qaqert.blogg.se - september 2023

Pyplot main plot title separator from subplot title

Some kind of interface to derive additional columns based on already existing ones (I do not know how this should look like atm.).This would allow to plot CSV data which is embedded in a larger file.

Skipping the first N lines of a file and dropping the last M as well.Implement utility functions for basic file transformations like:.Provide a way to set the line style and color for each separate column independently.This is useful if you want to plot a CSV file but do not remember the exact spelling of each column header. Set the scale of both Y axes independently when the automatic scaling does not deliver a reasonable result.īy now, only one utility function is implemented which lists all column headers in order of appearance.Move columns to alternative Y axes in their subplots which allows for pretty diverse data to be plotted in the same subplot, since both Y axes scale independently.Setting titles for subplots, labels for X and Y axes as well as legend texts for each plotted column.Group columns into subplots which allows for less cluttered, more readable plots.Setting default filename for the date file and the exported image file.

When working with YAML configuration files the range supported features is even broader:

Exporting the plot as a an image file supported by matplotlib without the need for a GUI.

Reducing the amount of plotted samples by taking every n-th sample or specifying a range of samples to plot.

This allows plotting any combination of columns. The following functionality can be accessed The plotting part of the script already supports a good range of features. A simple to use script to plot CSV files using matplotlib.Īdditionally to the ability to plot CSV files a selection of utility functions operating on CSV files.