When.com Web Search

  1. Ad

    related to: python seaborn data visualization

Search results

  1. Results From The WOW.Com Content Network
  2. A beginner’s guide to data visualization with Python and Seaborn

    www.aol.com/beginner-guide-data-visualization...

    There are many tools to perform data visualization, such as Tableau, Power BI, ChartBlocks, and more, which are no-code tools. A beginner’s guide to data visualization with Python and Seaborn ...

  3. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.

  4. Rug plot - Wikipedia

    en.wikipedia.org/wiki/Rug_plot

    A rug plot of 100 data points appears in blue along the x-axis. (The points are sampled from the normal distribution shown in gray. The other curves show various kernel density estimates of the data.) A rug plot is a plot of data for a single quantitative variable, displayed as marks along an axis. It is used to visualise the distribution of ...

  5. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...

  6. Correlogram - Wikipedia

    en.wikipedia.org/wiki/Correlogram

    In the analysis of data, a correlogram is a chart of correlation statistics. For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram.

  7. Hands-On Data Visualization - Wikipedia

    en.wikipedia.org/wiki/Hands-On_Data_Visualization

    Hands-On Data Visualization details design methods for interactive charts and customized maps, starting with drag-and-drop tools including Google Sheets, Datawrapper, and Tableau Public. It progresses to detail methods for editing source code templates built with Chart.js, Highcharts, and Leaflet on GitHub.

  8. Graph drawing - Wikipedia

    en.wikipedia.org/wiki/Graph_drawing

    Mathematica, a general-purpose computation tool that includes 2D and 3D graph visualization and graph analysis tools. [29] Microsoft Automatic Graph Layout, open-source .NET library (formerly called GLEE) for laying out graphs [30] NetworkX is a Python library for studying graphs and networks. Tulip, [31] an open-source data visualization tool

  9. Orange (software) - Wikipedia

    en.wikipedia.org/wiki/Orange_(software)

    Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.