In Python, the **`pandas` library** includes built-in functionalities that allow you to perform different tasks with only a few lines of code. One of these functionalities is *the creation of lags and leads of a column*.

- **`lag`** shifts a column down by a certain number.
- **`lead`** shifts a column up by a certain number.

# Method
In this method, we first initialize a `pandas` dataframe with a `numpy` array as input. Then we select a column and apply `lead` and `lag` by shifting that column up and down, respectively.

#importing pandas and numpy libraries
import pandas as pd
import numpy as np

#initializing pandas dataframe with numpy arrays
df = pd.DataFrame(np.random.randint(1, 100, 10).reshape(-1, 2), columns = list('ab'))

#applying leads and lags by shifting dataframe column up and down respectively
df['lag(a,1)'] = df['a'].shift(1)

df['lag(a,5)'] = df['a'].shift(5)

df['lead(b,2)'] = df['b'].shift(-2)

df['lead(b,4)'] = df['b'].shift(-4)

print(df)

How to create lags and leads of a column in a pandas DataFrame

Use pandas to shift a DataFrame column up or down, creating leads and lags easily.

ID	Leads 1	Lags 1
1	2	NaN
2	3	1
3	4	2
4	5	3
5	6	4
6	NaN	5

How to create lags and leads of a column in a pandas DataFrame

Input

Output

Method