Question

我想从同一行（轴= 1）的前一列值中减去当前列值，除了第一列值

My Dataframe:

   A   B  C  D
0  5  11  4  5
1  3   2  3  4
2  6   4  8  2
3  4   3  5  8

Expected Dataframe:

   A   B  C  D
0  5   6 -2  7
1  3  -1  4  0
2  6  -2  10 12
3  4  -1  6  2

Answer 1

似乎没有cum-diff内置函数

for x, y  in enumerate(df.columns):
    if x ==0 : 
        df[y]=df[y]
    else : 
        df[y]=df[y]-df[df.columns[x-1]]

df
Out[494]: 
   A  B   C  D
0  5  6  -2  7
1  3 -1   4  0
2  6 -2  10 -8
3  4 -1   6  2

def cumdiff(df,axis):
    if axis==1 :
        for x, y in enumerate(df.columns):
            if x == 0:
                df[y] = df[y]
            else:
                df[y] = df[y] - df[df.columns[x - 1]]
        return df
    else : 
        for x, y in enumerate(df.index):
            if x == 0:
                df[y] = df[y]
            else:
                df[y] = df[y] - df[df.columns[x - 1]]
        return df

cumdiff(df,axis=1)
Out[501]: 
   A  B   C  D
0  5  6  -2  7
1  3 -1   4  0
2  6 -2  10 -8
3  4 -1   6  2

Answer 2

您只需使用 pandas.DataFrame.expanding 和 reduce function 即可。所以你的代码可以是这样的：

import pandas as pd
from functools import reduce

data =  [[5,  11,  4,  5],
         [3,   2,  3,  4],
         [6,   4,  8,  2],
         [4,   3,  5,  8]]

df = pd.DataFrame(data=data, columns=['A','B','C','D'])

print(df)
>>>   A   B  C  D
   0  5  11  4  5
   1  3   2  3  4
   2  6   4  8  2
   3  4   3  5  8

diff_df = df.expanding(axis=1).apply(lambda x: reduce(lambda a,b : b-a,x)).astype(int)

print(diff_df)
>>>   A  B   C  D
   0  5  6  -2  7
   1  3 -1   4  0
   2  6 -2  10 -8
   3  4 -1   6  2

从熊猫数据框中同一行的上一列中减去当前列值

2 个答案: