如何在 plotly（python）中双向 plot plot，两侧均带有正标签？

Question

I'm trying to create a bi-directional barplot using Plotly in Python. I have used the code given at this link: bi-directional bar chart with annotation in python plotly

CODE:

import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots

# define data set
s1 = pd.Series(["negative_regulation_of_axon_extension_involved_in_axon_guidance",4,"regulation_of_neuronal_synaptic_plasticity",5])
s2 = pd.Series(["neuronal_stem_cell_population_maintenance",4,"synapse_assembly",8])
s3 = pd.Series(["neural_crest_cell_migration",5,"neuron_differentiation",11])
s4 = pd.Series(["chromatin_silencing",5,"axon_guidance",15])
s5 = pd.Series(["neuron_differentiation",28,"signal_transduction",113])
df = pd.DataFrame([list(s1),list(s2),list(s3),list(s4),list(s5)], columns = ['label1','value1','label2','value2'])

# create subplots
fig = make_subplots(rows=1, cols=2, specs=[[{}, {}]], shared_xaxes=True,
                    shared_yaxes=True, horizontal_spacing=0)

fig.append_trace(go.Bar(y=df.index, x=df.value1, orientation='h', width=0.4, showlegend=False, marker_color='#4472c4'), 1, 1)
fig.append_trace(go.Bar(y=df.index, x=df.value2, orientation='h', width=0.4, showlegend=False, marker_color='#ed7d31'), 1, 2)
fig.update_yaxes(showticklabels=False) # hide all yticks

annotations = []
for i, row in df.iterrows():
    if row.label1 != '':
        annotations.append({
            'xref': 'x1',
            'yref': 'y1',
            'y': i,
            'x': row.value1,
            'text': row.value1,
            'xanchor': 'right',
            'showarrow': False})
        annotations.append({
            'xref': 'x1',
            'yref': 'y1',
            'y': i-0.3,
            'x': -1,
            'text': row.label1,
            'xanchor': 'right',
            'showarrow': False})            
    if row.label2 != '':
        annotations.append({
            'xref': 'x2',
            'yref': 'y2',
            'y': i,
            'x': row.value2,
            'text': row.value2,
            'xanchor': 'left',
            'showarrow': False})  
        annotations.append({
            'xref': 'x2',
            'yref': 'y2',
            'y': i-0.3,
            'x': 1,
            'text': row.label2,
            'xanchor': 'left',
            'showarrow': False})

fig.update_layout(annotations=annotations)
fig.show()

I'm facing a couple of problems:

1. In my original data I have data with positive numbers only. But when I'm trying to plot the above data using this code the axis is getting distorted something like this:

Although if I'm providing the negative numbers for one dataset it's working fine:

data:

s1 = pd.Series(["negative_regulation_of_axon_extension_involved_in_axon_guidance",-4,"regulation_of_neuronal_synaptic_plasticity",5])
s2 = pd.Series(["neuronal_stem_cell_population_maintenance",-4,"synapse_assembly",8])
s3 = pd.Series(["neural_crest_cell_migration",-5,"neuron_differentiation",11])
s4 = pd.Series(["chromatin_silencing",-5,"axon_guidance",15])
s5 = pd.Series(["neuron_differentiation",-28,"signal_transduction",113])
df = pd.DataFrame([list(s1),list(s2),list(s3),list(s4),list(s5)], columns = ['label1','value1','label2','value2'])

result:

How to customize the same for the data when I have positive numbers for both axis, so that plot looks like the second image only but has positive numbers on the opposite axis?

2. If we look at the bars in the second image because of the axis, the bar for 4 seems to be bigger than the bar for 8 or 11 on the other side, Will it be possible to change it to relative somehow?

Thank you.

Answer 1

• a different approach using Plotly Express
• start by restructuring data frame to:

group	label	value
1	negative_regulation_of_axon_extension_involved_in_axon_guidance	4
1	neuronal_stem_cell_population_maintenance	4
1	neural_crest_cell_migration	5
1	chromatin_silencing	5
1	neuron_differentiation	28
2	regulation_of_neuronal_synaptic_plasticity	5
2	synapse_assembly	8
2	neuron_differentiation	11
2	axon_guidance	15
2	signal_transduction	113

• now can do a use group for color and facet_col
• finally format all the axes and layout to achieve your required outcome

import plotly.express as px
import pandas as pd

# define data set
s1 = pd.Series(
    [
        "negative_regulation_of_axon_extension_involved_in_axon_guidance",
        4,
        "regulation_of_neuronal_synaptic_plasticity",
        5,
    ]
)
s2 = pd.Series(["neuronal_stem_cell_population_maintenance", 4, "synapse_assembly", 8])
s3 = pd.Series(["neural_crest_cell_migration", 5, "neuron_differentiation", 11])
s4 = pd.Series(["chromatin_silencing", 5, "axon_guidance", 15])
s5 = pd.Series(["neuron_differentiation", 28, "signal_transduction", 113])
df = pd.DataFrame(
    [list(s1), list(s2), list(s3), list(s4), list(s5)],
    columns=["label1", "value1", "label2", "value2"],
)

fig = px.bar(
    pd.wide_to_long(
        df.reset_index(), stubnames=["label", "value"], i="index", j="group"
    )
    .reset_index()
    .drop(columns="index")
    .assign(group=lambda d: d["group"].astype(str)),
    y="label",
    x="value",
    facet_col="group",
    facet_col_spacing=10 ** -9,
    color="group",
    color_discrete_sequence=["#4472c4", "#ed7d31"],
)

fig.update_layout(
    yaxis2={"side": "right", "matches": None, "showticklabels": False},
    yaxis={"showticklabels": False},
    xaxis={"autorange": "reversed"},
    xaxis2={"matches": None},
    showlegend=False,
)
fig.for_each_annotation(lambda a: a.update(text=""))
fig.update_traces(texttemplate="%{y}", textposition="auto")