调整大 pandas 数据帧的一部分 [英] Transposing part of a pandas dataframe

问题描述

我有以下数据框：

 >>> df 
输出[15]：
组类型数量
 0 group_A购买100 123 
 1 group_A视图0 111 
 2 group_B视图0 222 
 3 group_A view 0 222 
  

我想转载数据，以便我最终得到： p>

  type group_A group_B 
 0 amount buy 100 0 
 1 number buy 0 123 
 2 number view 333 222 
  

如何实现？

解决方案

使用

  df = pd.DataFrame（[['group_A' '买''，100,123]，['group_A'，'view'，0,111]，['group_B'，'view'，0,222]，['group_A'，'view'，0,222]]，columns = ['group' ，'type'，'amount'，'number']）
  

首先总结指标和方向：

 >>> df = df.groupby（['type'，'group']）。sum（）.transpose（）。stack（0）.reset_index（）
>>> df 
 group level_0 type group_A group_B 
 0 amount buy 100 NaN 
 1 amount view 0 0 
 2 number buy 123 NaN 
 3 number view 333 222 
  

删除全部为零的行：

  df = df [〜（（df ['group_A'] == 0）|（df ['group_B'] == 0））] 
  pre> 
 
 
 Fillna's：
 >>> df.fillna（0）
 group level_0 type group_A group_B 
 0 amount buy 100 0 
 2 number buy 123 0 
 3 number view 333 222 
  
在这里有几个猜测，但应该给你一个开始。
 
I have the following dataframe:
>>> df
Out[15]: 
      group   type  amount  number
0   group_A    buy     100     123
1   group_A   view       0     111
2   group_B   view       0     222
3   group_A   view       0     222 
I'd like to pivot the data so that I end up with:
              type  group_A   group_B
0    amount    buy      100         0
1    number    buy        0       123
2    number   view      333       222
How do I accomplish this?
解决方案
Using:
df=pd.DataFrame([['group_A','buy',100,123],['group_A','view',0,111],['group_B','view',0,222],['group_A','view',0,222]],columns=['group','type','amount','number'])
First sum the indices and orientate:
>>> df = df.groupby(['type','group']).sum().transpose().stack(0).reset_index()
>>> df
group level_0  type  group_A  group_B
0      amount   buy      100      NaN
1      amount  view        0        0
2      number   buy      123      NaN
3      number  view      333      222
Drop rows that are all zero:
df = df[~((df['group_A']==0) | (df['group_B']==0))]
Fillna's:
>>> df.fillna(0)
group level_0  type  group_A  group_B
0      amount   buy      100        0
2      number   buy      123        0
3      number  view      333      222
Somewhat guessing in a few place here, but it should give you a start.

                        
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