Debugged NaN values in Afrobarometer data

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📅 2023-09-24 — Session: Debugged NaN values in Afrobarometer data

🕒 00:15–00:35
🏷️ Labels: Data_Processing, Nan, Afrobarometer, Python, Pandas
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary goal of this session was to identify and resolve NaN values in the datetime column of Afrobarometer datasets, and to implement a robust data processing pipeline using both R and Python.

Key Activities

  • Debugged NaN values in the Afrobarometer dataset, focusing on the datetime column.
  • Developed a systematic approach to load data and create a comprehensive covariate data frame.
  • Implemented a Python script using pandas to read and process multiple CSV files, mirroring an R implementation.
  • Addressed mixed date-time formats in pandas DataFrame using infer_datetime_format in pd.to_datetime.
  • Fixed date parsing errors in pandas by using ‘format=“mixed”‘.
  • Drafted an email update on the Afrobarometer dataset’s null values.

Achievements

  • Successfully identified and proposed solutions for handling NaN values and mixed date-time formats in the dataset.
  • Created a dual implementation in R and Python for data processing tasks.

Pending Tasks

  • Finalize and send the email update regarding the Afrobarometer dataset’s null values.

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