OyeTimmy/Nigeria-Covid-19-Data-Analysis

Covid-19 Nigerian Data Analysis # Covid-19 Nigeria Data Analysis Ustacky Capstone Project Analysis of the Novel Covid-19 data in Nigeria using pandas analytics # Project Steps - Web scraping from NCDC website - Manipulation and Exploration of Dataset using pandas - Manipulation of data types to the appropriate data types. - Manipulation of data using Pandas melt - Extraction of Unique values of data from the pool of raw data - Filtering, joining and Aggregation of Data - Data Visualization using seaborn # Insights From our analysis, we observed that Age and Population have been highly implicated as a risk factor in the infection and spread of the disease. Furthermore, the South Western region seem to be affected the most which in part could be due to its population while the Northern parts appear to have less cases in comparison, perhaps due to under-reporting or insufficient awareness. # Future Work In the coming days, I would like to explore how the recommendations implemented from this data has improved the prevention and control of the disease and also explore the effectiveness of the strategies currently being put in place such as vaccination, nose cover, social distancing etc. # Standout Section Apart from the instructions in the starter notebook, I was able to: - Use the pyplot to observe the regions that are most and least affected. - I was able to use drop column and manipulate the index to drop multi-line indexes. # Executive Summary. To-Do - Include your Executive Summary document in your repository.