How to make a horizontal stacked histplot based on counts?-CodePudding

I have a df which represents three states (S1, S2, S3) at 3 timepoints (1hr, 2hr and 3hr). I would like to show a stacked bar plot of the states but the stacks are discontinous or at least not cumulative. How can I fix this in Seaborn? It is important that time is on the y-axis and the state counts on the x-axis.

Below is some code.

data = [[3, 2, 18],[4, 13, 6], [1, 2, 20]]
df = pd.DataFrame(data, columns = ['S1',  'S2', 'S3'])
df = df.reset_index().rename(columns = {'index':'Time'})
melt = pd.melt(df, id_vars = 'Time')

plt.figure()
sns.histplot(data = melt,x = 'value', y = 'Time', bins = 3, hue = 'variable', multiple="stack")

EDIT: This is somewhat what I am looking for, I hope this gives you an idea. Please ignore the difference in the scales between boxes...

CodePudding user response：

This is pretty tough in seaborn as it doesn't natively support stacked bars. You can use either the builtin plot from pandas, or try plotly express.

data = [[3, 2, 18],[4, 13, 6], [1, 2, 20]]
df = pd.DataFrame(data, columns = ['S1',  'S2', 'S3'])
df = df.reset_index().rename(columns = {'index':'Time'})
# so your y starts at 1
df.Time =1

melt = pd.melt(df, id_vars = 'Time')
# so y isn't treated as continuous
melt.Time = melt.Time.astype('str')

Pandas can do it, but getting the labels in there is a bit of pain. Check around to figure out how to do it.

df.set_index('Time').plot(kind='barh', stacked=True)

Plotly makes it easier:

import plotly.express as px
px.bar(melt, x='value', y='Time', color='variable', orientation='h', text='value')

CodePudding user response：

If I understand correctly, I think you want to use value as a weight:

sns.histplot(
    data=melt,
    y='Time', weights='value', hue='variable',
    discrete=True,', multiple='stack, shrink=.8
)