What is Pandas Cumsum()?

What is Pandas Cumsum()?

The cumsum() function in Pandas is used to compute the cumulative sum of the values in a column or series. The cumulative sum is the sum of all the values in a series up to that point, including the current value.

For example, if the series is [1, 2, 3, 4, 5], the cumulative sum at each point would be [1, 3, 6, 10, 15].

Here's an example of using the cumsum() function in Pandas:

import pandas as pd

# create a sample series
s = pd.Series([1, 2, 3, 4, 5])

# compute the cumulative sum of the series
s_cumsum = s.cumsum()

# display the result
print(s_cumsum)

This will compute the cumulative sum of the series and return a new series with the same index as the original series.

The output will be:

0     1
1     3
2     6
3    10
4    15
dtype: int64

You can also use the cumsum() function on a dataframe to compute the cumulative sum of the values in one or more columns. For example:

# create a sample dataframe
df = pd.DataFrame({"A": [1, 2, 3, 4, 5],
                   "B": [2, 3, 4, 5, 6],
                   "C": [3, 4, 5, 6, 7]})

# compute the cumulative sum of the A and B columns
df_cumsum = df[["A", "B"]].cumsum()

# display the result
print(df_cumsum)

This will compute the cumulative sum of the A and B columns in the dataframe and return a new dataframe with the same index as the original dataframe. The output will be:

    A   B
0   1   2
1   3   5
2   6   9
3  10  14
4  15  20

As you can see, the cumsum() function is useful for computing the cumulative sum of a series or dataframe, which can be useful for a variety of analysis and visualization tasks.