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diff --git a/sources/pyside2/doc/tutorials/datavisualize/filter_data.rst b/sources/pyside2/doc/tutorials/datavisualize/filter_data.rst deleted file mode 100644 index b06b2fa15..000000000 --- a/sources/pyside2/doc/tutorials/datavisualize/filter_data.rst +++ /dev/null @@ -1,29 +0,0 @@ -Chapter 2 - Filtering data -=========================== - -In the previous chapter, you learned how to read and print data that is a -bit raw. Now, try to select a few columns and handle them properly. - -Start with these two columns: Time (time) and Magnitude (mag). After getting -the information from these columns, filter and adapt the data. Try formatting -the date to Qt types. - -There is not much to do for the Magnitude column, as it's just a floating point -number. You could take special care to check if the data is correct. This could -be done by filtering the data that follows the condition, "magnitude > 0", to -avoid faulty data or unexpected behavior. - -The Date column provides data in UTC format (for example, -2018-12-11T21:14:44.682Z), so you could easily map it to a QDateTime object -defining the structure of the string. Additionally, you can adapt the time -based on the timezone you are in, using QTimeZone. - -The following script filters and formats the CSV data as described earlier: - -.. literalinclude:: datavisualize2/main.py - :language: python - :linenos: - :lines: 40- - -Now that you have a tuple of QDateTime and float data, try improving the -output further. That's what you'll learn in the following chapters. |