Pandas中某一列的累积总和 – Python

在Pandas中，通过使用预定义的函数cumsum()，可以很容易地计算出一列的累积总和。

语法: cumsum(axis=None, skipna=True, *args, **kwargs)

参数:
axis：{指数（0），列（1）}。
skipna: 排除NA/null值。如果整个行/列是NA，结果将是NA

示例 1:

import pandas as pd
import numpy as np
  
# Create a dataframe
df1 = pd.DataFrame({"A":[2, 3, 8, 14], 
                   "B":[1, 2, 4, 3], 
                   "C":[5, 3, 9,2]}) 
  
# Computing sum over Index axis
print(df1.cumsum(axis = 0))

输出:

    A   B   C
0   2   1   5
1   5   3   8
2  13   7  17
3  27  10  19

示例 2:

import pandas as pd
import numpy as np
  
# Create a dataframe
df1 = pd.DataFrame({"A":[None, 3, 8, 14], 
                   "B":[1, None, 4, 3], 
                   "C":[5, 3, 9,None]}) 
  
# Computing sum over Index axis
print(df1.cumsum(axis = 0, skipna = True))

输出:

      A    B     C
0   NaN  1.0   5.0
1   3.0  NaN   8.0
2  11.0  5.0  17.0
3  25.0  8.0   NaN

示例 3:

import pandas as pd
import numpy as np
  
# Create a dataframe
df1 = pd.DataFrame({"A":[2, 3, 8, 14], 
                   "B":[1, 2, 4, 3], 
                   "C":[5, 3, 9,2]}) 
  
# Computing sum over Index axis
print(df1.cumsum(axis = 1))

输出:

    A   B   C
0   2   3   8
1   3   5   8
2   8  12  21
3  14  17  19