ML-CaPsule/COVID_19-DATA-ANALYSIS at master · akshaydubey05/ML-CaPsule

Name		Name	Last commit message	Last commit date
parent directory ..
Covid19_State_wise_Visualizations.ipynb		Covid19_State_wise_Visualizations.ipynb
Covid19_italy.ipynb		Covid19_italy.ipynb
Covid_19_Data_Analysis(SUYASH).ipynb		Covid_19_Data_Analysis(SUYASH).ipynb
README.md		README.md
Timeline analysis of Covid 19.ipynb		Timeline analysis of Covid 19.ipynb
covid.csv		covid.csv
covid19_Confirmed_dataset.csv		covid19_Confirmed_dataset.csv
covid19_data_analysis_in_python2.ipynb		covid19_data_analysis_in_python2.ipynb
covid19_italy_region.csv		covid19_italy_region.csv
state_wise_daily.csv		state_wise_daily.csv
worldwide_happiness_report.csv		worldwide_happiness_report.csv

README.md

                                            # COVID_19-DATA-ANALYSIS

This project aims to solve daily cases as statewise analysis , covid19 daily cases in India ,Italy.

      Dataset :

Dataset used can be take through repository.

Go to other sheets and check for 'state_wise_daily','covid' sheet name.

   Setup Instruction:

Prerequisites Experience with jupyter notebook or google colab.

Knowledge of following is recomended:

pandas

matplotlib

seaborn

numpy

plotly

     Steps followed

Step 1. Data Preprocessing.

Step 2. Data visualization of previous data available.

Step 3. Many more

     Conclusion

Number of recovered cases are high as compared to deceased cases, which shows that recovery rate for covid19 cases in India is very good.

India might see a third wave but not as sharp and hard as the second one.

To avoid third wave we all should follow all necessary precautions and keep safe.