Pandas DataFrame cumsum() Method
Example
Multiply the values for each row with the values from the previous row:
import pandas as pd
data = [[10, 18, 11], [13, 15, 8], [9, 20, 3]]
df = pd.DataFrame(data)
print(df.cumsum())
Try it Yourself »
Definition and Usage
The cumsum() method returns a DataFrame with
the cumulative sum for each row.
The cumsum() method goes through the values
in the DataFrame, from the top, row by row, adding the values with the value from the previous row, ending up with a DataFrame where the last row
contains the sum of all values for each column.
If the axis parameter is set to axes='columns',
the method goes through the values, column by column, and ends up with a
DataFrame where the last columns contains the sum of all values for each row.
Syntax
dataframe.cumsum(axis, skipna, args, kwargs)
Parameters
The
axis
and skipna parameters are
keyword arguments.
| Parameter | Value | Description |
|---|---|---|
| axis | 0 |
Optional, default 0, specifies the axis to run the accumulation over. |
| skip_na | True |
Optional, default True. Set to False if the result should NOT skip NULL values |
| args | Optional. These arguments has no effect, but could be accepted by a NumPy function | |
| kwargs | Optional, keyword arguments. These arguments has no effect, but could be accepted by a NumPy function |
Return Value
A DataFrame object.
This function does NOT make changes to the original DataFrame object.
