/Data-Science-Blog-Post

This is the repository for project Data Science Blog Post, a part of the Data Science Nanodegree Program by Udacity.

Primary LanguageJupyter Notebook

Data-Science-Blog-Post

This is the repository for project Data Science Blog Post, a part of the Data Scientist Nanodegree Program by Udacity.

  1. Project Overview
  2. Libraries
  3. Files
  4. Results
  5. References

1. Project Overview

The aim of this project is to build a model for classifies disaster messages. The dataset collected by Figure Eight. The disaster response dataset contains 30,000 messages, It has been encoded with 36 different categories related to disaster response and has been stripped of messages with sensitive information in their entirety.

2. Libraries

  • Python versions 3.*.
  • Python Libraries:
    • pandas
    • numpy
    • matplotlib
    • seaborn
    • plotly

5. Files 

- analysis
|- .ipynb_checkpoints
|- COVID-19 Report.ipynb
|- COVID-19 Report.html
- datasources
|- novel-corona-virus-2019-dataset
| |- covid_19_data.csv
| |- COVID19_line_list_data.csv
| |- COVID19_open_line_list.csv
| |- time_series_covid_19_confirmed.csv
| |- time_series_covid_19_confirmed_US.csv
| |- time_series_covid_19_deaths.csv
| |- time_series_covid_19_deaths_US.csv
| |- time_series_covid_19_recovered.csv
- images
|- image-0
|- image-1
|- image-2
|- image-3
|- image-4
|- image-5
- results
|- COVID-19 Report.html
- README.md

4. Results

The result of the analysis is presented in this post Status Breakdown of COVID-19 Pandemic Cases.

5. References

I wish to thank Kaggle and JHU CSSE for the Novel Coronavirus (COVID-19) Cases dataset. Also, thanks for Udacity for advice.