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Created a bar chart or histogram to visualize the distribution of a categorical (e.g., gender) or continuous (e.g., age) variable using Python visualization libraries.

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Prodigy InfoTech Internship: Data Analysis Insights

  • Welcome to the repository for my internship at Prodigy InfoTech! This space documents Task 1 of my journey, which centers around data preprocessing, analysis, and extracting meaningful insights.
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πŸ“Š Task Summary

  • Developed a bar chart or histogram to represent the distribution of a categorical (e.g., gender) or continuous (e.g., age) variable within a dataset. This helped in visualizing population patterns effectively.

πŸ’‘ Skills & Learning

  • Through this task, I enhanced my skills in creating clear, insightful visualizations using Python tools like Matplotlib and Seaborn. It also deepened my understanding of how graphical representation aids in data interpretation.

βš™οΈ Tools and Libraries used

  • Jupyter notebook
  • Pandas
  • Numpy
  • Matplotlip & Seaborn for visualization

πŸ† Output


🀝 Let's Connect

  • Explore the repository, share your thoughts, or reach out to discuss data analysis, internship experiences, or related topics. Always open to learning and collaboration!

πŸ“¬ Contact

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Created a bar chart or histogram to visualize the distribution of a categorical (e.g., gender) or continuous (e.g., age) variable using Python visualization libraries.

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