Pandas中一列的累积和 - Python
使用预定义函数cumsum()可以轻松计算 Pandas 中列的累积总和。
Syntax: cumsum(axis=None, skipna=True, *args, **kwargs)
Parameters:
axis: {index (0), columns (1)}
skipna: Exclude NA/null values. If an entire row/column is NA, the result will be NA
Returns: Cumulative sum of the column
示例 1:
Python3
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))
Python3
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))
Python3
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 1 5
1 5 3 8
2 13 7 17
3 27 10 19
示例 2:
Python3
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:
Python3
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