compare_wins_shots.py

# Generate linear fit and chart 1
slope, intercept, r_value, p_value, std_err = stats.linregress(
    seasonal_df['rebound_ratio'], seasonal_df['win'])
line = slope * seasonal_df['rebound_ratio'].values + intercept

ch1_data = go.Scatter(
    x=seasonal_df['rebound_ratio'].values,
    y=seasonal_df['win'].values,
    mode='markers',
    marker=go.Marker(color='rgb(255, 127, 14)'),
    name='Data')

ch1_fit = go.Scatter(
    x=seasonal_df['rebound_ratio'].values,
    y=line,
    mode='lines',
    marker=go.Marker(color='rgb(31, 119, 180)'),
    name='Fit')

# Generate linear fit and chart 2
slope, intercept, r_value, p_value, std_err = stats.linregress(
    seasonal_df['rebound_ratio'], seasonal_df['shots'])
line = slope * seasonal_df['rebound_ratio'].values + intercept

ch2_data = go.Scatter(
    x=seasonal_df['rebound_ratio'].values,
    y=seasonal_df['shots'].values,
    mode='markers',
    marker=go.Marker(color='rgb(255, 127, 14)'),
    name='Data',
    xaxis='x2',
    yaxis='y2')

ch2_fit = go.Scatter(
    x=seasonal_df['rebound_ratio'].values,
    y=line,
    mode='lines',
    marker=go.Marker(color='rgb(31, 119, 180)'),
    name='Fit',
    xaxis='x2',
    yaxis='y2')

# Generate linear fit and chart 3
slope, intercept, r_value, p_value, std_err = stats.linregress(
    seasonal_df['shots'], seasonal_df['win'])
line = slope * seasonal_df['shots'].values + intercept

ch3_data = go.Scatter(
    x=seasonal_df['shots'].values,
    y=seasonal_df['win'].values,
    mode='markers',
    marker=go.Marker(color='rgb(255, 127, 14)'),
    name='Data',
    xaxis='x3',
    yaxis='y3')

ch3_fit = go.Scatter(
    x=seasonal_df['shots'].values,
    y=line,
    mode='lines',
    marker=go.Marker(color='rgb(31, 119, 180)'),
    name='Fit',
    xaxis='x3',
    yaxis='y3')

#Set Figure
fig = tools.make_subplots(
    rows=1,
    cols=3,
    subplot_titles=('Rebounds Rate vs Wins', 'Rebound Rate vs Shots ',
                    'Shots vs Wins'),
    horizontal_spacing=0.1)
fig.append_trace(ch1_data, 1, 1)  #rebs predicting wins
fig.append_trace(ch1_fit, 1, 1)

fig.append_trace(ch2_data, 1, 2)  #rebs predicting shots
fig.append_trace(ch2_fit, 1, 2)

fig.append_trace(ch3_data, 1, 3)  #shots predicting wins
fig.append_trace(ch3_fit, 1, 3)

#Set Axis
fig['layout']['xaxis'].update(title='Ratio of Shots Leading to Rebounds')
fig['layout']['xaxis2'].update(title='Ratio of Shots Leading to Rebounds')
fig['layout']['xaxis3'].update(title='Number of Shots')

fig['layout']['yaxis'].update(title='Number of Wins')
fig['layout']['yaxis2'].update(title='Number of Shots')
fig['layout']['yaxis3'].update(title='Number of Wins')

fig['layout'].update(
    height=400,
    width=1000,
    title=None,
    showlegend=False,
)

iplot(fig)