DataFrame.shift() - ( Pandas DataFrame Basics )

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Syntax

DataFrame.shift(periods=1, freq=None, axis=0, fill_value=None)

Example

import pandas as pd

df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]})

df_shifted = df.shift(periods=1)

print(df_shifted)

Output

     a    b
0  NaN  NaN
1  1.0  4.0
2  2.0  5.0

Explanation

DataFrame.shift() is a Pandas function that shifts the index by a specified number of periods. This can be useful for time-series data or for comparing data with previous or future time points.

The function shifts the index values and optionally fills any gaps with a specified value. By default, the shift is applied along the row axis (axis=0), but it can also be applied along the column axis (axis=1).

In the above example, we create a simple Pandas DataFrame with two columns and then use df.shift(periods=1) to shift the index values down by one period. This produces a new DataFrame with the same columns, but with the first row containing NaN values.

Use

The DataFrame.shift() function is useful for analyzing time-series data or comparing data at different time points. By shifting the index values by a specified number of periods, we can compare data at previous or future time points and observe trends or changes over time.

Important Points

• DataFrame.shift() is a Pandas function that shifts the index by a specified number of periods
• The shift can be applied along the row axis (axis=0) or the column axis (axis=1)
• The function optionally fills any gaps with a specified value

Summary

In conclusion, DataFrame.shift() is a useful function in Pandas for analyzing time-series data and comparing data at different time points. By shifting the index values by a specified number of periods, we can observe trends and changes over time and make comparisons with previous or future time points.