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Python | Pandas dataframe.cumsum()
  • Last Updated : 16 Nov, 2018

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Pandas dataframe.cumsum() is used to find the cumulative sum value over any axis. Each cell is populated with the cumulative sum of the values seen so far.

Syntax: DataFrame.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: cumsum : Series



Example #1: Use cumsum() function to find the cumulative sum of the values along the index axis.




# importing pandas as pd
import pandas as pd
  
# Creating the dataframe
df = pd.DataFrame({"A":[5, 3, 6, 4],
                   "B":[11, 2, 4, 3],
                   "C":[4, 3, 8, 5],
                   "D":[5, 4, 2, 8]})
  
# Print the dataframe
df

Output :

Now find the cumulative sum of the values over the index axis




# To find the cumulative sum
df.cumsum(axis = 0)

Output :

 

Example #2: Use cumsum() function to find the cumulative sum of the values seen so far along the column axis.




# importing pandas as pd
import pandas as pd
  
# Creating the dataframe
df = pd.DataFrame({"A":[5, 3, 6, 4],
                   "B":[11, 2, 4, 3],
                   "C":[4, 3, 8, 5],
                   "D":[5, 4, 2, 8]})
  
# To find the cumulative sum along column axis
df.cumsum(axis = 1)

Output :

 

Example #3: Use cumsum() function to find the cumulative sum of the values seen so far along the index axis in a data frame with NaN value present in dataframe.




# importing pandas as pd
import pandas as pd
  
# Creating the dataframe
df = pd.DataFrame({"A":[5, 3, None, 4],
                   "B":[None, 2, 4, 3],
                   "C":[4, 3, 8, 5],
                   "D":[5, 4, 2, None]})
  
# To find the cumulative sum
df.cumsum(axis = 0, skipna = True)

Output :

The output is a dataframe with cells containing the cumulative sum of the values seen so far along the index axis. Any Nan value in the dataframe is skipped.

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