 ... 5.4 26.4 1.5 2.9 4.5 0.129 -0.9 1.7 0.8 1.2 \n",
"11 4.7 ... 11.8 15.7 0.9 1.7 2.6 0.124 -0.6 3.0 2.3 1.1 \n",
"14 5.7 ... 11.8 13.7 1.3 0.9 2.1 0.070 -0.2 -0.3 -0.5 0.6 \n",
"68 11.1 ... 12.7 20.9 1.1 0.5 1.5 0.082 -0.3 -1.3 -1.6 0.1 \n",
"252 0.8 ... 0.0 15.7 0.0 0.0 0.0 0.060 -3.0 -4.3 -7.3 0.0 \n",
"267 5.0 ... 15.4 13.7 1.5 1.8 3.3 0.119 -2.8 2.0 -0.8 0.4 \n",
"394 6.8 ... 10.1 25.8 1.4 0.3 1.7 0.149 3.1 -3.3 -0.3 0.2 \n",
"5 4.8 ... 15.3 20.8 1.8 0.9 2.7 0.181 0.4 0.2 0.7 0.5 \n",
"99 2.5 ... 9.3 10.2 0.5 0.6 1.1 0.109 -0.9 1.4 0.4 0.3 \n",
"160 3.3 ... 14.0 16.3 0.6 0.5 1.1 0.100 -0.8 0.5 -0.3 0.2 \n",
"413 8.4 ... 14.0 23.2 2.0 0.8 2.8 0.134 -0.2 -0.7 -0.9 0.3 \n",
"232 7.0 ... 15.9 15.6 2.8 1.3 4.1 0.123 0.9 1.1 2.0 1.6 \n",
"439 7.7 ... 13.7 18.0 1.2 0.7 1.9 0.145 0.0 1.0 1.0 0.5 \n",
"112 1.5 ... 14.3 15.1 -0.1 0.0 -0.1 -0.177 -7.5 -4.1 -11.6 -0.1 \n",
"127 11.2 ... 10.3 21.4 2.0 3.3 5.3 0.134 -1.9 1.2 -0.7 0.6 \n",
"217 6.1 ... 14.8 12.7 1.5 2.3 3.8 0.114 -0.3 1.7 1.4 1.4 \n",
"305 3.2 ... 23.8 14.8 1.2 0.7 1.9 0.104 -1.0 -1.4 -2.5 -0.1 \n",
"372 3.1 ... 16.8 9.2 0.5 1.6 2.1 0.092 -1.8 2.4 0.6 0.7 \n",
"30 11.0 ... 8.8 26.1 0.5 0.1 0.6 0.079 -0.7 -2.7 -3.5 -0.1 \n",
"251 0.7 ... 12.9 9.9 -0.1 0.0 0.0 -0.057 -8.2 0.0 -8.3 -0.1 \n",
"52 5.2 ... 22.6 13.2 1.1 2.6 3.7 0.155 -2.0 5.5 3.5 1.6 \n",
"329 4.5 ... 8.2 22.1 -0.3 0.2 -0.1 -0.026 -5.2 -2.4 -7.7 -0.4 \n",
"458 13.6 ... 11.1 21.9 1.1 0.4 1.5 0.032 -0.7 -1.4 -2.1 -0.1 \n",
"44 5.2 ... 9.3 17.3 -0.1 0.4 0.4 0.022 -3.7 -0.9 -4.6 -0.6 \n",
"109 17.5 ... 6.5 27.8 8.1 3.0 11.1 0.282 4.4 2.3 6.7 4.1 \n",
".. ... ... ... ... ... ... ... ... ... ... ... ... \n",
"452 4.0 ... 14.6 18.2 -0.4 0.1 -0.3 -0.026 -4.5 -1.9 -6.4 -0.6 \n",
"21 11.3 ... 12.0 16.7 1.6 3.1 4.7 0.100 0.2 1.3 1.5 2.0 \n",
"54 5.6 ... 16.2 18.6 0.9 1.1 2.0 0.087 -1.0 0.0 -1.0 0.3 \n",
"67 13.2 ... 10.5 23.2 0.8 0.9 1.7 0.043 0.1 -2.2 -2.1 -0.1 \n",
"429 6.2 ... 12.3 14.2 4.0 1.7 5.7 0.150 0.0 -0.3 -0.3 0.8 \n",
"106 2.8 ... 11.1 20.2 -0.2 0.0 -0.1 -0.026 -1.9 -4.8 -6.7 -0.3 \n",
"262 12.6 ... 14.2 21.0 5.5 1.0 6.5 0.142 3.5 -2.0 1.4 1.9 \n",
"136 4.1 ... 22.5 21.6 -0.3 0.2 -0.1 -0.031 -4.9 -1.6 -6.5 -0.2 \n",
"185 1.9 ... 9.4 10.3 1.3 0.6 1.9 0.131 -0.6 -0.3 -0.9 0.2 \n",
"237 5.6 ... 13.4 18.0 0.6 0.3 0.9 0.131 0.9 -0.4 0.6 0.2 \n",
"477 7.1 ... 10.5 19.1 3.2 1.3 4.5 0.167 0.2 0.4 0.7 0.9 \n",
"139 15.1 ... 15.5 26.1 1.8 1.5 3.3 0.073 1.5 -0.2 1.4 1.9 \n",
"425 0.5 ... 0.0 12.3 0.1 0.0 0.1 0.475 6.9 -8.6 -1.7 0.0 \n",
"83 5.9 ... 16.0 12.8 6.1 2.6 8.7 0.226 2.1 2.4 4.4 3.0 \n",
"193 3.3 ... 10.8 14.3 0.3 0.5 0.9 0.065 -3.7 -0.6 -4.2 -0.4 \n",
"89 2.0 ... 16.7 14.1 0.0 0.1 0.1 0.092 -3.0 -1.1 -4.1 0.0 \n",
"338 14.2 ... 14.7 24.8 1.6 1.4 3.0 0.076 0.9 -0.5 0.4 1.1 \n",
"79 6.4 ... 9.2 21.2 -0.5 1.0 0.5 0.032 -1.1 -0.5 -1.6 0.1 \n",
"133 8.9 ... 7.3 17.8 1.3 0.1 1.4 0.050 0.1 -2.3 -2.2 -0.1 \n",
"238 8.5 ... 10.3 15.8 1.4 0.5 1.9 0.055 -0.1 -0.4 -0.6 0.6 \n",
"288 12.6 ... 9.0 19.8 4.0 2.5 6.4 0.153 3.7 0.3 4.0 3.1 \n",
"34 5.0 ... 12.1 19.9 0.1 0.7 0.8 0.067 -2.0 0.6 -1.4 0.1 \n",
"85 2.4 ... 15.6 16.7 -0.1 0.1 0.0 -0.022 -4.4 0.7 -3.7 0.0 \n",
"179 5.7 ... 12.9 17.6 -0.3 0.3 0.0 -0.003 -2.8 -2.2 -5.0 -0.6 \n",
"84 12.7 ... 10.0 20.4 1.2 1.3 2.5 0.062 0.2 -0.5 -0.2 0.9 \n",
"199 1.4 ... 11.3 13.7 -0.1 0.0 -0.1 -0.030 -5.3 -2.3 -7.6 -0.1 \n",
"261 6.9 ... 21.3 20.6 -0.9 0.2 -0.7 -0.029 -2.9 -2.2 -5.0 -0.9 \n",
"366 13.4 ... 12.4 24.5 2.6 2.9 5.5 0.153 0.2 0.8 1.0 1.3 \n",
"340 6.8 ... 18.7 18.9 0.1 2.0 2.1 0.084 -2.2 2.0 -0.2 0.6 \n",
"125 1.0 ... 0.0 22.6 0.0 0.0 0.0 -0.056 -1.9 -5.3 -7.2 0.0 \n",
"\n",
"[478 rows x 49 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nba_df.sort_values(\"player\", ascending=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #7. Filter the data set. Create three sub DataFrames from the `position` column for `G`, `F`, and `C`."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "False",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3077\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3078\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3079\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: False",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-7-eac4a07c8076>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnba_df_guard\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnba_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnba_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"pos\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"G\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2686\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2687\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2688\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2689\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2690\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2693\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2694\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2695\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2697\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 2487\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2488\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2489\u001b[0;31m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2490\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2491\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m 4113\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4114\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4115\u001b[0;31m \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4116\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4117\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3078\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3079\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3080\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3081\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3082\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: False"
]
}
],
"source": [
"nba_df_guard = nba_df[nba_df[[\"pos\"] == \"G\"]]\n",
"\n",
"#I don't understand this error."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### #8. Run `describe()` on these new DataFrames. Compare the mean field goals (the `fg` column) between positions."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nba_df_guard.describe()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nba_df_forward.describe()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nba_df_center.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The end!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Great job!"
]
}
],
"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": "3.7.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
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