padas.shift() what does it do in python

The pandas library is a powerful data manipulation and analysis tool in Python. The shift() function is used to shift the index of a DataFrame or a Series by a specified number of periods. It can be applied to both rows and columns.

Here's the syntax of the shift() function:

main.py
DataFrame.shift(periods=1, freq=None, axis=0, fill_value=None)
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• periods specifies the number of periods to shift. A positive value will shift the index forward, while a negative value will shift it backward. By default, it is set to 1.
• freq is an optional parameter that represents the time frequency of the data.
• axis determines whether the shift is applied to rows (axis=0) or columns (axis=1). By default, it is set to 0.
• fill_value is an optional parameter that determines the value to use for newly created missing values. By default, missing values are filled with NaN (Not a Number).

Here's an example usage of the shift() function on a DataFrame in pandas:

main.py
import pandas as pd

# Create a DataFrame
data = {'A': [1, 2, 3, 4, 5]}
df = pd.DataFrame(data)

# Shift the index forward by 2 periods
df_shifted = df.shift(periods=2)
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In the above example, the original DataFrame df has the values [1, 2, 3, 4, 5] in column 'A'. After applying df.shift(periods=2), the resulting DataFrame df_shifted will have the values [NaN, NaN, 1, 2, 3] in column 'A', where the first two values are filled with NaN as there are no values to shift backward.

Note that the shift() function does not modify the original DataFrame; it returns a new shifted DataFrame instead.