For research purposes at my university, I need to create a stacked bar chart for speech data. I would like to represent the hours of speech on the y-axis and the frequency on the x-axis. The speech comes from different components, hence the stacked part of the chart. The data resides in a Pandas dataframe, which has a lot of columns, but the important ones are "component", "hours" and "ps_med_frequency" which are used in the graph.
A simplified view of the DF (it has 6.2k rows and 120 columns, a-k components):
| component | filename | ps_med_freq (rounded to integer) | hours (length) | ... |
|---|---|---|---|---|
| a | fn0001_ps | 230 | 0.23 | |
| b | fn0002_ps | 340 | 0.12 | |
| c | fn003_ps | 278 | 0.09 |
I have already tried this with matplotlib, seaborn or just the plot method from the Pandas dataframe itself. None seem to work properly.
A snippet of seaborn code I have tried:
sns.barplot(data=meta_dataframe, x='ps_med_freq', y='hours', hue='component', dodge=False)
And basically all variations of this as well.
Below you can see one of the most "viable" results I've had so far:
