并排条形图 [英] Side by Side BarPlot

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本文介绍了并排条形图的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试使用 seabornpandas 创建这种并排"条形图.

这是我创建数据框的方式:

dfs = pd.DataFrame(data={'investors': ['first','second','third'], 'stocks': [23, 123, 54], 'bonds': [54, 67, 123], '房地产': [45, 243, 23]})

这是条形图代码:

sns.factorplot(x='investors', y='bonds', data=dfs, kind='bar')

有人可以帮忙吗?谢谢

解决方案

使用

I'm trying to create this kind of "side by side" barplot with seaborn and pandas.

this is how I create data frame:

dfs = pd.DataFrame(data={'investors': ['first','second','third'], 'stocks': [23, 123, 54], 'bonds': [54, 67, 123], 'real estate': [45, 243, 23]})

And here is barplot code:

sns.factorplot(x='investors', y='bonds', data=dfs, kind='bar')

Can anyone please help? Thanks

解决方案

Use melt on your dateframe then plot it with seaborn.

update: factorplot was changed to catplot in newer versions of seaborn.

sns.catplot(x = 'investors', y='value', 
            hue = 'investments',data=dfs1, 
            kind='bar')


# import libraries
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd

dfs = pd.DataFrame(data={'investors': ['first','second','third'], 
                         'stocks': [23, 123, 54], 
                         'bonds': [54, 67, 123], 
                         'real estate': [45, 243, 23]})

dfs1 = pd.melt(dfs, id_vars = "investors")

print(dfs1)

    investors    investments    value
0   first         stocks         23
1   second        stocks        123
2   third         stocks         54
3   first          bonds         54
4   second         bonds         67
5   third          bonds        123
6   first      real estate       45
7   second     real estate      243
8   third      real estate       23


sns.factorplot(x = 'investors', y='value', 
               hue = 'investments',data=dfs1, kind='bar')
plt.show()

output :-

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