Checking Date Order in a Column Using Pandas

Last update on April 09 2025 12:55:07 (UTC/GMT +8 hours)

14. Checking Consistent Date Order in a Column

Write a Pandas program to check consistent date order in a column.

Note: Chronological order is a way that follows the order in which a series of events happened.

This exercise demonstrates how to validate that dates in a column are in chronological order.

Sample Solution :

Code :

import pandas as pd
# Create a sample DataFrame with dates
df = pd.DataFrame({
    'Event': ['Start', 'Middle', 'End'],
    'Date': ['2020-01-01', '2020-01-15', '2020-01-10']
})

# Convert the 'Date' column to datetime
df['Date'] = pd.to_datetime(df['Date'], errors='coerce')

# Check if the dates are in chronological order
chronological_order = df['Date'].is_monotonic_increasing

# Output the result
print(f"Are the dates in chronological order? {chronological_order}")

Output:

Are the dates in chronological order? False

Explanation:

• Created a DataFrame with date strings.
• Converted the 'Date' column to datetime format using to_datetime().
• Used is_monotonic_increasing to check if the dates are in chronological order.

For more Practice: Solve these Related Problems:

• Write a Pandas program to verify that dates in a column are in chronological order and report any disorder.
• Write a Pandas program to check for gaps in a date column and output the missing date ranges.
• Write a Pandas program to validate that a date column is sorted and, if not, sort it while preserving original row indices.
• Write a Pandas program to compare two date columns and ensure that one consistently precedes the other, flagging any exceptions.

Python-Pandas Code Editor:

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