The **`cumsum`** function in pandas returns a cumulative sum over a dataframe or series axis. 

The return series or dataframe is of the same size as the original one, except with the cumulative sum.

The illustration below shows how the `cumsum` function works in pandas:

# Syntax

The syntax of the `cumsum` function is as follows:

```python
Series.cumsum(axis=None, skipna=True, *args, **kwargs)
```

# Parameters

The table below describes each parameter of the `cumsum` function:

| Parameter  | Description  |
| - | - |
| `axis`  | The axis of the cumulative sum. `axis` takes a bool value. `0` refers to column-wise sum, whereas `1` refers to row-wise. By default, `axis` is `0`. |
| `skipna`  | Determines if null values need to be excluded or not. By default, `skipna` is `True`.  |
| `args`  | Additional keywords have no effect but might be accepted for compatibility with NumPy.  |
|`**kwargs`|Any additional arguments.|

> All parameters are optional.

# Return value

The `cumsum` function returns a series or dataframe with the cumulative sum at each index. The length of the return object is the same as the original series or dataframe.

# Example

The code snippet below shows how the `cumsum` function is used in pandas:

import pandas as pd
import numpy as np

s = pd.Series([2, np.nan, 5, -1, 0])
print("Original Series")
print(s)
print('\n')

print("Cumulative Sum-NA values are ignored by default")
print(s.cumsum())
print('\n')

print("If skip_na is False")
print(s.cumsum(skipna=False))
print('\n')

print("Original Dataframe")
df = pd.DataFrame([[2.0, 1.0], [3.0, np.nan], [1.0, 0.0]], columns=list('AB'))
print(df)
print('\n')

print("By default, cumulative sum")
print(df.cumsum())
print('\n')

print("Sum by Axis = 1 (row-wise)")
print(df.cumsum(axis=1))
print('\n')

Parameter	Description
`axis`	The axis of the cumulative sum. `axis` takes a bool value. `0` refers to column-wise sum, whereas `1` refers to row-wise. By default, `axis` is `0`.
`skipna`	Determines if null values need to be excluded or not. By default, `skipna` is `True`.
`args`	Additional keywords have no effect but might be accepted for compatibility with NumPy.
`**kwargs`	Any additional arguments.

What is the cumsum function in pandas?

Syntax

Parameters

Return value

Example