将列设置为列索引 pandas 数据框 [英] Set a column as Column Index Pandas Dataframe
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问题描述
假设我拥有此数据集,并用于分析每个州城乡地区男女识字率之间的趋势.我需要将索引设置为
Name
我可以做的- df.set_index('Name',inplace = True)
现在我想将我的数据分为 Rural和Urban
并期望输出为-
我该如何实现?
我尝试使用 groupby
Literacy_States = Literacy_States.groupby(['Name','TRU'])['M_LIT','F_LIT'].count().unstack('TRU').plot.bar()
但是输出是:
解决方案
您可以在这里查看: Matplotlib条形图,显示了x值对于男性和女性
您将拥有:农村和城市,而不是男性和女性.
Let's say I have this data set and for analysing the trends between male and female literacy across rural and urban region of every state . I need to set index as Name
Which I can do as -
df.set_index('Name',inplace=True)
Now I want to segregate my data into Rural and Urban
And expect the ouput as -
How can I acheive this ?
EDIT: I tried doing it using groupby
Literacy_States=Literacy_States.groupby(['Name','TRU'])['M_LIT','F_LIT'].count().unstack('TRU').plot.bar()
But ouput is :
解决方案
You can have a look here: Matplotlib bar chart that displays the x values for male and females
Instead of Male and Females, you have: Rural and Urban.
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