Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/robinmillford/india-s-covid-19-journey-a-case-study-analysis
In this extensive project, I embarked on a profound exploration of India's journey through the COVID-19 pandemic. This endeavor involved a multi-faceted approach, encompassing data preprocessing with Python, data analysis with SQL queries, and data visualization using Power BI.
https://github.com/robinmillford/india-s-covid-19-journey-a-case-study-analysis
covid-19 data-analysis data-cleaning-and-preprocessing data-visualization jupyter-notebook powerbi pythin3 sql
Last synced: about 11 hours ago
JSON representation
In this extensive project, I embarked on a profound exploration of India's journey through the COVID-19 pandemic. This endeavor involved a multi-faceted approach, encompassing data preprocessing with Python, data analysis with SQL queries, and data visualization using Power BI.
- Host: GitHub
- URL: https://github.com/robinmillford/india-s-covid-19-journey-a-case-study-analysis
- Owner: RobinMillford
- Created: 2023-10-02T06:26:07.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-10-02T07:06:02.000Z (about 1 year ago)
- Last Synced: 2023-10-03T10:50:00.160Z (about 1 year ago)
- Topics: covid-19, data-analysis, data-cleaning-and-preprocessing, data-visualization, jupyter-notebook, powerbi, pythin3, sql
- Language: Jupyter Notebook
- Homepage:
- Size: 13.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
Awesome Lists containing this project
README
# India's COVID-19 Journey: A Case Study Analysis
In this extensive project, I embarked on a profound exploration of India's journey through the COVID-19 pandemic. This endeavor involved a multi-faceted approach, encompassing data preprocessing with Python, data analysis with SQL queries, and data visualization using Power BI. The project aimed to extract valuable insights from available datasets, providing a holistic view of India's response to the pandemic.
### Data Cleaning and Python Data Manipulation
The project commenced with a critical step: data cleaning. Recognizing the importance of data quality, I meticulously renamed columns within the datasets to ensure uniformity and clarity. Additionally, Python played a vital role in data cleaning and manipulation. Python code was employed to perform various tasks, ensuring that the datasets were primed for in-depth analysis.
### Data Analysis with SQL
The core of this project involved data analysis through SQL queries. These queries were meticulously crafted to address specific problem statements and extract meaningful insights. Here's a closer look at the key areas explored:
### 1. COVID-19 Recovery Rate Analysis
I quantified the recovery rate among Indian states, extracting the number of recovered and active cases from the 'statewisedata' table. This analysis shed light on how effectively different regions were managing the pandemic.
### 2. Hospital Bed Availability Assessment
Hospital bed availability was a critical concern during the pandemic. By analyzing the 'hospitalbeds' table, I assessed the availability of hospital beds in various states. This involved evaluating both the total population beds and the number of beds available, contributing to informed decision-making regarding healthcare infrastructure.
### 3. Testing Statistics Exploration
The 'icmrtestingdata' table provided valuable insights into India's testing efforts. I calculated the total number of samples tested, the total number of positive cases, and the difference between them. This analysis offered a comprehensive view of the testing landscape in the country.
### Data Visualization with Power BI
To enhance the project's impact and accessibility, data visualization was conducted using Power BI. The visualizations served as a dynamic means to communicate insights effectively. These interactive visual representations allowed stakeholders and decision-makers to explore the data intuitively, gaining a deeper understanding of India's COVID-19 journey.
Dashboard 1 - 
Dashboard 2 - 
Dashboard 3 - 
Dashboard 4 - 
### Conclusion
This project signifies a comprehensive analysis of India's response to the COVID-19 pandemic. The combined use of Python, SQL, and Power BI empowered the extraction of valuable insights from the datasets. These insights can be instrumental in policy-making, healthcare resource allocation, and pandemic management.
By leveraging the strengths of data preprocessing, SQL analysis, and data visualization, this project provides a comprehensive case study of India's COVID-19 situation. It underscores the significance of data-driven decision-making in tackling complex global challenges.