Implemented Pandas DataFrame Boolean Count Logic

📅 2023-04-25 — Session: Implemented Pandas DataFrame Boolean Count Logic

🕒 14:00–14:10
🏷️ Labels: Pandas, Data Analysis, Python, Dataframe, Boolean Logic
📂 Project: Dev
⭐ Priority: MEDIUM

The session aimed to implement efficient data analysis techniques using Pandas to count occurrences of boolean column values in a DataFrame.

Utilized the groupby method in Pandas to group data by boolean columns and count projects with scores above 0.5.
Created a DataFrame to store counts of projects with scores above 0.5 for specified boolean columns.
Updated code to replace the deprecated .append() method with pd.concat() for data aggregation.
Developed logic to count projects with scores above a threshold for columns starting with ‘ad_sector_names_’ or ‘mjsector_‘.
Calculated counts and percentages of projects with scores above and below 0.5 for specified boolean columns.

Successfully implemented a robust method to count and analyze boolean column data in Pandas.
Transitioned from using .append() to pd.concat() ensuring compatibility with future Pandas versions.

Further optimization of the code for performance improvements in large datasets.
Validation of results with real-world data to ensure accuracy.