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Merge pull request #13 from plotly/horizontal-bar
horizontal-bar-charts notebook
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‎notebooks/horizontal-bar-charts.md

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@@ -8,9 +8,19 @@ jupyter:
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format_version: '1.1'
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jupytext_version: 1.1.1
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kernelspec:
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display_name: Python 2
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display_name: Python 3
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language: python
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name: python2
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name: python3
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language_info:
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codemirror_mode:
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name: ipython
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version: 3
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file_extension: .py
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mimetype: text/x-python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.6.7
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plotly:
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description: How to make horizontal bar charts in Python with Plotly.
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display_as: basic
@@ -24,80 +34,94 @@ jupyter:
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permalink: python/horizontal-bar-charts/
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thumbnail: thumbnail/horizontal-bar.jpg
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title: Horizontal Bar Charts | plotly
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v4upgrade: true
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---
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#### New to Plotly?
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Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
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<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
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<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!
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#### Version Check
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Plotly's python package is updated frequently. Run `pip install plotly --upgrade` to use the latest version.
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See more examples of bar charts (including vertical bar charts) and styling options [here](https://plot.ly/python/bar-charts/).
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### Horizontal Bar Chart with plotly express
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Plotly express functions take as argument a tidy [pandas DataFrame](https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html). For a horizontal bar char, use the `px.bar` function with `orientation='h'`.
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#### Basic Horizontal Bar Chart with plotly express
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```python
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import plotly.express as px
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tips = px.data.tips()
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fig = px.bar(tips, x="total_bill", y="day", orientation='h')
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fig.show()
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```
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#### Configure horizontal bar chart
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In this example a column is used to color the bars, and we add the information from other columns to the hover data.
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```python
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import plotly
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plotly.__version__
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import plotly.express as px
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tips = px.data.tips()
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fig = px.bar(tips, x="total_bill", y="sex", color='day', orientation='h',
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hover_data=["tip", "size"],
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height=400,
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title='Restaurant bills')
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fig.show()
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```
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### Horizontal Bar Chart with go.Bar
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When data are not available as a tidy dataframe, you can use the more generic function `go.Bar` from `plotly.graph_objects`. All the options of `go.Bar` are documented in the reference https://plot.ly/python/reference/#bar
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#### Basic Horizontal Bar Chart
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import plotly.graph_objects as go
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data = [go.Bar(
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fig = go.Figure(go.Bar(
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x=[20, 14, 23],
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y=['giraffes', 'orangutans', 'monkeys'],
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orientation = 'h'
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)]
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orientation='h'))
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py.iplot(data, filename='horizontal-bar')
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fig.show()
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```
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### Colored Horizontal Bar Chart
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import plotly.graph_objects as go
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trace1 = go.Bar(
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fig = go.Figure()
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fig.add_trace(go.Bar(
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y=['giraffes', 'orangutans', 'monkeys'],
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x=[20, 14, 23],
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name='SF Zoo',
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orientation = 'h',
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marker = dict(
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color = 'rgba(246, 78, 139, 0.6)',
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line = dict(
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color = 'rgba(246, 78, 139, 1.0)',
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width = 3)
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orientation='h',
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marker=dict(
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color='rgba(246, 78, 139, 0.6)',
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line=dict(color='rgba(246, 78, 139, 1.0)', width=3)
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)
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)
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trace2 = go.Bar(
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))
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fig.add_trace(go.Bar(
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y=['giraffes', 'orangutans', 'monkeys'],
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x=[12, 18, 29],
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name='LA Zoo',
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orientation = 'h',
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marker = dict(
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color = 'rgba(58, 71, 80, 0.6)',
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line = dict(
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color = 'rgba(58, 71, 80, 1.0)',
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width = 3)
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orientation='h',
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marker=dict(
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color='rgba(58, 71, 80, 0.6)',
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line=dict(color='rgba(58, 71, 80, 1.0)', width=3)
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)
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)
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data = [trace1, trace2]
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layout = go.Layout(
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barmode='stack'
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)
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))
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fig = go.Figure(data=data, layout=layout)
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py.iplot(fig, filename='marker-h-bar')
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fig.update_layout(barmode='stack')
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fig.show()
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```
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### Color Palette for Bar Chart
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import plotly.graph_objects as go
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top_labels = ['Strongly<br>agree', 'Agree', 'Neutral', 'Disagree',
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'Strongly<br>disagree']
@@ -117,24 +141,20 @@ y_data = ['The course was effectively<br>organized',
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'my<br>ability to think critically about<br>the subject',
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'I would recommend this<br>course to a friend']
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traces = []
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fig = go.Figure()
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for i in range(0, len(x_data[0])):
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for xd, yd in zip(x_data, y_data):
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traces.append(go.Bar(
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x=[xd[i]],
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y=[yd],
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fig.add_trace(go.Bar(
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x=[xd[i]], y=[yd],
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orientation='h',
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marker=dict(
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color=colors[i],
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line=dict(
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color='rgb(248, 248, 249)',
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width=1)
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line=dict(color='rgb(248, 248, 249)', width=1)
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)
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))
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layout = go.Layout(
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fig.update_layout(
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xaxis=dict(
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showgrid=False,
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showline=False,
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barmode='stack',
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paper_bgcolor='rgb(248, 248, 255)',
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plot_bgcolor='rgb(248, 248, 255)',
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margin=dict(
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l=120,
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r=10,
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t=140,
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b=80
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),
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margin=dict(l=120, r=10, t=140, b=80),
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showlegend=False,
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)
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showarrow=False))
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space += xd[i]
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layout['annotations'] = annotations
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fig.update_layout(annotations=annotations)
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fig = go.Figure(data=traces, layout=layout)
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py.iplot(fig, filename='bar-colorscale')
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fig.show()
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```
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### Bar Chart with Line Plot
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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from plotly import tools
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import plotly.graph_objects as go
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from plotly.subplots import make_subplots
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import numpy as np
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@@ -226,14 +239,17 @@ y_saving = [1.3586, 2.2623000000000002, 4.9821999999999997, 6.5096999999999996,
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y_net_worth = [93453.919999999998, 81666.570000000007, 69889.619999999995,
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78381.529999999999, 141395.29999999999, 92969.020000000004,
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66090.179999999993, 122379.3]
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x_saving = ['Japan', 'United Kingdom', 'Canada', 'Netherlands',
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'United States', 'Belgium', 'Sweden', 'Switzerland']
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x_net_worth = ['Japan', 'United Kingdom', 'Canada', 'Netherlands',
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'United States', 'Belgium', 'Sweden', 'Switzerland'
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]
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trace0 = go.Bar(
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x = ['Japan', 'United Kingdom', 'Canada', 'Netherlands',
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'United States', 'Belgium', 'Sweden', 'Switzerland']
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# Creating two subplots
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fig = make_subplots(rows=1, cols=2, specs=[[{}, {}]], shared_xaxes=True,
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shared_yaxes=False, vertical_spacing=0.001)
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fig.append_trace(go.Bar(
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x=y_saving,
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y=x_saving,
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y=x,
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marker=dict(
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color='rgba(50, 171, 96, 0.6)',
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line=dict(
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),
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name='Household savings, percentage of household disposable income',
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orientation='h',
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)
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trace1 = go.Scatter(
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x=y_net_worth,
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y=x_net_worth,
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), 1, 1)
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fig.append_trace(go.Scatter(
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x=y_net_worth, y=x,
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mode='lines+markers',
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line=dict(
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color='rgb(128, 0, 128)'),
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line_color='rgb(128, 0, 128)',
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name='Household net worth, Million USD/capita',
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)
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layout = dict(
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), 1, 2)
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fig.update_layout(
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title='Household savings & net worth for eight OECD countries',
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yaxis=dict(
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showgrid=False,
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side='top',
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dtick=25000,
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),
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legend=dict(
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x=0.029,
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y=1.038,
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font=dict(
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size=10,
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),
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),
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margin=dict(
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l=100,
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r=20,
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t=70,
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b=70,
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),
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legend=dict(x=0.029, y=1.038, font_size=10),
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margin=dict(l=100, r=20, t=70, b=70),
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paper_bgcolor='rgb(248, 248, 255)',
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plot_bgcolor='rgb(248, 248, 255)',
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)
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y_nw = np.rint(y_net_worth)
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# Adding labels
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for ydn, yd, xd in zip(y_nw, y_s, x_saving):
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for ydn, yd, xd in zip(y_nw, y_s, x):
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# labeling the scatter savings
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annotations.append(dict(xref='x2', yref='y2',
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y=xd, x=ydn - 20000,
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'(2015), Household savings (indicator), ' +
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'Household net worth (indicator). doi: ' +
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'10.1787/cfc6f499-en (Accessed on 05 June 2015)',
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font=dict(family='Arial', size=10,
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color='rgb(150,150,150)'),
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font=dict(family='Arial', size=10, color='rgb(150,150,150)'),
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showarrow=False))
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layout['annotations'] = annotations
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# Creating two subplots
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fig = tools.make_subplots(rows=1, cols=2, specs=[[{}, {}]], shared_xaxes=True,
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shared_yaxes=False, vertical_spacing=0.001)
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fig.append_trace(trace0, 1, 1)
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fig.append_trace(trace1, 1, 2)
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fig.update_layout(annotations=annotations)
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fig['layout'].update(layout)
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py.iplot(fig, filename='oecd-networth-saving-bar-line')
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fig.show()
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```
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### Reference
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See more examples of bar charts and styling options [here](https://plot.ly/python/bar-charts/).<br> See https://plot.ly/python/reference/#bar for more information and chart attribute options!
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```python
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from IPython.display import display, HTML
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display(HTML('<link href="//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700" rel="stylesheet" type="text/css" />'))
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display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))
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#! pip install git+https://github.com/plotly/publisher.git --upgrade
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import publisher
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publisher.publish(
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'horizontal-bars.ipynb', 'python/horizontal-bar-charts/', 'Horizontal Bar Charts | plotly',
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'How to make horizontal bar charts in Python with Plotly.',
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title = 'Horizontal Bar Charts | plotly',
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name = 'Horizontal Bar Charts',
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thumbnail='thumbnail/horizontal-bar.jpg', language='python',
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has_thumbnail='true', display_as='basic', order=5,
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ipynb= '~notebook_demo/5')
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```
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```python
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```

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