📅 2023-03-09 — Session: Enhanced Data Visualization and Cleaning Techniques

🕒 17:40–18:10
🏷️ Labels: Python, Data Visualization, Data Cleaning, Geospatial Analysis
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance data visualization and cleaning techniques using Python, focusing on geospatial analysis, data cleaning, and conditional formatting.

Key Activities

  • Mapping Violence Data in Africa: Utilized matplotlib and geopandas to plot a map of Africa with violence data points.
  • Identifying Non-Integer Values: Employed pandas to detect and handle non-integer values in a DataFrame.
  • Replacing NaN Values: Used numpy to replace NaN values in arrays and convert data types.
  • Highlighting DataFrame Cells: Implemented conditional formatting in pandas to highlight cells based on a threshold.

Achievements

  • Successfully plotted geospatial data on a map of Africa.
  • Enhanced data cleaning processes by identifying and handling non-integer and NaN values.
  • Improved data visualization by applying conditional formatting to DataFrames.

Pending Tasks

  • Further exploration of resources for researching violent conflicts in Algeria, including databases like UCDP and ACLED.