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+import pandas as pd%0A%0Asubway_df = pd.read_csv('nyc_subway_weather.csv')%0A%0A%0Adef correlation(x, y):%0A    '''%0A    computes correlation between two%0A    variables.%0A    '''%0A    x_std = (x - x.mean()) / x.std(ddof=0)%0A    y_std = (y - y.mean()) / y.std(ddof=0)%0A%0A    correl = (x_std * y_std).mean()%0A    return correl%0A%0A%0A%0Aif __name__ == %22__main__%22:%0A%0A    entries = subway_df%5B'ENTRIESn_hourly'%5D%0A    cumulative_entries = subway_df%5B'ENTRIESn'%5D%0A    rain = subway_df%5B'meanprecipi'%5D%0A    temp = subway_df%5B'meantempi'%5D%0A%0A    print correlation(entries, rain)%0A    print correlation(entries, temp)%0A    print correlation(rain, temp)%0A    print correlation(entries, cumcumulative_entries)%0A

Create correlation.py