Dataset Retrieval and Data Mining with Orange: A Hands-on Tutorial
How to Download and Use Orange Datasets
Orange is a popular open source tool for data mining, machine learning, and data visualization. It allows you to build data analysis workflows visually, with a large and diverse toolbox of widgets. In this article, you will learn how to download and use Orange datasets, which are collections of data that you can use for your own projects or for learning purposes.
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What is Orange Data Mining?
Orange Data Mining is a software that enables you to perform data analysis and visualization without coding. You can simply drag and drop widgets on the canvas, connect them, load your datasets, and harvest the insights. You can also extend the functionality of Orange with various add-ons, such as text mining, network analysis, bioinformatics, and more.
Features and benefits of Orange
Some of the features and benefits of Orange are:
It is free and open source, so you can use it for any purpose.
It has a user-friendly graphical interface that makes data analysis easy and fun.
It supports interactive data exploration and visualization, with widgets for statistical distributions, box plots, scatter plots, decision trees, hierarchical clustering, heatmaps, MDS, linear projections, etc.
It offers a wide range of machine learning algorithms, such as classification, regression, clustering, association rules mining, etc.
It can handle various types of data, such as numerical, categorical, text, image, time series, etc.
It can import data from different sources, such as files, URLs, Google Sheets, etc.
It can export data and visualizations in various formats, such as CSV, Excel, PNG, SVG, etc.
It has a vibrant community of users and developers who provide support and feedback.
How to install Orange
To install Orange on your computer, you can follow these steps:
Go to and choose the version that suits your operating system (Windows, macOS or Linux).
Download the standalone installer (default) or the portable version (no installation needed).
Run the installer or extract the zip file and open the shortcut in the extracted folder.
Launch Orange and start creating your workflows.
How to access Orange datasets
Orange provides several datasets that you can use for your data analysis projects or for learning purposes. You can access these datasets in different ways:
Using the Datasets widget
The Datasets widget allows you to load a dataset from an online repository. You can choose from a list of datasets that are provided with a description and information on the data size, number of instances, number of variables, target and tags. The dataset is downloaded to the local memory and thus instantly available even without an internet connection. You can also search for a dataset by name or tag. To use the Datasets widget:
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Add the Datasets widget to the canvas from the Data category.
Select a dataset from the list or search for one by name or tag.
If Send Data Automatically is ticked, the selected dataset is sent to the output. Alternatively, press Send Data.
Connect the output of the Datasets widget to another widget that accepts data input.
Using the File widget
The File widget allows you to load a dataset from a local file or a URL. You can import any comma-, tab-, or space-delimited data file or Excel file. You can also edit the features of the dataset by double-click ing on the Edit Domain button. You can also reload the data from the source by clicking on the Reload button. To use the File widget:
Add the File widget to the canvas from the Data category.
Click on the Browse button and select a file from your computer or enter a URL in the text box.
If Send Data Automatically is ticked, the loaded dataset is sent to the output. Alternatively, press Send Data.
Connect the output of the File widget to another widget that accepts data input.
Using URL or Google Sheets
You can also load a dataset from a URL or a Google Sheets document by using the URL or Google Sheets option in the Datasets widget. To use this option:
Add the Datasets widget to the canvas from the Data category.
Select URL or Google Sheets from the list of datasets.
Enter a valid URL or a Google Sheets ID in the text box.
If Send Data Automatically is ticked, the loaded dataset is sent to the output. Alternatively, press Send Data.
Connect the output of the Datasets widget to another widget that accepts data input.
How to explore and visualize Orange datasets
Once you have loaded a dataset in Orange, you can explore and visualize it using various widgets. Here are some examples of how you can do that:
Using the Data Table widget
The Data Table widget allows you to view and edit your data in a tabular format. You can sort, filter, select, and copy your data. You can also change the type and role of your variables by double-clicking on their headers. To use the Data Table widget:
Add the Data Table widget to the canvas from the Data category.
Connect an input data source to the Data Table widget.
View and edit your data in the table.
If Send Automatically is ticked, any changes you make to your data are sent to the output. Alternatively, press Send Selected Rows or Send All Rows.
Connect the output of the Data Table widget to another widget that accepts data input.
Using the Box Plot widget
The Box Plot widget allows you to visualize the distribution of your data using box plots. You can compare different groups of data based on one or more variables. You can also select and filter your data by clicking on the boxes or whiskers. To use the Box Plot widget:
Add the Box Plot widget to the canvas from the Visualize category.
Connect an input data source to the Box Plot widget.
Select a variable for Group by and one or more variables for Variables.
View and compare your data using box plots.
If Send Automatically is ticked, any data you select in the box plots are sent to the output. Alternatively, press Send Selected Data or Send All Data.
Connect the output of the Box Plot widget to another widget that accepts data input.
Using other widgets for data analysis and machine learning
Besides these two widgets, there are many other widgets that you can use for data analysis and machine learning in Orange. For example, you can use:
The Scatter Plot widget to visualize your data using scatter plots and select interesting subsets of data by drawing shapes or lassoing points.
The Distributions widget to visualize your data using histograms and density plots and compare different groups of data based on one or more variables.
The PCA widget to perform principal component analysis on your data and reduce its dimensionality.
The k-Means widget to perform k-means clustering on your data and find groups of similar instances.
The Classification Tree widget to build a decision tree classifier on your data and visualize its structure and performance.
Conclusion
In this article, you learned how to download and use Orange datasets, which are collections of data that you can use for your own projects or for learning purposes. You also learned how to access these datasets in different ways, such as using the Datasets widget, the File widget, or URL or Google Sheets. Finally, you learned how to explore and visualize these datasets using various widgets, such as the Data Table widget, the Box Plot widget, and others. Orange is a powerful and easy-to-use tool for data mining, machine learning