Display only existing x-axis values for each facet in a multi-faceted bar plot using plotly

For the following multifacet plot

df = pd.DataFrame({
    'row': [0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1],
    'col': [0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1 ],
    'x_value': [1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4], 
    'count':  [1,7,4,0,0,3,1,3,1,9,2,2,0,0,3,4]


})

df = df.query('count != 0 ')

fig = px.bar(df, x='x_value', y='count', facet_col='col', facet_row='row', template='simple_white')
fig.for_each_xaxis(lambda xaxis: xaxis.update(showticklabels=True, title_font = dict(size =20), type = 'category'))


fig.show()

for each subplot, i want to show ONLY the x-ticks present in the data.

The circled ticks should not be showing:

To get what you are looking for, you need to customize each x-axis (and y-axis, if required) to include matches=None. This will stop trying to match the columns across each of the subplots. So, replace the line...

fig.for_each_xaxis(lambda xaxis: xaxis.update(showticklabels=True, title_font = dict(size =20), type = 'category'))

with

fig.for_each_xaxis(lambda xaxis: xaxis.update(showticklabels=True, matches=None, title_font = dict(size =20), type = 'category'))

and you will get below plot. Hope this is what you are looking for...