Pandas Data Validation: Exercises and Solutions for Data Integrity

Last update on December 21 2024 07:41:18 (UTC/GMT +8 hours)

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Pandas Data Validation [15 exercises with solution]

Exercises on validating data integrity, including checking for constraints, validating data types, and ensuring data consistency.

1. Write a Pandas program to check for missing values in a DataFrame.
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2. Write a Pandas program to check and ensure that the data types of all columns are consistent.
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3. Write a Pandas program to validate the data type of a specific column in a DataFrame.
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4. Write a Pandas program to check duplicate rows in a DataFrame.
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5. Write a Pandas program to remove duplicate rows from a DataFrame.
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6. Write a Pandas program to validate data based on custom conditions.
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7. Write a Pandas program to check that a specific column contains only unique values.
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8. Write a Pandas program to detect outliers in a DataFrame.
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9. Write a Pandas program to validate date formats in a DataFrame.
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10. Write a Pandas program that ensures no missing values in a critical column.
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11. Write a Pandas program that validates string length in a DataFrame column.
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12. Write a Pandas program to verify numeric range in a DataFrame column.
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13. Write a Pandas program that validates the format of email addresses.
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14. Write a Pandas program to check consistent date order in a column.
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15. Write a Pandas program that ensures no negative values in a DataFrame column.
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Do not submit any solution of the above exercises at here, if you want to contribute go to the appropriate exercise page.

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