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Summary Python Data Operations 5: Group and Pivot Tables $8.04   Add to cart

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Summary Python Data Operations 5: Group and Pivot Tables

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Summarised notes of Pandas data operations covered in the Principles of Programming course, part of the Computer Science and AI bachelor degree. The notes are initially written in Jupyter Notebook. They contain practical examples of data operations in python and images to explain the structures and...

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  • Basic data operations
  • December 9, 2022
  • 6
  • 2022/2023
  • Summary

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By: haidarihalim • 1 year ago

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Python Data Operations 5: Group and Pivot Tables
(Using the numpy and pandas packages imported in section one.)

This fith section contains:

Groupby

Iterate through groups
Basic groupings
Advanced groupings
Group with more levels
Pivot table
Stack and Unstack


# creating test dataframe
test_df = pd.DataFrame(
[['A3', 0, -1, 0, 'si'],
['B1', 1, None, 0, 'no'],
['B3', 4, None, 0, 'no'],
['B3', 5, 1, 0, 'si'],
['A1', 4, 0, None, None],
['A3', 1, 2, 1, 'si'],
['C2', 4, 1, 1, 'no']],
columns=['Assignment', 'UserId', 'Score', 'PrevAttempts', 'Exempted'],
index=[f'R{i}' for i in range(7)]
)
test_df


Assignment UserId Score PrevAttempts Exempted

R0 A3 0 -1.0 0.0 si

R1 B1 1 NaN 0.0 no

R2 B3 4 NaN 0.0 no

R3 B3 5 1.0 0.0 si

R4 A1 4 0.0 NaN None

R5 A3 1 2.0 1.0 si

R6 C2 4 1.0 1.0 no




Groupby
The .groupby method divides the records/rows of a table in different groups, generally to
later apply certain operations separately to each group.

A grouping has two phases:

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