Python Pandas: Plotting 100% stacked graph issue

Question

I got a dataframe df5 with the following table which I read in from read_csv,

Week_Days,Category,Total_Products_Sold,Total_Profit
0.Monday,A,3221,9999.53
0.Monday,B,1038,26070.33
0.Monday,C,699,13779.56
0.Monday,E,3055,18157.26
0.Monday,F,47569,215868.15
0.Monday,G,2348,23695.25
0.Monday,H,6,57
0.Monday,I,14033,64594.24
0.Monday,J,13876,47890.91
0.Monday,K,3878,14119.74
0.Monday,L,243,2649.6
0.Monday,M,2992,16757.38
1.Tuesday,A,2839,8864.78
1.Tuesday,B,1013,26254.69
1.Tuesday,C,656,13206.98
1.Tuesday,E,2696,15872.45
1.Tuesday,F,43039,197621.18
1.Tuesday,G,2107,21048.72
1.Tuesday,H,3,17
1.Tuesday,I,12297,56942.99
1.Tuesday,J,12095,40724.2
1.Tuesday,K,3418,12551.26
1.Tuesday,L,243,2520.3
1.Tuesday,M,2375,13268.28
2.Wednesday,A,2936,9119.93
2.Wednesday,B,1061,26927.86
2.Wednesday,C,634,10424.05
2.Wednesday,E,2835,16627.35
2.Wednesday,F,46128,218014.59
2.Wednesday,G,1986,19173.64
4.Friday,H,24,233
4.Friday,I,17576,81648.75
4.Friday,J,16468,55820.9
4.Friday,K,4294,16603.39
4.Friday,L,440,4258.51
4.Friday,M,3600,20142.44
5.Saturday,A,4658,15051.13
5.Saturday,B,1492,38236.07
5.Saturday,C,1057,15449.7
5.Saturday,E,5335,29904.96
5.Saturday,F,79925,362120.61
5.Saturday,G,4324,44088.79
5.Saturday,H,26,933
5.Saturday,I,22688,106313.86
5.Saturday,J,21882,74725.11
5.Saturday,K,5402,20875.84
5.Saturday,L,458,4692.84
5.Saturday,M,4896,27769.68
6.Sunday,A,3429,11310.1
6.Sunday,B,1104,27282.99
6.Sunday,C,1051,11567.08
6.Sunday,E,3913,22740.63
6.Sunday,F,56048,259105.03
6.Sunday,G,3224,32528.39
6.Sunday,H,21,749
6.Sunday,I,15853,74876.77
6.Sunday,J,16072,55259.76
6.Sunday,K,4383,16058.36
6.Sunday,L,327,3348.82
6.Sunday,M,3551,20814.05

I want to plot 2 100% stacked bar charts for Total Products Sold and Total Profit each, where the x-axis is Week Days and the labels are the different Categories.

My code for Total Products Sold is

df5 = df5.set_index(['Week_Days', 'Category'])
df5 = df5.div(df5.sum(1), axis=0)
ax = df5[['Total_Products_Sold']].plot(kind='bar', stacked=True, width = 0.3, figsize=(20, 10), colormap="RdBu")
patches, labels = ax.get_legend_handles_labels()
ax.legend(bbox_to_anchor=(1.1, 1.0))
ax.set_xlabel('Week Days')
ax.set_ylabel('Products Sold')

The graph I got returned looks nothing I need. It is not 100 stacked and the legend is Total Products Sold and not the different categories in Category.

Can someone please help? Thanks.

Regards, Lobbie

Answer 1

The easiest way is to make a pivot table with the values you care about. Try something like this:

tps = df5.pivot_table(values=['Total_Products_Sold'], 
                      index='Week_Days',
                      columns='Category',
                      aggfunc='sum')

tps = tps.div(tps.sum(1), axis=0)
tps.plot(kind='bar', stacked=True)

For me this produces the following:

You can do the same thing for Total_Profit separately.