Manipulating Time Series Data in Python

The Korshub Take

This intermediate Python course details core operations for cleaning, transforming, and analyzing time-indexed data with pandas. You will learn to navigate datetime indices, change sample frequencies, and construct rolling financial metrics.

Who It's For

Data analysts and financial researchers who want to manipulate and aggregate time series data using Python's pandas library.

Key Takeaways

• Pandas Datetime Indexing: Use built-in pandas methods for filtering, slicing, and manipulating temporal data.
• Resampling & Frequency Shift: Resample time series datasets to alter sampling frequency and calculate rolling or cumulative statistics.
• Financial Index Construction: Apply your skills to construct a value-weighted stock index using real stock market data.