pandas 按索引分组并计算总和 [英] Pandas group by index and calculate sum

问题描述

我有以下数据框:

Node  Type       
0     InData         2944.516970
      InInterests    3703.208935
1     InData         6207.580040
      InInterests    3505.068411
2     InData         8133.002730
      InInterests    3735.028306
3     InData         9426.704710
      InInterests    2665.989291
4     InData         2604.157800
      InInterests    3103.310729
5     InData         6784.829160
      InInterests    3293.815375
6     InData         6823.617400
      InInterests    4121.833980
7     InData         4072.702770
      InInterests    3033.609368
8     InData         4614.608240
      InInterests    2955.216811
9     InData         6986.500750
      InInterests    2986.820394
Name: KilobytesRaw, dtype: float64

我想计算InData和InInterests的总和，但是在熊猫

I want to compute the sum of InData and InInterests, but couldn't find this case in the Pandas indexing page, nor on Google. So my I want my dataframe to look like this

Node         
0     mean         2944.516970
1     mean         6207.580040
...
9     mean         8133.002730

有人可以帮忙吗?

推荐答案

使用df.groupby(level=0).sum()

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