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Module:Chart creates bar and pie charts on Wikipedia without need for external tools; Many spreadsheet, drawing, and desktop publishing programs allow you to create graphs and export them as images. gnuplot can produce a wide variety of charts and graphs; see samples with source code at Commons. In Python using matplotlib
This is a list of software to create any kind of information graphics: either includes the ability to create one or more infographics from a provided data set either it is provided specifically for information visualization
Chart Studio Cloud is a free, online tool for creating interactive graphs. It has a point-and-click graphical user interface for importing and analyzing data into a grid and using stats tools. [ 13 ] Graphs can be embedded or downloaded.
Google Sheets – Online spreadsheet with built-in charting function for basic chart types; KChart – the charting tool of the Calligra Suite; LibreOffice Calc - Built-in charting function for basic chart types; Microsoft Excel – Built-in charting function for basic chart types; Apache OpenOffice Calc - Built-in charting function for basic ...
Use the SVG format. Upload to Wikimedia Commons using the Commons Upload Wizard. Be sure to include a licensing tag (GFDL, CC, public domain, etc.). Don't use any natural language in the plot - numbers and symbols only. Place descriptive text in the caption. If needed you can also write extended information in the image description page.
Dbt has the goal of allowing analysts to work more like software engineers, in line with the dbt viewpoint. [11] Dbt uses YAML files to declare properties. seed is a type of reference table used in dbt for static or infrequently changed data, like for example country codes or lookup tables), which are CSV based and typically stored in a seeds ...
It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.
Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License. It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques". [1]