#!/usr/bin/env python
# coding: utf-8

# In[2]:


get_ipython().run_line_magic('matplotlib', 'inline')


# In[3]:


import requests
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
shot_chart_url = 'http://stats.nba.com/stats/shotchartdetail?CFID=33&CFPAR'\
                'AMS=2014-15&ContextFilter=&ContextMeasure=FGA&DateFrom=&D'\
                'ateTo=&GameID=&GameSegment=&LastNGames=0&LeagueID=00&Loca'\
                'tion=&MeasureType=Base&Month=0&OpponentTeamID=0&Outcome=&'\
                'PaceAdjust=N&PerMode=PerGame&Period=0&PlayerID=201935&Plu'\
                'sMinus=N&Position=&Rank=N&RookieYear=&Season=2014-15&Seas'\
                'onSegment=&SeasonType=Regular+Season&TeamID=0&VsConferenc'\
                'e=&VsDivision=&mode=Advanced&showDetails=0&showShots=1&sh'\
                'owZones=0'


# In[4]:


# Get the webpage containing the data
response = requests.get(shot_chart_url)
# Grab the headers to be used as column headers for our DataFrame
headers = response.json()['resultSets'][0]['headers']
# Grab the shot chart data
shots = response.json()['resultSets'][0]['rowSet']


# In[5]:


shot_df = pd.DataFrame(shots, columns=headers)
# View the head of the DataFrame and all its columns
from IPython.display import display
with pd.option_context('display.max_columns', None):
    display(shot_df.head())


# In[6]:


sns.set_style("white")
sns.set_color_codes()
plt.figure(figsize=(12,11))
plt.scatter(shot_df.LOC_X, shot_df.LOC_Y)
plt.show()