https://github.com/mithildabhi/prodigy_ds_02
Performed data cleaning and exploratory data analysis (EDA) on the Titanic dataset to uncover patterns, trends, and relationships between variables using Python libraries like Pandas, Matplotlib, and Seaborn.
https://github.com/mithildabhi/prodigy_ds_02
data-science intenship prodigy-infotech
Last synced: 21 days ago
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Performed data cleaning and exploratory data analysis (EDA) on the Titanic dataset to uncover patterns, trends, and relationships between variables using Python libraries like Pandas, Matplotlib, and Seaborn.
- Host: GitHub
- URL: https://github.com/mithildabhi/prodigy_ds_02
- Owner: mithildabhi
- Created: 2025-05-12T04:35:38.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-12T07:16:57.000Z (about 1 year ago)
- Last Synced: 2025-05-22T04:12:14.738Z (about 1 year ago)
- Topics: data-science, intenship, prodigy-infotech
- Language: Jupyter Notebook
- Homepage:
- Size: 537 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Prodigy InfoTech Internship: Exploratory Data Analysis (EDA)
Welcome to **Task 2** of my internship at **Prodigy InfoTech**!
This task focuses on performing **data cleaning** and **exploratory data analysis (EDA)** using real-world datasets to extract meaningful insights.
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## 🔍 Task Summary
Performed data cleaning and EDA on a dataset of my choice.
I used the famous **Titanic dataset** from Kaggle to explore relationships between variables and uncover trends and patterns.
**Sample Dataset:** [Titanic Dataset – Kaggle](https://www.kaggle.com/c/titanic/data)
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## 📊 Skills & Knowledge Gained
- Hands-on experience in **data preprocessing**, handling **missing values**, and fixing inconsistent data.
- Used **Pandas**, **Matplotlib**, and **Seaborn** to explore and visualize the dataset.
- Discovered correlations and trends that could influence model building and data-driven decisions.
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## 🤝 Let’s Connect
Feel free to explore the repository, provide feedback, or reach out to collaborate or discuss anything related to **data science** or **internship experiences**.
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## 📬 Contact
- **Email:** mithildabhi898@gmail.com
- **LinkedIn:** [Mithil Dabhi](https://www.linkedin.com/in/mithildabhi)