Syntax error How does the pandas series.expanding() method work?

How does the pandas series.expanding() method work?

The series.expanding() method is one of the window methods of pandas and it Provides expanding transformations. And it returns a window subclassed for the particular operation.

The parameters for this method are min_periods, center, axis, and method. The default value for the min_periods is 1 and it also takes an integer value. The center parameter takes a boolean value and the default one is False. In the same way, the default value for the axis parameter is 0, and for the method is ‘single’.

Example 1

In this following example, the series.expanding() method calculated the cumulative sum of the entire series object

# importing packages
import pandas as pd
import numpy as np

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

# apply expanding method
result = s.expanding().sum()
print("Result:")
print(result)

Explanation

Initially, we have created a series object using a list of integers.

Output

The output is as follows −

0    1
1    2
2    3
3    4
4    5
dtype: int64

Result:
0     1.0
1     3.0
2     6.0
3    10.0
4    15.0
dtype: float64

The series.expanding() method successfully calculated the cumulative sum of series elements using the sum() function.

Example 2

Here we will calculate the cumulative mean of entire series elements using series.expanding() method and mean function.

# importing packages
import pandas as pd
import numpy as np

# create a series
s = pd.Series([1,3, 5, np.nan, 7, 9])
print(s)

# apply expanding method
result = s.expanding().mean()
print("Result:")
print(result)

Output

The output is given below −

0    1.0
1    3.0
2    5.0
3    NaN
4    7.0
5    9.0
dtype: float64

Result:
0    1.0
1    2.0
2    3.0
3    3.0
4    4.0
5    5.0
dtype: float64

The series.expanding() method calculates the cumulative average of entire series elements and the missing values are replaced by the previous value.

Updated on: 2022-03-07T07:43:15+05:30

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