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Pakistan COVID-19 Exploratory Data Analysis

  • This analysis will illustrate 3 Months Analysis from July 11, 2020 to October 11, 2020.
  • Python libraries; Numpy and Pandas are used for this analysis.
  • And lastly, Seaborn and Matplotlib libraries are used for the visualisation of this analysis.

How it works?

  • A real-world COVID dataset have been used for this analysis,
    downloaded from: https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_daily_reports
  • Two separate CSV files have been used, containing July and October data, respectively.
  • Then specifically extracted and cleansed Pakistan's data from it, and made a separate CSV file for easy access.
  • Then plotted data regarding Confirmed, Active, Death and Recovered Cases overall the country.
  • And lastly, plotted data regarding Confirmed, Active, Death and Recovered Cases, region wise.

Source Code

  • Numpy: A python library used for working with arrays. It also has functions for working in domain of linear algebra, fourier transform, and matrices.
  • Pandas: A python library that provides high-performance, easy to use structures and data analysis tools. It also provides in-memory 2D table object called Dataframe.
  • Matplotlib: A comprehensive library for creating static, animated, and interactive visualizations in Python.
  • Seaborn: A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.
import numpy as np 
import pandas as pd
import matplotlib.pyplot as plt 
import seaborn as sns

Real-world datasets