Python Pandas:绘制100％堆叠图问题 [英] Python Pandas: Plotting 100% stacked graph issue

问题描述

我从下表读取了从read_csv中读取的数据帧df5，

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

我想绘制2个100％堆叠的条形图，分别表示已售出的产品总数和利润总额，其中x轴是工作日，标签是不同的类别.

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.

我的总销售商品代码为

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')

我返回的图形看起来不需要任何东西.它不是100叠，图例是已售产品总数"，而不是类别"中的不同类别.

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.

有人可以帮忙吗?谢谢.

Can someone please help? Thanks.

关于， 罗比

推荐答案

最简单的方法是使用所需的值制作数据透视表.尝试这样的事情:

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)

对我来说，这产生了以下内容:

For me this produces the following:

您可以分别为Total_Profit做同样的事情.

You can do the same thing for Total_Profit separately.

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