# Python | Pandas Series.cumsum() to find cumulative sum of a Series

Pandas ** Series.cumsum()** is used to find Cumulative sum of a series. In cumulative sum, the length of returned series is same as input and every element is equal to sum of all previous elements.

Syntax:Series.cumsum(axis=None, skipna=True)

Parameters:axis:0 or ‘index’ for row wise operation and 1 or ‘columns’ for column wise operationskipna:Skips NaN addition for elements after the very next one if True.

Result type:Series

**Example #1:**

In this example, a series is created from a Python list using Pandas .Series() method. The list also contains a Null value and the skipna parameter is kept default, that is True.

`# importing pandas module` `import` `pandas as pd` ` ` `# importing numpy module` `import` `numpy as np` ` ` `# making list of values` `values ` `=` `[` `3` `, ` `4` `, np.nan, ` `7` `, ` `2` `, ` `0` `]` ` ` `# making series from list` `series ` `=` `pd.Series(values)` ` ` `# calling method` `cumsum ` `=` `series.cumsum()` ` ` `# display` `cumsum` |

**Output:**

3 7 NaN 14 16 16 dtype: float64

**Explanation**

Cumulative sum is sum of current and all previous values. As shown in above output, the addition was done as follows

3 3+4 = 7 7+NaN = NaN 7+7 = 14 14+2 = 16 16+0 = 16

**Example #2: **skipna=False

In this example, a series is created just like in the above example. But the `skipna `

parameter is kept False. Hence NULL values won’t be ignored and it would be added every time after it’s occurrence.

`# importing pandas module` `import` `pandas as pd` ` ` `# importing numpy module` `import` `numpy as np` ` ` `# making list of values` `values ` `=` `[` `1` `, ` `20` `, ` `13` `, np.nan, ` `0` `, ` `1` `, ` `5` `, ` `23` `]` ` ` `# making series from list` `series ` `=` `pd.Series(values)` ` ` `# calling method` `cumsum ` `=` `series.cumsum(skipna ` `=` `False` `)` ` ` `# display` `cumsum` |

**Output:**

0 1.0 1 21.0 2 34.0 3 NaN 4 NaN 5 NaN 6 NaN 7 NaN dtype: float64

**Explanation: **As it can be seen in output, all the values after first occurrence of NaN are also NaN since any number + NaN is also NaN.

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