This repository contains the jupyter notebooks and the original data, which represents 40% of the module rubric. Jupyter Notebooks, Python, Pandas, Matplotlib and Seaborne (data visualisation libraries), were all self taught.
- Clean a publicly available dataset to faciliate future analysis.
- Produce the density and box plots
- Make work that others can make use of (top priority).
- Demonstrate problem solving
- Demonstrate perseverance and problem solving either for technical problems or in identifying new cleaning operations.
- Produce a pivot table and a scatterplot with a fitted trend line and highlight groups within the scatter plot based on another categorical column of data.
- Problem solving python, pandas, jupyter notebooks, matplotlib and seaborne issues, plus data cleaning problems.
- Draw conclusions from visualisations, including a density plot and a scatter plot.
- Derive valuable avenues to explore for future Data Analysts.