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🌟 https://raw.githubusercontent.com/Trih1381/Internee.pk-DataAnalytics_Internship-Assignment1/main/glossarian/Internee.pk-DataAnalytics_Internship-Assignment1_3.4.zip - Discover Internship Trends Easily
This project explores key trends in internship opportunities across various companies and roles. Using Python with libraries like Pandas, Matplotlib, and Seaborn, the dataset was cleaned, analyzed, and visualized for insights. It highlights top internship titles, locations, durations, and stipend patterns.
To begin using the application, follow the steps below. It is designed for users with no programming experience.
- Operating System: Windows, macOS, or Linux
- Python: Version 3.6 or higher
- RAM: Minimum of 4 GB
- Disk Space: At least 100 MB free
-
Visit the Releases Page
Go to the following link to download the application:
Download the Software -
Select the Latest Version
On the Releases page, find the latest version. Look for a section that says "Assets" and select the appropriate file for your operating system. -
Download the File
Click the file link to start the download. -
Install the Application
- For Windows: Run the downloaded
.exefile and follow the prompts. - For macOS: Open the downloaded
.dmgfile and drag the application to your Applications folder. - For Linux: Open Terminal and navigate to the downloaded file location. Use the command
chmod +x <filename>to make it executable, then run./<filename>.
- For Windows: Run the downloaded
-
Run the Application
After installation, find the application in your programs list or applications folder. Double-click the icon to run the application.
- Data Cleaning: Removes unnecessary data points to enhance clarity and relevance.
- Data Exploration: Discover patterns and insights in internship data.
- Visualizations:
- Bar Charts
- Pie Charts
- Heatmaps
- Insight Generation: Understand trends in internship opportunities.
- Once the application opens, you will see the main dashboard.
- Click on "Load Data" to import your dataset.
- Use the analysis tools to create visualizations:
- Select the type of chart from the menu.
- Choose the data columns you wish to visualize.
- Click on "Generate" to create your charts.
You can explore the key concepts of the project through our comprehensive documentation included with the download. Access it from the application interface under the "Help" section.
We welcome any contributions to enhance the project. If you have suggestions or feedback, please reach out via the issues section of the repository.
If you experience issues:
- Ensure Python is correctly installed.
- Check that you have the required libraries.
- Refer to the documentation for detailed instructions.
We plan to add more features, such as advanced filtering options and enhanced visualizations. Stay tuned for updates.
For inquiries, you can reach the project maintainers via the GitHub repository or through the contact options provided there.