Obtaining and plotting a step plot for time series dataframe-CodePudding

I had the following dataframe containing information about stages as a time series:

import pandas as pd
d = {'Stages': ['Stage 1', 'Stage 2', 'Stage 2', 'Stage 2', 'Stage 3', 'Stage 1'], 'Start(s)': [0, 630, 780, 840, 900, 930], 'End(s)': [630, 780, 840, 900, 930, 960]}
df = pd.DataFrame(data=d)

    Stages         Start(s) End(s)
0   Stage 1          0      630
1   Stage 2         630     780
2   Stage 2         780     840
3   Stage 2         840     900
4   Stage 3         900     930
5   Stage 1         930     960

I wanted to obtain a step plot as shown

-2 = Unscored -1 = Artefact / Movement 0 = Wake 1 = N1 sleep 2 = N2 sleep 3 = N3 sleep 4 = REM sleep

NB : You may need to use a Python version (>=3.7, <3.11) to install all of yasa dependencies. Python version (3.11.0) seems to not be supported yet.

CodePudding user response：

My first thought was to use the

This is about the bare minimum; it ignores the particular formatting specific to the sleep cycle, rather it hopefully shows you how to draw the desired curve "from scratch".

Additional notes:

If you need to invert the y axis, you can convert the stages to negative integers instead of positive ones.
If you need to rename the y labels, you can use plt.yticks([1, 2, 3], ['a', 'b', 'c']) to rename them.
Generally this approach is reliant on the "stages" being interpretable as integers. If you had additional stages that were not numeric, you would need to recode them to numbers, and then change their name using plt.yticks as above.