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# Cumulative sum of a column in Pandas – Python

• Last Updated : 26 Jul, 2020

Cumulative sum of a column in Pandas can be easily calculated with the use of a pre-defined function cumsum()

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

Example 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``))`

Output:

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

Example 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``))`

Output:

```      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
```

Example 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``))`

Output:

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

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