In this tutorial, we are going to analyze Covid-19 data using Python. We mainly use the Plotly and Matplotlib libraries for this work.
It works on the information related to the total confirmed cases, active cases, recovered cases, serious/critical cases, and death cases. In particular, we analyze data of top 20 countries' cases and plot information using treemap, pie chart, bar graph, and line graph.
The ratio between population and the total number of tests done is analyzed. In addition to this, the information relates to a particular country can also be obtained along with the date.
Title of the project:
Covid-19 Data Analysis using Python.
Description:
Hello everyone!
In this tutorial, we are going to analyze Covid-19 data using Python. We mainly use the Plotly and Matplotlib libraries for this work.
It works on the information related to the total confirmed cases, active cases, recovered cases, serious/critical cases, and death cases. In particular, we analyze data of top 20 countries' cases and plot information using treemap, pie chart, bar graph, and line graph.
The ratio between population and the total number of tests done is analyzed. In addition to this, the information relates to a particular country can also be obtained along with the date.
Prerequisites:
1) Dataset files of covid cases with a .csv extension.
2) Install Jupyter Notebook or any similar working environment with the latest version of Python installed.
3) Python language.
4) Knowledge of Python libraries like numpy, pandas, matplotlib.
Datasets:
It contains the datasets of-
i. worldometer data, (209, 16)
ii. country wise data, (187, 15)
iii. day wise data, (188, 12)
iv. combined data, (35156, 10)
Implementation:
Submitted by Madhulika Damor (damormadhu24)
Download packets of source code on Coders Packet
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