1 files changed, 29 insertions, 0 deletions
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.