In [43]:

    

import pandas as pd
import scipy.stats as st 
import matplotlib.pyplot as plt
import numpy as np
df=pd.read_excel('survey2.xlsx')
print(df.columns)
Qs=['What kind(s) of Unit 1 work have you done? ','Which division(s) have you done Unit 1 work in?','I am a member of an equity-seeking group with respect to:']
Titles=['kinds_of_work','divisions','Equity']
names=[['TA','CI','CPO','AI','Access','TATP'],['Humanities','Socsci','Physsci','Lifesci','Indie'],['Gender','Sexual','Racial','Disability','Other','Prefer','None']]
A2=[['TA','CI','CPO','Invigilator','Invigilators','TATP'],['Humanities','Social','Physical','Life','Independent'],['Gender','Sexual','Racial','Disability','Other','Prefer','None']]


    

    




Index(['Timestamp',
       'Please choose your top 5 priority issues from the below list of financial issues:',
       'I would not even consider voting yes on the next Collective Agreement without progress on:',
       'Optional comments on financial priorities',
       'Please choose your top 5 priority issues from the below list of non-financial issues:',
       'I would not even consider voting yes on the next Collective Agreement without progress on:.1',
       'Optional comments on non-financial priorities', 'I am a...',
       'What kind(s) of Unit 1 work have you done? ',
       'What department(s) have you done Unit 1 work in?',
       'Which division(s) have you done Unit 1 work in?',
       'Which campus(es) have you done Unit 1 work at?',
       'I am a member of an equity-seeking group with respect to:'],
      dtype='object')

In [42]:

    

#print(df[df.columns[8]].value_counts())
for ii in range(0,len(Qs)):
    Q=Qs[ii]
    data=[]
    P=[]
    Pl=[]
    Pw=[]
    Pwl=[]
    height=0.35
    fig=plt.figure(figsize=(16,16),dpi=100)
    ax1=plt.subplot(211)
    ax2=plt.subplot(212)r
    for jj in range(0,len(A2[ii])):
        x=[]
        xw=[]
        A=A2[ii][jj]#As[ii][jj]
        df2=df[(df[Q].str.contains(A))]
        for kk in range(0,df2.shape[0]):
            x.extend(df2.iloc[kk][4].replace(', I',';I').replace(', A',';A').replace(', D',';D').replace(', P',';P').replace(', N',';N').split(';'))
        f=st.itemfreq(np.array(sorted(x,key=str.lower)))
        ylabels=f[:,0]
        ind = np.arange(len(ylabels)) 
        xw=np.array(f[:,1]).astype(float)/np.sum(np.array(f[:,1]).astype(float))
        x=np.array(f[:,1]).astype(float)#/np.sum(np.array(f[:,1]).astype(float))
        if jj==0:
            sw=np.zeros(np.shape(x))
            s=np.zeros(np.shape(x))
        P.append(ax1.barh(ind,x,height,left=s))
        Pl.append(P[jj][0])
        Pw.append(ax2.barh(ind,xw,height,left=sw))
        Pwl.append(Pw[jj][0])
        sw+=xw
        s+=x
    ax1.legend(Pl,(names[ii]))
    ax1.set_yticks(ind)
    ax1.set_yticklabels(ylabels)
    ax2.legend(Pwl,(names[ii]))
    ax2.set_yticks(ind)
    ax2.set_yticklabels(ylabels)
    plt.gcf().subplots_adjust(left=.5)
    fig.savefig(Titles[ii]+'_non.png')
#    plt.show()


    

In [41]:

    

#print(df[df.columns[8]].value_counts())
for ii in range(0,len(Qs)):
    Q=Qs[ii]
    data=[]
    P=[]
    Pl=[]
    Pw=[]
    Pwl=[]
    height=0.35
    fig=plt.figure(figsize=(16,16),dpi=100)
    ax1=plt.subplot(211)
    ax2=plt.subplot(212)
    for jj in range(0,len(A2[ii])):
        x=[]
        xw=[]
        A=A2[ii][jj]#As[ii][jj]
        df2=df[(df[Q].str.contains(A))]
        for kk in range(0,df2.shape[0]):
            x.extend(df2.iloc[kk][1].replace(', I',';I').replace(', Crea',';Crea').replace(', Red',';Red').split(';'))
        f=st.itemfreq(np.array(sorted(x,key=str.lower)))
        ylabels=f[:,0]
        ind = np.arange(len(ylabels)) 
        xw=np.array(f[:,1]).astype(float)/np.sum(np.array(f[:,1]).astype(float))
        x=np.array(f[:,1]).astype(float)#/np.sum(np.array(f[:,1]).astype(float))
        if jj==0:
            sw=np.zeros(np.shape(x))
            s=np.zeros(np.shape(x))
        P.append(ax1.barh(ind,x,height,left=s))
        Pl.append(P[jj][0])
        Pw.append(ax2.barh(ind,xw,height,left=sw))
        Pwl.append(Pw[jj][0])
        sw+=xw
        s+=x
    ax1.legend(Pl,(names[ii]))
    ax1.set_yticks(ind)
    ax1.set_yticklabels(ylabels)
    ax2.legend(Pwl,(names[ii]))
    ax2.set_yticks(ind)
    ax2.set_yticklabels(ylabels)
    plt.gcf().subplots_adjust(left=.5)
    fig.savefig(Titles[ii]+'_fin.png')
#    plt.show()