📅 2023-10-17 — Session: Streamlined Data Analysis and Visualization Workflow
🕒 07:00–08:30
🏷️ Labels: Python, Data Analysis, Visualization, R Programming, Task Management
📂 Project: Dev
Session Goal: The session aimed to enhance the efficiency and effectiveness of data analysis and visualization processes using Python and R.
Key Activities:
- Provided guidance on time management strategies for task delivery.
- Collected task details to tailor assistance and improve task management.
- Developed a structured plan for data analysis, including creating a codebook and addressing R script issues.
- Prepared afrobarometer data and aggregated time series datasets.
- Simplified CSV processing with a Python script for loading files and generating statistics.
- Clarified steps for constructing histograms from datasets and addressed visualization preferences.
- Outlined a process for loading CSV data and creating stacked histograms using pandas and matplotlib.
- Enhanced [[data visualization]] code to include text information and value counts.
- Developed a data analysis script for Jupyter Notebook with structured code and markdown headings.
Achievements:
- Established a clear workflow for data preparation and visualization.
- Implemented Python scripts for efficient data processing and visualization.
- Enhanced understanding of histogram construction and [[data visualization]] techniques.
Pending Tasks:
- Further refinement of R scripts for data analysis.
- Integration of additional [[data visualization]] features as per user preferences.