https://github.com/iamzehan/inspect-panda

EDA tool for Data Science & Machine Learning. Quickly inspect your dataset effortlessly with a Graphical User Interface designed to suit your needs.
https://github.com/iamzehan/inspect-panda

data-analysis data-analytics data-science data-science-projects data-visualization eda machine-learning python streamlit

Last synced: 1 day ago
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EDA tool for Data Science & Machine Learning. Quickly inspect your dataset effortlessly with a Graphical User Interface designed to suit your needs.

• Host: GitHub
• URL: https://github.com/iamzehan/inspect-panda
• Owner: iamzehan
• License: mit
• Created: 2022-08-03T11:10:49.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2024-01-11T19:59:08.000Z (over 2 years ago)
• Last Synced: 2024-04-16T07:18:05.097Z (over 2 years ago)
• Topics: data-analysis, data-analytics, data-science, data-science-projects, data-visualization, eda, machine-learning, python, streamlit
• Language: Python
• Homepage:
• Size: 61.5 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Security: SECURITY.md

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README

          
# Tool for Exploratory Data Analysis meant for Data Science and Machine Learning Projects

## Inspect Panda

___

'Inspect Panda' is a tool to perform some basic and advanced exploratory data analysis on the go. It is a helper tool that saves you a ton of time to get an idea about your datasets with a few clicks.

The tools it offers are:

- Missing Values Exploration and Handling.


    - Count Missing Values


    - Drop NaN


          - Drop Columns with NaNs


          - Drop Rows with NaNs


    - Fill NaNs


          - ffill


          - bfill


          - fillna


- Scaling and Normalization


    - Plot Scaled Data


    - Plot Normalized Data


    

- Date Time anomaly Detection.


    - Compare Dates


    - Detect Abnormality in Dates


    

- Feature Selection.


   - Mutual Information Gathering 


   - Correlations 


   - Clustering 


   - $Chi^2$ 


   - Feature Importance 


   - Principal Component Analysis (PCA)


- Detecting Inconsistent Data Entries.


   - Unique Values


   - FuzzyWuzzy

 - Powerful and Convenient visualizations

Here's the link to the app: [Link](https://inspect-panda.streamlit.app/)