Pandas Data Cleaning and Preprocessing: Exercises, Solutions with Explanation

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Pandas Data Cleaning and Preprocessing [15 exercises with solution]

More exercises focused on cleaning and preprocessing data, including dealing with outliers, duplicates, and data normalization.

1. Write a Pandas program to fill missing values (NaN) in a DataFrame using fillna().
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2. Write a Pandas program to drop rows with missing data.
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3. Write a Pandas program to detect duplicates using duplicated() method.
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4. Write a Pandas program to remove duplicates rows from a DataFrame.
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5. Write a Pandas program to handle outliers in a DataFrame with Z-Score method.
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6. Write a Pandas program that normalizes data with Min-Max scaling.
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7. Write a Pandas program to bin data into categories.
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8. Write a Pandas program that handles text data with str.replace().
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9. Write a Pandas program to convert data types using astype().
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10. Write a Pandas program to remove leading and trailing whitespace using str.strip().
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11. Write a Pandas program to change column names to lowercase.
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12. Write a Pandas program to replacing missing data with mean value.
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13. Write a Pandas program to remove columns with too many missing values.
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14. Write a Pandas program to reorder columns in a DataFrame.
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15. Write a Pandas program to split a column into multiple columns.
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