Polars: Up & Running!

Welcome to Polars: Up & Running!

Welcome to your journey with Polars - the lightning-fast DataFrame library that will transform how you work with data!

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We've loaded some weather data for you to experiment with. Try this:
print(weather_df)

Course Structure:
1. Getting Started
   - Your first Polars DataFrame
   - Basic operations and syntax
   - Understanding Series and DataFrames

2. Core Concepts
   - Working with columns
   - Filtering and selection
   - Grouping and aggregation
   - The power of expressions

3. Performance Features
   - Lazy evaluation
   - Parallel processing
   - Memory efficiency
   - Best practices

4. Real-World Applications
   - Data cleaning
   - Time series operations
   - Complex transformations
   - Integration with other tools

The weather_df DataFrame contains daily temperature and weather conditions for different cities.
Try these commands:

# View the first few rows
print(weather_df.head())

# Get basic information about the DataFrame
print(weather_df.describe())

# Select specific columns
print(weather_df.select(['city', 'temperature']))