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LinkedIn Learning

pandas Code Challenges

via LinkedIn Learning

Overview

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Test your pandas knowledge with this edition of Code Challenges.

Syllabus

Introduction
  • Stretch and test your knowledge with pandas code challenges
  • What you should know
1. Reading and Initial Exploration of Data
  • Read data from CSV and Excel files
  • Check DataFrame information and identify types of columns
  • The summary statistics of numerical and categorical features
  • Add new columns to a DataFrame
2. Indexing and Slicing
  • Select specific columns in a DataFrame
  • Subset the data from labels using .loc[] method
  • Subset the data from indexing using .iloc[] method
3. Data Cleaning
  • Check for missing values
  • Correct the data type of a column
  • Parse dates in time series data
4. Filtering Data
  • Write conditional statements to filter rows
  • Chain multiple conditionals to narrow down the search
  • Using bitwise operators to filter rows
  • Filtering to find target demography
5. Grouping and Aggregation
  • Apply the three-step process to group and aggregate data
  • Group and aggregate multiple columns
  • Apply a custom aggregate function
  • Calculate stock returns for every year since 2003

Taught by

Harshit Tyagi

Reviews

4.8 rating at LinkedIn Learning based on 125 ratings

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