DS Practical: Practical-3

Introduction to Orange Tool

Introduction to Orange Tool:

Provides data visualization and data analysis for novice and expert, through interactive workflows.

Large widget toolbox and several add-ons
Developed by Bioinformatics Lab at University of Ljubljana, Slovenia, in collaboration with open source community.

Widgets in the Orange Tool

1) File: The file widgets reads the input data file and sends the dataset to its output channel. The history of most recently opened files is maintained in the widget.

2) CSV File Import: This widget reads comma-separated files and sends the dataset to its output channel. Files separators can be commas, semicolons, spaces, tabs or manually-defined delimiters.

3) Datasets: Dataset widget retrieves selected dataset from the server and sends it to the output. The file is downloaded to the local memory and thus instantly available even without the internet connection.

4) Data Table: This widget receives one or more datasets in its input and presents them as a spreadsheet.

5) Data Info: A simple widget that presents information on the dataset size, features, targets, meta attributes, and location.

6) Data Sampler: The data sampler widget implements several data sampling methods. It outputs a sampled and a complementary dataset.

7) Select Columns: The select columns widget is used to manually compose your data domain. The user can decide which attributes will be used and how.

8) Box Plot: The box plot widget shows the distribution of attribute value. It is a good practice to check any new data with this widget to quickly discover any anomalies, such as duplicate values, outliers, and alike.

9) Distributions: The Distributions widget displays the value distribution of discrete or continuous attributes. If the data contains a class variable, the distribution may be conditioned on the class.

10) Scatter Plot: The Scatter Plot widget provides a 2-dimensional scatter plot visualization for continuous attributes. The data is displayed as a collection of points.

11) Line Plot: Line plot a type of plot which displays the data as a series of points, connected by straight line segments. It only works for numerical data, while categorical can be used for grouping of the data points.