Mastering advanced indexing and slicing in Pandas DataFrames

Last update on December 21 2024 07:41:01 (UTC/GMT +8 hours)

Pandas Advanced Indexing and Slicing [15 exercises with solution]

Advanced techniques for indexing, slicing, and selecting data in DataFrames, including multi-level indexing (MultiIndex). Practice with the following comprehensive exercises.

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1. Write a Pandas program to select rows where the value in the 'A' column is greater than 4.
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2. Write a Pandas program to select only the 'X' and 'Y' columns from the DataFrame.
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3. Write a Pandas program to set a MultiIndex and access specific data using it.
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4. Write a Pandas program to slice DataFrame based on MultiIndex levels.
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5. Write a Pandas program to swap the levels of a MultiIndex DataFrame.
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6. Write a Pandas program to reset the index of a MultiIndex DataFrame.
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7. Write a Pandas program that uses .loc for indexing.
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8. Write a Pandas program to use Boolean indexing to select rows where column 'x' > 6.
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9. Write a Pandas program to select the first three rows using iloc.
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10. Write a Pandas program to use .loc to select rows based on a condition
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11. Write a Pandas program that uses .loc to set values in the DataFrame.
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12. Write a Pandas program that uses .loc to slice DataFrame based on row and column labels.
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13. Write a Pandas program to select rows where column 'X' > 5 and column 'Y' < 5.
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14. Write a Pandas program that uses .loc to slice a MultiIndex DataFrame.
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15. Write a Pandas program that uses MultiIndex to select data based on conditions.
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