Uncover Insights with the Exploratory Data Analysis (EDA) Web App
Data analysis is a crucial step in extracting valuable insights from datasets. To simplify this process, I have developed an interactive web application for Exploratory Data Analysis (EDA). This web app allows users to upload CSV files, analyze data types, and gain deeper insights into textual and numerical columns.
Features
1. User-Friendly Interface
The EDA web app provides an intuitive interface for users to navigate through the analysis process. With a few clicks, users can upload their datasets and explore various aspects of their data.
2. Comprehensive Data Information
Upon uploading a CSV file, the app displays essential information about the dataset. Users can quickly understand the data types, missing values, and the distribution of each column.
3. Textual Column Analysis
For textual columns, the app offers detailed insights. Users can analyze unique values, generate word clouds, and identify the top words. This feature is particularly useful for understanding patterns in text-based data.
4. Numerical Column Analysis
Numerical columns are not left behind. The app provides basic statistics, histograms, covariance matrices, pair plots, and correlation matrices for a thorough numerical analysis.
5. Refresh Option
To start fresh, users can use the “Refresh” button, resetting the app to its initial state. This feature is handy when users want to analyze multiple datasets sequentially.
How to Use
- Upload Your Dataset:
- Click on “Choose a CSV file” to upload your dataset.
- Ensure your CSV file contains both textual and numerical columns for a comprehensive analysis.
2. Select Analysis Type:
- Choose between analyzing textual or numerical columns.
- For textual columns, select the specific column for analysis.
- For numerical columns, select one or more columns.
3. Analyze:
- Explore the various analysis options such as word clouds, histograms, covariance, pair plots, and more.
- Understand the patterns and relationships within your data.
4. Refresh to Beginning:
- Use the “Refresh” button to reset the app to its initial state.
Tech Stack
- Streamlit
- Pandas
- Matplotlib
- Seaborn
- WordCloud
- NLTK
Installation
# Clone the repository
git clone https://github.com/Jeetanand/Exploratory_Data_Analysis_webapp.git
# Change directory
cd Exploratory_Data_Analysis_webapp# Install dependencies
pip install -r requirements.txt
Run the App
streamlit run EDA_app.pyConclusion
The EDA web app simplifies the data analysis process, making it accessible to both beginners and experienced data analysts. Its user-friendly interface and comprehensive features empower users to uncover hidden patterns and draw meaningful conclusions from their datasets.
Happy analyzing!
