SQL and DataFrame Analysis for Educational Data

📅 2025-05-01 — Session: SQL and DataFrame Analysis for Educational Data

🕒 00:00–00:40
🏷️ Labels: SQL, Dataframe, Python, Data Analysis, Visualization, Education
📂 Project: Teaching
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to analyze educational data using SQL queries and DataFrames in Python, focusing on the aggregation of educational institutions and their populations by province and department.

Key Activities

• Identified and resolved a ValueError in the DataFrame ee_df_clean_sim due to column length discrepancies.
• Developed SQL queries to aggregate educational data, focusing on the number of institutions and populations.
• Corrected SQL syntax errors using pandasql and ensured clean execution of queries.
• Addressed column ambiguity errors in SQL joins by using unique aliases.
• Created a generic wrapper function for graphing in Python using matplotlib and seaborn.
• Constructed and analyzed various DataFrames, including ee_vs_pop_df, to visualize educational data.

Achievements

• Successfully executed SQL queries to merge and analyze educational data by department.
• Developed functions to generate educational data visualizations using Seaborn.
• Constructed and cleaned DataFrames for further analysis and visualization.

Pending Tasks

• Confirm reconstruction of the DataFrame bp_df_clean or await new data loading.

Session Context

This session involved extensive data analysis using SQL and Python, focusing on educational data aggregation and visualization. The session was productive, resolving key errors and enhancing data visualization capabilities.