Select Pandas dataframe rows between two dates

import modules

import pandas as pd
import numpy as np

create dummy dataframe

raw_data = {'name': ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'],
'age': [20, 19, 22, 21],
'favorite_color': ['blue', 'red', 'yellow', "green"],
'grade': [88, 92, 95, 70],
'birth_date': ['01-02-1996', '08-05-1997', '04-28-1996', '12-16-1995']}
df = pd.DataFrame(raw_data, index = ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'])
df

	age	birth_date	favorite_color	grade	name
Willard Morris	20	01-02-1996	blue	88	Willard Morris
Al Jennings	19	08-05-1997	red	92	Al Jennings
Omar Mullins	22	04-28-1996	yellow	95	Omar Mullins
Spencer McDaniel	21	12-16-1995	green	70	Spencer McDaniel

Select Pandas dataframe rows between two dates

We can perform this using a boolean mask First, lets ensure the 'birth_date' column is in date format

df['birth_date'] = pd.to_datetime(df['birth_date'])

next, set the desired start date and end date to filter df with -- these can be in datetime (numpy and pandas), timestamp, or string format

start_date = '03-01-1996'
end_date = '06-01-1997'

next, set the mask -- we can then apply this to the df to filter it

mask = (df['birth_date'] > start_date) & (df['birth_date'] <= end_date)

assign mask to df to return the rows with birth_date between our specified start/end dates

df = df.loc[mask]
df

	age	birth_date	favorite_color	grade	name
Omar Mullins	22	1996-04-28	yellow	95	Omar Mullins