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See more examples of bar charts (including vertical bar charts) and styling options here.
Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures. For a horizontal bar char, use the px.bar function with orientation='h'.
import plotly.express as px
df = px.data.tips()
fig = px.bar(df, x="total_bill", y="day", orientation='h')
fig.show()In this example a column is used to color the bars, and we add the information from other columns to the hover data.
import plotly.express as px
df = px.data.tips()
fig = px.bar(df, x="total_bill", y="sex", color='day', orientation='h',
hover_data=["tip", "size"],
height=400,
title='Restaurant bills')
fig.show()You can also use the more generic go.Bar class from plotly.graph_objects. All the options of go.Bar are documented in the reference https://plotly.com/python/reference/bar/
import plotly.graph_objects as go
fig = go.Figure(go.Bar(
x=[20, 14, 23],
y=['giraffes', 'orangutans', 'monkeys'],
orientation='h'))
fig.show()import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Bar(
y=['giraffes', 'orangutans', 'monkeys'],
x=[20, 14, 23],
name='SF Zoo',
orientation='h',
marker=dict(
color='rgba(246, 78, 139, 0.6)',
line=dict(color='rgba(246, 78, 139, 1.0)', width=3)
)
))
fig.add_trace(go.Bar(
y=['giraffes', 'orangutans', 'monkeys'],
x=[12, 18, 29],
name='LA Zoo',
orientation='h',
marker=dict(
color='rgba(58, 71, 80, 0.6)',
line=dict(color='rgba(58, 71, 80, 1.0)', width=3)
)
))
fig.update_layout(barmode='stack')
fig.show()import plotly.graph_objects as go
top_labels = ['Strongly<br>agree', 'Agree', 'Neutral', 'Disagree',
'Strongly<br>disagree']
colors = ['rgba(38, 24, 74, 0.8)', 'rgba(71, 58, 131, 0.8)',
'rgba(122, 120, 168, 0.8)', 'rgba(164, 163, 204, 0.85)',
'rgba(190, 192, 213, 1)']
x_data = [[21, 30, 21, 16, 12],
[24, 31, 19, 15, 11],
[27, 26, 23, 11, 13],
[29, 24, 15, 18, 14]]
y_data = ['The course was effectively<br>organized',
'The course developed my<br>abilities and skills ' +
'for<br>the subject', 'The course developed ' +
'my<br>ability to think critically about<br>the subject',
'I would recommend this<br>course to a friend']
fig = go.Figure()
for i in range(0, len(x_data[0])):
for xd, yd in zip(x_data, y_data):
fig.add_trace(go.Bar(
x=[xd[i]], y=[yd],
orientation='h',
marker=dict(
color=colors[i],
line=dict(color='rgb(248, 248, 249)', width=1)
)
))
fig.update_layout(
xaxis=dict(
showgrid=False,
showline=False,
showticklabels=False,
zeroline=False,
domain=[0.15, 1]
),
yaxis=dict(
showgrid=False,
showline=False,
showticklabels=False,
zeroline=False,
),
barmode='stack',
paper_bgcolor='rgb(248, 248, 255)',
plot_bgcolor='rgb(248, 248, 255)',
margin=dict(l=120, r=10, t=140, b=80),
showlegend=False,
)
annotations = []
for yd, xd in zip(y_data, x_data):
# labeling the y-axis
annotations.append(dict(xref='paper', yref='y',
x=0.14, y=yd,
xanchor='right',
text=str(yd),
font=dict(family='Arial', size=14,
color='rgb(67, 67, 67)'),
showarrow=False, align='right'))
# labeling the first percentage of each bar (x_axis)
annotations.append(dict(xref='x', yref='y',
x=xd[0] / 2, y=yd,
text=str(xd[0]) + '%',
font=dict(family='Arial', size=14,
color='rgb(248, 248, 255)'),
showarrow=False))
# labeling the first Likert scale (on the top)
if yd == y_data[-1]:
annotations.append(dict(xref='x', yref='paper',
x=xd[0] / 2, y=1.1,
text=top_labels[0],
font=dict(family='Arial', size=14,
color='rgb(67, 67, 67)'),
showarrow=False))
space = xd[0]
for i in range(1, len(xd)):
# labeling the rest of percentages for each bar (x_axis)
annotations.append(dict(xref='x', yref='y',
x=space + (xd[i]/2), y=yd,
text=str(xd[i]) + '%',
font=dict(family='Arial', size=14,
color='rgb(248, 248, 255)'),
showarrow=False))
# labeling the Likert scale
if yd == y_data[-1]:
annotations.append(dict(xref='x', yref='paper',
x=space + (xd[i]/2), y=1.1,
text=top_labels[i],
font=dict(family='Arial', size=14,
color='rgb(67, 67, 67)'),
showarrow=False))
space += xd[i]
fig.update_layout(annotations=annotations)
fig.show()import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np
y_saving = [1.3586, 2.2623000000000002, 4.9821999999999997, 6.5096999999999996,
7.4812000000000003, 7.5133000000000001, 15.2148, 17.520499999999998
]
y_net_worth = [93453.919999999998, 81666.570000000007, 69889.619999999995,
78381.529999999999, 141395.29999999999, 92969.020000000004,
66090.179999999993, 122379.3]
x = ['Japan', 'United Kingdom', 'Canada', 'Netherlands',
'United States', 'Belgium', 'Sweden', 'Switzerland']
# Creating two subplots
fig = make_subplots(rows=1, cols=2, specs=[[{}, {}]], shared_xaxes=True,
shared_yaxes=False, vertical_spacing=0.001)
fig.append_trace(go.Bar(
x=y_saving,
y=x,
marker=dict(
color='rgba(50, 171, 96, 0.6)',
line=dict(
color='rgba(50, 171, 96, 1.0)',
width=1),
),
name='Household savings, percentage of household disposable income',
orientation='h',
), 1, 1)
fig.append_trace(go.Scatter(
x=y_net_worth, y=x,
mode='lines+markers',
line_color='rgb(128, 0, 128)',
name='Household net worth, Million USD/capita',
), 1, 2)
fig.update_layout(
title=dict(text='Household savings & net worth for eight OECD countries'),
yaxis=dict(
showgrid=False,
showline=False,
showticklabels=True,
domain=[0, 0.85],
),
yaxis2=dict(
showgrid=False,
showline=True,
showticklabels=False,
linecolor='rgba(102, 102, 102, 0.8)',
linewidth=2,
domain=[0, 0.85],
),
xaxis=dict(
zeroline=False,
showline=False,
showticklabels=True,
showgrid=True,
domain=[0, 0.42],
),
xaxis2=dict(
zeroline=False,
showline=False,
showticklabels=True,
showgrid=True,
domain=[0.47, 1],
side='top',
dtick=25000,
),
legend=dict(x=0.029, y=1.038, font_size=10),
margin=dict(l=100, r=20, t=70, b=70),
paper_bgcolor='rgb(248, 248, 255)',
plot_bgcolor='rgb(248, 248, 255)',
)
annotations = []
y_s = np.round(y_saving, decimals=2)
y_nw = np.rint(y_net_worth)
# Adding labels
for ydn, yd, xd in zip(y_nw, y_s, x):
# labeling the scatter savings
annotations.append(dict(xref='x2', yref='y2',
y=xd, x=ydn - 20000,
text='{:,}'.format(ydn) + 'M',
font=dict(family='Arial', size=12,
color='rgb(128, 0, 128)'),
showarrow=False))
# labeling the bar net worth
annotations.append(dict(xref='x1', yref='y1',
y=xd, x=yd + 3,
text=str(yd) + '%',
font=dict(family='Arial', size=12,
color='rgb(50, 171, 96)'),
showarrow=False))
# Source
annotations.append(dict(xref='paper', yref='paper',
x=-0.2, y=-0.109,
text='OECD "' +
'(2015), Household savings (indicator), ' +
'Household net worth (indicator). doi: ' +
'10.1787/cfc6f499-en (Accessed on 05 June 2015)',
font=dict(family='Arial', size=10, color='rgb(150,150,150)'),
showarrow=False))
fig.update_layout(annotations=annotations)
fig.show()See more examples of bar charts and styling options here.
See https://plotly.com/python/reference/bar/ for more information and chart attribute options!