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 operation skipna: 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. Python3

# 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. Python3 1==

# 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.