Week 4 - Data Processing with Pandas

Introduction to Pandas

DataFrame operations

Grouping and Aggregation

Joining and Merging

Different Data Types

Advanced Transformations

Writing Data

Alternatives to Pandas

Practice

Assignment

Gotchas & Pitfalls

• Teachers

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1. Introduction to Pandas and DataFrames

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Suggested Topics

• What is Pandas: a data manipulation library built on NumPy
• DataFrames: the core structure for tabular data (rows and columns)
• Series: one-dimensional labeled arrays (columns in a DataFrame)
• Index: row labels and their importance for data alignment
• Creating DataFrames: from dicts, lists, CSV files, databases
• Selecting data: column selection, filtering rows, loc/iloc
• Inspecting data: shape, dtypes, head/tail, describe, info
• Dealing with missing data: NaN values, fillna, dropna
• Data types: inferring vs specifying types
• Basic operations: arithmetic, string methods on columns

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