Question: I have a facet wraped group of plotly express barplots , each with a title. How can I left align each subplot's title with the left of its plot window?  import lorem import plotly.express as px import numpy as np import random items = np.repeat([lorem.sentence() for i in range(10)], 5) response = list(range(1,6)) * 10 n = [random.randint(0, 10) for i in range(50)] ( px.bar(x=response, y=n, facet_col=items, facet_col_wrap=4, height=1300) .for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1])) .for_each_xaxis(lambda xaxis: xaxis.update(showticklabels=True)) .for_each_yaxis(lambda yaxis: yaxis.update(showticklabels=True)) .show() )  I tried adding .for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1], x=0)) but it results in: 

Answer: There's a few major challenges here:  annotations are not aware of their column in the facet plot (which makes determining the x value difficult) the order in which annotations are created are from left to right, bottom to top (therefore, the annotations at the bottom of the plot are created first) if the number of subplots doesn't divide the number of columns evenly, then the first {remainder} number of annotations are made in the bottom row, and then subsequent annotations start the next row up, where the {remainder} = {number of annotations} % {number of columns}  To help visualize: x x x x x x x x ⭠ followed by these ones left to right, ... x x ⭠ these annotations are created first left to right  This means we would like to iterate through (annotation1, x_location_of_col1), (annotation2, x_location_of_col2), (annotation3, x_location_of_col1)... because the placement of the title is based on knowing when the column restarts. In your facet plot there are 10 annotations, 12 total subplots, and 4 columns. Therefore we want to keep track of the x values for each subplot which we can extract from the layouts: the information inside fig.layout['xaxis'], fig.layout['xaxis2']... contain the starting x-values for each subplot in paper coordinates, and we can use the information up to 'xaxis4' (since we have 4 columns), and store this info inside x_axis_start_positions which in our case is [0.0, 0.255, 0.51, 0.7649999999999999] (this is derived in my code, we definitely don't want to hardcode this) Then using the fact that there are 4 columns, 10 annotations, and 12 plots, we can work out that there are 10 // 4 = 2 full rows of plots, and the first row has 10 % 4 = 2 plots in the first row of annotations that are created. We can distill this information into the x starting positions we iterate through for the placement of each title: x_axis_start_positions_iterator = x_axis_start_positions[:remainder] + x_axis_start_positions*number_of_full_rows # [0.0, 0.255, 0.0, 0.255, 0.51, 0.7649999999999999, 0.0, 0.255, 0.51, 0.7649999999999999]  Then we iterate through all 10 annotations and 10 starting positions for the titles, overwriting the positions of the automatically generated annotations. Update: I have wrapped this in a function called left_align_facet_plot_titles that takes a facet plot fig as an input, figures out the number of columns, and left aligns each title. import lorem import plotly.express as px import numpy as np import random items = np.repeat([lorem.sentence() for i in range(10)], 5) response = list(range(1,6)) * 10 n = [random.randint(0, 10) for i in range(50)] fig = ( px.bar(x=response, y=n, facet_col=items, facet_col_wrap=4, height=1300) .for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1])) .for_each_xaxis(lambda xaxis: xaxis.update(showticklabels=True)) .for_each_yaxis(lambda yaxis: yaxis.update(showticklabels=True)) ) def left_align_facet_plot_titles(fig): ## figure out number of columns in each facet facet_col_wrap = len(np.unique([a['x'] for a in fig.layout.annotations])) # x x x x # x x x x <-- then these annotations # x x <-- these annotations are created first ## we need to know the remainder ## because when we iterate through annotations ## they need to know what column they are in ## (and annotations natively contain no such information) remainder = len(fig.data) % facet_col_wrap number_of_full_rows = len(fig.data) // facet_col_wrap annotations = fig.layout.annotations xaxis_col_strings = list(range(1, facet_col_wrap+1)) xaxis_col_strings[0] = '' x_axis_start_positions = [fig.layout[f'xaxis{i}']['domain'][0] for i in xaxis_col_strings] if remainder == 0: x_axis_start_positions_iterator = x_axis_start_positions*number_of_full_rows else: x_axis_start_positions_iterator = x_axis_start_positions[:remainder] + x_axis_start_positions*number_of_full_rows for a, x in zip(annotations, x_axis_start_positions_iterator): a['x'] = x a['xanchor'] = 'left' fig.layout.annotations = annotations return fig fig = left_align_facet_plot_titles(fig) fig.show()   And if we change the number of columns in the figure with fig = px.bar(..., facet_col_wrap=3, ...) and pass this figure to the function, the results are also as expected: