Developed advanced correlation functions in Pandas

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📅 2023-10-23 — Session: Developed advanced correlation functions in Pandas

🕒 22:10–23:45
🏷️ Labels: Python, Pandas, Data Analysis, Correlation, Time Series
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The goal of this session was to enhance data analysis capabilities by developing advanced correlation functions using the Pandas library in Python.

Key Activities

  • Developed a function to compute correlations of a specified column with all other columns in a Pandas DataFrame.
  • Implemented a MultiIndex approach to organize correlation results more effectively.
  • Explored the use of the min_periods parameter to ensure correlations are calculated only with a minimum number of valid observations.
  • Addressed handling of missing values in correlation calculations, ensuring accurate results by considering only non-missing data.
  • Created a function to calculate correlations between a focal time series and other time series, incorporating thresholds for filtering results.

Achievements

  • Successfully implemented multiple Python functions to calculate correlations in various contexts, including handling missing values and using MultiIndex for better result organization.

Pending Tasks

  • Further testing and validation of the developed functions with larger datasets to ensure performance and accuracy.
  • Integration of these functions into larger data analysis workflows for practical application.

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