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#!pip install seaborn


    

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import numpy as np 
import pandas as pd 
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
%matplotlib inline


    

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filename= "../data/kobe/kobe_bryant_shot_data.csv.gz"
df = pd.read_csv(filename, na_values={'shot_made_flag': ''})


    

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df.head()


    

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df.columns


    

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df.shot_made_flag.value_counts(dropna=False)


    

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df = df.dropna()


    

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df['team_name'].head()


    

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df['team_name'].unique()


    

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df['combined_shot_type'].head()


    

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df['combined_shot_type'].value_counts()


    

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df['combined_shot_type'].value_counts().plot(kind='bar', figsize=(8, 4), rot=0)


    

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df.plot(kind='scatter', x='loc_x', y='loc_y', color='blue', alpha=0.02, figsize=(5,10))


    

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ranges = df.shot_zone_range.unique()

cmap = {range_name:color for range_name, color in zip(ranges, sns.color_palette(n_colors=len(ranges)))}

df.plot(kind='scatter', x='loc_x', y='loc_y', alpha=0.03, figsize=(5,10),
    c=df.shot_zone_range.map(cmap))


    

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zones = df.shot_zone_area.unique()
cmap = {zone_name:color for zone_name, color in zip(zones, sns.color_palette(n_colors=len(zones)))}

df.plot(kind='scatter', x='loc_x', y='loc_y', alpha=0.03, figsize=(5,10),
    c=df.shot_zone_area.map(cmap))


    

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