Rewrite this code to calculate statistics by scipy.stats wilcoxon stat, p = mannwhitneyu(data[data['version'] == 'gate_30']['sum_gamerounds'], data[data['version'] == 'gate_40']['sum_gamerounds']) print('Mann-Whitney Statistics=%.3f, p=%.3f' % (stat, p))

from scipy.stats import mannwhitneyu
import numpy as np

def mann_whitney_plus_means(turnstile_weather):
    '''
    This function will consume the turnstile_weather dataframe containing
    our final turnstile weather data. 
    
    You will want to take the means and run the Mann Whitney U test on the 
    ENTRIESn_hourly column in the turnstile_weather dataframe.
    
    This function should return:
        1) the mean of entries with rain
        2) the mean of entries without rain
        3) the Mann-Whitney U statistic and p-value comparing the number of entries
           with rain and the number of entries without rain
    
    You should feel free to use scipy's Mann-Whitney implementation, and you 
    might also find it useful to use numpy's mean function.
    
    Here are the functions' documentation:
    http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.