COVID-19 (Coronavirus) Data Analysis and Data Visualization


Turan S., Yağanoğlu M.

International Online Conferences On Engineering and Natural Sciences, Gümüşhane, Turkey, 5 - 07 July 2021, vol.1, no.1, pp.324, (Summary Text)

  • Publication Type: Conference Paper / Summary Text
  • Volume: 1
  • City: Gümüşhane
  • Country: Turkey
  • Page Numbers: pp.324
  • Erzincan Binali Yildirim University Affiliated: No

Abstract

COVID-19 disease, which turned into a pandemic, was first seen in Wuhan, China on December 31, 2019. With the spread of the virus, the first case was seen in Turkey on March 11, 2020. The aim of this study is to analyze the 2020 coronavirus datasets with data science steps using the Python programming language on the Anaconda Navigator, and to provide a correct understanding of the COVID-19 epidemic worldwide, mathematical analyzes and visualization results were obtained. "Pandas, numpy, matplotlib, seaborn" libraries were used in analysis and visualization processes. The data used consists of KCDC (Korea Disease Control and Prevention Centers), which quickly and transparently announces COVID-19 information, and 2243 data sets containing patient information structured based on local governments' report materials (22/01/2020 - 04/03/2020). In the data set we used in the study; Cleaning out the outlier, correcting the noise data, eliminating the inconsistencies, filling missing values, ignoring the data, not processing it, filling the missing fields automatically and performing the data processing stages, meaningful results were obtained from the data sets and visualized.