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Understanding Pandas DataFrames: A Complete Guide with Real-World Examples
A beginner-friendly guide to Pandas DataFrames that covers essential data manipulation techniques using real-world Toyota sales data examples. The article progresses from basic concepts like loading a
nd inspecting data to more advanced operations like handling missing values and data transformation.

Reasons to Read -- Learn:

  • how to practically work with real-world datasets using Pandas, including specific methods for loading, inspecting, and analyzing Toyota sales data with concrete code examples.
  • how to identify and handle missing values in datasets, as demonstrated with the discovery of 1,274 missing values in the commission_pct column out of 5,000 records in the Toyota dataset.
  • essential DataFrame manipulation techniques, including how to create new columns, transform existing data (like converting text to uppercase), and perform basic statistical analysis using methods like .describe().
    • 4 min readauthor: Durga Gadiraju
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