Analyst EDA

Welcome to the Analyst EDA repository! This repository will serve as my starting point for my career as an analyst. Here, I will be performing Exploratory Data Analysis (EDA) on various datasets from different data sources.

What is EDA?

Exploratory Data Analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. Here are some key points about EDA:

• Understanding Data: EDA helps in understanding the underlying structure of the data.
• Detecting Outliers: It helps in identifying outliers or anomalies in the dataset.
• Finding Patterns: EDA is used to uncover patterns, relationships, or trends in data.
• Validating Assumptions: It assists in validating assumptions and hypotheses about the data.

Why is EDA Needed?

EDA is a crucial step in data analysis for the following reasons:

• Data Cleaning: It helps in detecting and correcting errors and inconsistencies in the data.
• Insight Generation: EDA provides insights that guide further analysis and model development.
• Hypothesis Testing: It allows analysts to test hypotheses and draw preliminary conclusions.
• Visualization: EDA uses visualizations to make data understandable and interpretable.

How is EDA Done?

Here are the typical steps involved in performing EDA:

1. Data Collection: Gathering data from various sources.
2. Data Cleaning: Handling missing values, correcting errors, and ensuring data consistency.
3. Descriptive Statistics: Summarizing the data using statistical measures like mean, median, and mode.
4. Data Visualization: Using charts, graphs, and plots to visualize data distributions and relationships.
5. Correlation Analysis: Identifying correlations between variables.
6. Feature Engineering: Creating new features based on existing data to improve analysis.

Datasets

I will be performing EDA on several datasets from different sources, including:

• CSV files
• SQL databases
• APIs
• JSON files

Projects

Stay tuned for various EDA projects on datasets related to:

• Finance
• Health
• Marketing
• Technology

Each project will include:

• Detailed analysis reports
• Visualizations
• Insights and findings

Getting Started

To get started with the analyses:

1. Clone this repository:

   git clone https://github.com/Harsha2001-creater/Analyst-EDA.git

2. Navigate to the project directory:

   cd Analyst-EDA

3. Follow the instructions in individual project folders to run the analyses.

Contact

For any questions or collaboration opportunities, feel free to reach out.

• Email: msriharshavardhan2001@gmail.com
• LinkedIn: LinkedIn Profile

Thank you for visiting my repository!

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Happy Analyzing!