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Data3Sixty - Pie and bar charts

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    Adrian Williams

    You can use the Python node to leverage the pandas and the matplotlib Python packages to create plots.

    Attached is a zip file that explains how you can install 3rd party Python packages into the site-packages folder of a Desktop Analyze instance. The document describes the installation of numpy and pandas. In addition to this you will need to install the matplotlib package.

    The Python_Node_Output_TimeSeries_Plot_Image.zip file contains an example of how you can use the matplotlib package to create a chart image - in this case consisting of multiple series data corresponding to time series forecast data. Matplotlib can be used to create bar and pie charts - see the documentation for the package or other online resources.

    A Generate Data node is configured to specify the filename of the csv file containing the source data for the chart image and name of the file in which to save the resulting chart.

     

     

    The Python node is configured to read in the source chart data filename and the chart output file name. 

     

    Pandas is used to read in the data as a data frame and construct individual data frames for each of the series to be plotted in the chart. The matplotlib module is then used to create the plot lines and add labels and a title to the chart. The generatd chart is then saved as the specified image file.

     

    The example chart image will be as follows:

     

    Attached files

    Install_numpy_pandas_in_Data360_Analyze.zip
    Python_Node_Output_TimeSeries_Plot_Image.zip

     

     

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    Adrian Williams

    The data flow in the above zip file requires the use of Analyze v.3.6.0 or above.

    Here is a version of the data flow that can be used with Analyze v.3.4.x

     

    Attached files

    Python_Node_Output_TimeSeries_Plot_Image_432--share - 15 Jun 2020.lna

     

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