Validating date formats in a Pandas DataFrame
Pandas: Data Validation Exercise-9 with Solution
Write a Pandas program to validate date formats in a DataFrame.
The following exercise demonstrates how to validate that a column contains correctly formatted date values using to_datetime().
Sample Solution :
Code :
import pandas as pd
# Create a sample DataFrame with date strings
df = pd.DataFrame({
'Event': ['Conference', 'Meeting', 'Seminar'],
'Date': ['2020-05-01', '2020-06-15', 'Invalid-Date']
})
# Validate the 'Date' column by converting it to datetime
df['Valid_Date'] = pd.to_datetime(df['Date'], errors='coerce')
# Output the result
print(df)
Output:
Event Date Valid_Date 0 Conference 2020-05-01 2020-05-01 1 Meeting 2020-06-15 2020-06-15 2 Seminar Invalid-Date NaT
Explanation:
- Created a DataFrame with date strings, including an invalid date.
- Used to_datetime() to validate the 'Date' column, converting invalid dates to NaT.
- Displayed the DataFrame with a new 'Valid_Date' column that contains validated dates.
Python-Pandas Code Editor:
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