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diff --git a/sources/pyside6/doc/tutorials/datavisualize/filter_data.rst b/sources/pyside6/doc/tutorials/datavisualize/filter_data.rst new file mode 100644 index 000000000..b06b2fa15 --- /dev/null +++ b/sources/pyside6/doc/tutorials/datavisualize/filter_data.rst @@ -0,0 +1,29 @@ +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. |