The study aims to add concept on the impact of the pandemic with respect to the cases recorded and their resultant deaths. Furthermore, the vulnerability index offers clear relationship between the pandemic and states performance in Nigeria

The study aims to add concept on the impact of the pandemic with respect to the cases recorded and their resultant deaths. Furthermore, the vulnerability index offers clear relationship between the pandemic and states performance in Nigeria

#Project Steps

Step 1: The appropriate libraries were imported and data was scraped from the Official NCDC Website

Libraries Imported

.matplotlib.pyplot .warnings .time .BeautifulSoup from bs4 .seaborn .requests .numpy .urllib.request .pandas .csv

Methods Used

.strip() .find_all() .append() .reshape() .read_html() .time() .get() .Find()

Attributes Used

.content Step 2: Data was extracted from the Josh Hopkins Data Repository

Methods Used

.read_csv()

Step 3: Data was extracted from external data sources

Methods Used

.read_csv()

Step 4: Data from Josh Hopkins Repository which contained global data was removed to Nigeria's data, columns was renamed from the NCDC data to another and special characters was removed from the numerical columns.

Methods Used

.apply() .drop() .rename() .melt() to_datetime()

Attributes Used

.columns

Step 5: Data Analyses is performed and visualizations is created.

Methods Used

.diff() .max() .idmax() .rename() .replace() .merge() .twinx() .corr() .nlargest() .color_palette() .set_context() .figure() .title() .xlabel & ylabel .xticks & yticks .abs() .plot_relation() .sum() .legend() .xlim & ylim .axhline() .max() .idmax() .rename() .replace() .merge() .twinx() .corr()

Attributes Used

.Date .index

Plots Created

.pointplot .heatmap .pie .regplot .barplot .lineplot

Expressions

.lambda expression

Presentation