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https://github.com/zrkhadija/analyzing-parisian-associations-a-data-exploration-project
This project focuses on analyzing data about associations registered in Paris. Using an API, the data was fetched in JSON format and transformed into a pandas dataframe for exploration and analysis. The dataset includes details such as the statutory name, postal code, city of registration, sectors of activity, domains of activity..
https://github.com/zrkhadija/analyzing-parisian-associations-a-data-exploration-project
analysis data-visualization json-api paris
Last synced: about 1 month ago
JSON representation
This project focuses on analyzing data about associations registered in Paris. Using an API, the data was fetched in JSON format and transformed into a pandas dataframe for exploration and analysis. The dataset includes details such as the statutory name, postal code, city of registration, sectors of activity, domains of activity..
- Host: GitHub
- URL: https://github.com/zrkhadija/analyzing-parisian-associations-a-data-exploration-project
- Owner: zrkhadija
- Created: 2024-05-18T16:26:40.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-11-21T14:44:57.000Z (2 months ago)
- Last Synced: 2024-11-21T15:33:07.180Z (2 months ago)
- Topics: analysis, data-visualization, json-api, paris
- Language: Jupyter Notebook
- Homepage:
- Size: 410 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# 📊 Analyzing Parisian Associations: A Data Exploration Project
This project provides an exploratory analysis of associations registered in Paris. Using data obtained from an API, the project processes JSON-format data into a pandas dataframe and performs a detailed analysis of the dataset.## 🚀 Features
- **Data Collection**: Fetch data from an API in JSON format.
- **Data Transformation**: Convert JSON data into a structured pandas dataframe for analysis.
- **Data Analysis**: Explore key attributes of associations such as their statutory names, sectors of activity, domains, audiences, and geographical locations.
- **Visualization**: (Optional) Generate insights with visualizations to highlight trends and distributions.
## 📊 Dataset Description
The dataset contains the following fields:- **Statutory Name**: The official name of the association.
- **Postal Code and City**: Location details of the association.
- **Sectors of Activity**: The areas in which the association is active.
- **Domain of Activity**: Broader categories defining the association's purpose.
- **Audiences**: Target groups of the association.
- **Geographical Sector**: Areas where the association operates.
- **Registry Identifier**: Unique ID if the association is registered in the Parisian directory.
## 🛠️ Technologies Used
- **Python**: For data processing and analysis.
- **pandas**: For data manipulation and transformation.
- **API Requests**: For fetching the data.