https://github.com/krupanss/Interactive-Exploratory-Data-Analysis

An Interactive Shiny Application for exploratory data analysis thru visualization
https://github.com/krupanss/Interactive-Exploratory-Data-Analysis

Last synced: 3 months ago
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An Interactive Shiny Application for exploratory data analysis thru visualization

• Host: GitHub
• URL: https://github.com/krupanss/Interactive-Exploratory-Data-Analysis
• Owner: krupanss
• License: gpl-3.0
• Created: 2017-10-13T06:10:35.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-10-13T10:56:32.000Z (over 7 years ago)
• Last Synced: 2024-08-13T07:15:25.149Z (6 months ago)
• Language: R
• Size: 149 KB
• Stars: 4
• Watchers: 2
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Interactive-Exploratory-Data-Analysis

An application for exploratory data analysis thru Interactive Visualizations

# About

Exploratory Data Analysis is one of the key components of a data science project. It is a crucial step to take before diving in to the machine learning or data modeling. EDA can sometimes be time consuming due to reasons like huge number of variables in the data set, writing code for each plot or group of plots. In order to eliminate these difficulties and reduce the time here is a simple tool which provides different interactive visualizations used in EDA just on click of a button.

## Download the source code and open it in R Studio with the following packages installed. 

shiny, shinyjs, shinydashboard, plotly, DT, xlsx, evaluate, shinycssloaders, dplyr, tools, stringr

# Manual

IEDA is a simple application and is easy to use. Follow the below series of simple steps to utilise the tool.

1. Upload the dataset file in the selected format in the "DataSource" tab and click on submit.

2. On submit, you can do pre-processing of Data in the "Data Processing" Pane on the right side.

3. In the "Data Strucure" tab, you can view the strucure of data.

4. In the "Data Preview" tab, you can view the actual data.

5. In the "Select Column Features" tab, you can choose the feature of the columns.

6. Select Dimensions for Discrete or non continuous variables

7. Select Measures for Continuous variables

8. Select Exclude to exclude the variable in the EDA

9. Once the pre-processing is completed, click on Explore button on the bottom in the "Select Column Features" tab.

10. On clicking the "Explore Button", Seven different interactive visualizations with options are presented and can be accessed in the sidebar panel.