Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus, and it has affected major parts of the world. Nigeria, a West-African country, has also been affected by the COVID-19 pandemic after recording its first case on 27th February 2020.
Nigeria is a country with 37 states - Federal Capital Territory included- and a fast-growing economic environment with about 200 million citizens. COVID-19 has affected several country activities as the country steadily progressed from its first case to shutting down major airports, state-wide lockdown, curfews, and reviving its economy.
After importing all required libraries, dataset were collected from The Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) repository using the Urlib.request since the NCDC COVID-19 official website could not be accessed. These dataset include:
# Global Daily Confirmed Cases
# Global Daily Recovered Cases
# Global Daily Death Cases
# covid_external.csv
# Budget data.csv
# RealGDP.csv
Data were cleaned by dropping columns with a null value and zero value, removing commas from numerical values.
Data were also converted to appropriate datatypes.
Nigeria data was extracted from the world COVID-19 record for analysis.
The dataframe was transposed to give it a better presentation
Pandas DataFrame for Daily Confirmed, Recovered and deaths Cases were gotten.
A bar plot that shows the Top 10 states in terms of Confirmed Covid (Laboratory test ) cases, discharged, and death cases were generated.
A line plot for the total daily confirmed, recovered, and death cases in Nigeria were each generated.
The daily infection rate was determined to show the derivate of the total cases on a bar plot
The daily confirmed, recovered, and death cases datasets were combined and viewed on a bar chart.
The daily infection rate was determined and plotted on a line graph.
The maximum infection rate for a day was calculated signifying the number of new cases and the date found was identified.
The relationship between the external dataset and the NCDC COVID-19 dataset was determined based on the top 10 confirmed cases versus the overall community vulnerability index as well as the least 10 cases by merging the two datasets on a common column (states) and plotting their result on the same axis of a line plot.
A regression plot between two variables (Confirmed Cases and Population Density) was generated to visualize their linear relationships.
A pie chart was generated to visualize the proportion/percentage of confirmed cases per region within the country.
The percentage difference between the pre-covid_19 and the covid_19 Q2 was determined.
The state with the highest and lowest initial and revised budget was determined, also the percentage difference between the initial budget and the revised budget was determined. All these were added on to the original dataset and plotted on a bar plot.
The global covid_19 dataset consists of 289 rows and 1144 valid columns while Nigeria's data consist of 1 row and 506 valid columns.
Lagos has the most confirmed cases in Nigeria with 26708 cases while Delta state has the least cases with 1843 cases.
Lagos has the most discharged cases in Nigeria with 24037 cases while Delta state has the least cases with 1737 cases.
Lagos has the most death cases in Nigeria (236 cases) while Delta state has the least cases (36 cases).
It was observed that there were very few death cases in Nigeria.
Maximum daily infection was observed to be 6158.0 and the date it occurred was observed to be 2021-12-22.
The top 10 and least 10 confirmed cases versus the overall community vulnerability index merge show that the Overall CCVI Index in these states is very low, which means that the impact of the virus on these communities after the virus arrives is low.
Analysis of the real GDP data shows that the GDP dropped from 413801074.72 Pre-Covid_19 to 15890000.0 during Q2 2020, a %change of 96%. A visualization was also presented.
Lagos state has the highest initial and revised budget, Yobe state has the lowest initial budget while Nasarawa state has the lowest revised budget.