Python Pandas – Filter DataFrame between two dates

To filter DataFrame between two dates, use the dataframe.loc method. This allows you to select rows based on date conditions using boolean indexing.

Creating a DataFrame with Date Records

At first, import the required library and create a DataFrame with date columns ?

import pandas as pd

# Dictionary of lists with date records
d = {'Car': ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'],
     'Date_of_Purchase': ['2021-07-10', '2021-08-12', '2021-06-17', 
                          '2021-03-16', '2021-02-19', '2021-08-22']}

# Creating dataframe from the above dictionary of lists
dataFrame = pd.DataFrame(d)
print("DataFrame...")
print(dataFrame)

DataFrame...
       Car Date_of_Purchase
0      BMW        2021-07-10
1    Lexus        2021-08-12
2     Audi        2021-06-17
3 Mercedes        2021-03-16
4   Jaguar        2021-02-19
5  Bentley        2021-08-22

Filtering Between Two Dates

To filter cars purchased between two specific dates (2021-05-10 and 2021-08-25), use the loc method with boolean conditions ?

import pandas as pd

# Dictionary of lists with date records
d = {'Car': ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'],
     'Date_of_Purchase': ['2021-07-10', '2021-08-12', '2021-06-17', 
                          '2021-03-16', '2021-02-19', '2021-08-22']}

dataFrame = pd.DataFrame(d)

# Filter cars purchased between two dates
resDF = dataFrame.loc[(dataFrame["Date_of_Purchase"] >= "2021-05-10") & 
                      (dataFrame["Date_of_Purchase"] <= "2021-08-25")]

print("Cars purchased between 2021-05-10 and 2021-08-25:")
print(resDF)

Cars purchased between 2021-05-10 and 2021-08-25:
       Car Date_of_Purchase
0      BMW        2021-07-10
1    Lexus        2021-08-12
2     Audi        2021-06-17
5  Bentley        2021-08-22

How It Works

The filtering uses boolean indexing with these components:

• dataFrame["Date_of_Purchase"] >= "2021-05-10" ? Checks if date is greater than or equal to start date
• dataFrame["Date_of_Purchase"] ? Checks if date is less than or equal to end date
• & operator ? Combines both conditions (both must be True)
• dataFrame.loc[] ? Selects rows where the boolean condition is True

Alternative Methods

You can also use between() method for cleaner syntax ?

import pandas as pd

d = {'Car': ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'],
     'Date_of_Purchase': ['2021-07-10', '2021-08-12', '2021-06-17', 
                          '2021-03-16', '2021-02-19', '2021-08-22']}

dataFrame = pd.DataFrame(d)

# Using between() method
resDF = dataFrame[dataFrame["Date_of_Purchase"].between("2021-05-10", "2021-08-25")]
print("Using between() method:")
print(resDF)

Using between() method:
       Car Date_of_Purchase
0      BMW        2021-07-10
1    Lexus        2021-08-12
2     Audi        2021-06-17
5  Bentley        2021-08-22

Conclusion

Use dataFrame.loc[] with boolean conditions or between() method to filter DataFrame rows between two dates. The between() method provides cleaner syntax for date range filtering.