AfroQuant
Work with data. Understand the code.
Practical help using R and Python for data preparation, statistical analysis, visualisation, troubleshooting and reproducible workflows.
Areas of support
R and RStudio
- Data preparation and transformation
- Descriptive and exploratory analysis
- Data visualisation with ggplot2
- Hypothesis testing
- Correlation and regression analysis
- Exploratory and confirmatory factor analysis (EFA and CFA)
- Structural equation modelling (SEM) with lavaan
- Mediation and path analysis
- Troubleshooting and debugging code
- Reproducible analysis
Python
- Importing data from CSV, Excel and APIs
- Data cleaning and transformation
- Merging, grouping and reshaping datasets
- Exploratory data analysis
- Data visualisation with Matplotlib and Seaborn
- Hypothesis testing with SciPy
- Linear and logistic regression
- Troubleshooting and debugging code
- Readable, reproducible code