ai-dataset-and-tools / covid-19

Performing Exploratory Data Analysis on COVID-19 Dataset and display the results by plotting of various types such as the plot of Worldwide Cases- confirmed, deaths, recovered and analysis by country. • After performing EDA, the cleaning and preprocessing of the dataset to make predictions using the ML technique(LightGBM, which is a gradient boosting framework that uses tree-based learning algorithms).

COVID-19

COVID-19 Context From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, we do not know how it affects people.

So daily level information on the affected people can give some interesting insights when it is made available to the broader data science community.

Johns Hopkins University has made an excellent dashboard using the affected cases data. Data is extracted from the google sheets associated and made available here.

Edited: Now data is available as csv files in the Johns Hopkins Github repository. Please refer to the github repository for the Terms of Use details. Uploading it here for using it in Kaggle kernels and getting insights from the broader DS community.

Content 2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.

The data is available from 22 Jan, 2020.

Column Description Main file in this dataset is covid_19_data.csv and the detailed descriptions are below.

covid_19_data.csv

Sno - Serial number ObservationDate - Date of the observation in MM/DD/YYYY Province/State - Province or state of the observation (Could be empty when missing) Country/Region - Country of observation Last Update - Time in UTC at which the row is updated for the given province or country. (Not standardised and so please clean before using it) Confirmed - Cumulative number of confirmed cases till that date Deaths - Cumulative number of of deaths till that date Recovered - Cumulative number of recovered cases till that date 2019_ncov_data.csv

This is older file and is not being updated now. Please use the covid_19_data.csv file