[Python] Stacked Bar Graphs with only Plotly Express

I have data stored in three different lists like this:

labels = ['label1', 'label2', 'label3']
types = ['type1', 'type2', 'type3', 'type4', 'type5', 'type6']
counts = [[3,5,2,1,7,10], [2,2,4,1,7,2], [1,6,8,11,2,3]]


counts list holds counts of types for every label, like: label1 has 3 of type1, 5 of type2, ...; label2 has 2 of type1, 2 of type2, ... etc.

I can create a stacked bar graph with plotly.graph_objects but I want to create this graph with plotly.express.

My code to create the stacked bar graph with plotly.graph_objects:

import plotly.graph_objects as go

for i in range(len(types)):
if i == 0:
fig = go.Figure(go.Bar(x=labels, y=[sub for sub in counts], name=types))
else:
fig.add_trace(go.Bar(x=labels, y=[sub for sub in counts], name=types))

fig.update_layout(barmode='stack')
fig.show()


How can I achieve the same result with only using plotly.express, since I create all my other graphs with plotly.express and don't want to import plotly.graph_objects

Update: I can pass my data to a pandas dataframe and create the graph with plotly.express with the code below:

import pandas as pd
import plotly.express as px

df = pd.DataFrame([count for sub in counts for count in sub],
index=pd.MultiIndex.from_product([labels,types]),
names=['label', 'type'],
columns=['count'])
fig = px.bar(df, x=df.index.get_level_values('label'),
y='count',
color=df.index.get_level_values('type'),
barmode='stack')
fig.show()


But is there any way to do it without pandas too?

Continue reading...