New to Plotly?¶

Plotly's Python library is free and open source! Get started by downloading the client and reading the primer.
You can set up Plotly to work in online or offline mode, or in jupyter notebooks.
We also have a quick-reference cheatsheet (new!) to help you get started!

Version Check¶

Plotly's python package is updated frequently. Run pip install plotly --upgrade to use the latest version.

In [1]:

import plotly
plotly.__version__

Out[1]:

'2.7.0'

Basic Bar Chart¶

In [2]:

import plotly.plotly as py
import plotly.graph_objs as go

data = [go.Bar(
            x=['giraffes', 'orangutans', 'monkeys'],
            y=[20, 14, 23]
    )]

py.iplot(data, filename='basic-bar')

Out[2]:

Grouped Bar Chart¶

In [3]:

import plotly.plotly as py
import plotly.graph_objs as go

trace1 = go.Bar(
    x=['giraffes', 'orangutans', 'monkeys'],
    y=[20, 14, 23],
    name='SF Zoo'
)
trace2 = go.Bar(
    x=['giraffes', 'orangutans', 'monkeys'],
    y=[12, 18, 29],
    name='LA Zoo'
)

data = [trace1, trace2]
layout = go.Layout(
    barmode='group'
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='grouped-bar')

Out[3]:

Stacked Bar Chart¶

In [4]:

import plotly.plotly as py
import plotly.graph_objs as go

trace1 = go.Bar(
    x=['giraffes', 'orangutans', 'monkeys'],
    y=[20, 14, 23],
    name='SF Zoo'
)
trace2 = go.Bar(
    x=['giraffes', 'orangutans', 'monkeys'],
    y=[12, 18, 29],
    name='LA Zoo'
)

data = [trace1, trace2]
layout = go.Layout(
    barmode='stack'
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='stacked-bar')

Out[4]:

Bar Chart with Hover Text¶

In [5]:

import plotly.plotly as py
import plotly.graph_objs as go

trace0 = go.Bar(
    x=['Product A', 'Product B', 'Product C'],
    y=[20, 14, 23],
    text=['27% market share', '24% market share', '19% market share'],
    marker=dict(
        color='rgb(158,202,225)',
        line=dict(
            color='rgb(8,48,107)',
            width=1.5,
        )
    ),
    opacity=0.6
)

data = [trace0]
layout = go.Layout(
    title='January 2013 Sales Report',
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='text-hover-bar')

Out[5]:

Bar Chart with Direct Labels¶

In [6]:

import plotly.plotly as py
import plotly.graph_objs as go

x = ['Product A', 'Product B', 'Product C']
y = [20, 14, 23]

data = [go.Bar(
            x=x,
            y=y,
            text=y,
            textposition = 'auto',
            marker=dict(
                color='rgb(158,202,225)',
                line=dict(
                    color='rgb(8,48,107)',
                    width=1.5),
            ),
            opacity=0.6
        )]

py.iplot(data, filename='bar-direct-labels')

Out[6]:

Grouped Bar Chart with Direct Labels¶

In [7]:

import plotly.plotly as py
import plotly.graph_objs as go

x = ['Product A', 'Product B', 'Product C']
y = [20, 14, 23]
y2 = [16,12,27]

trace1 = go.Bar(
    x=x,
    y=y,
    text=y,
    textposition = 'auto',
    marker=dict(
        color='rgb(158,202,225)',
        line=dict(
            color='rgb(8,48,107)',
            width=1.5),
        ),
    opacity=0.6
)

trace2 = go.Bar(
    x=x,
    y=y2,
    text=y2,
    textposition = 'auto',
    marker=dict(
        color='rgb(58,200,225)',
        line=dict(
            color='rgb(8,48,107)',
            width=1.5),
        ),
    opacity=0.6
)

data = [trace1,trace2]

py.iplot(data, filename='grouped-bar-direct-labels')

Out[7]:

Rotated Bar Chart Labels¶

In [8]:

import plotly.plotly as py
import plotly.graph_objs as go

trace0 = go.Bar(
    x=['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
       'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
    y=[20, 14, 25, 16, 18, 22, 19, 15, 12, 16, 14, 17],
    name='Primary Product',
    marker=dict(
        color='rgb(49,130,189)'
    )
)
trace1 = go.Bar(
    x=['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
       'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
    y=[19, 14, 22, 14, 16, 19, 15, 14, 10, 12, 12, 16],
    name='Secondary Product',
    marker=dict(
        color='rgb(204,204,204)',
    )
)

data = [trace0, trace1]
layout = go.Layout(
    xaxis=dict(tickangle=-45),
    barmode='group',
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='angled-text-bar')

Out[8]:

Customizing Individual Bar Colors¶

In [9]:

import plotly.plotly as py
import plotly.graph_objs as go

trace0 = go.Bar(
    x=['Feature A', 'Feature B', 'Feature C',
       'Feature D', 'Feature E'],
    y=[20, 14, 23, 25, 22],
    marker=dict(
        color=['rgba(204,204,204,1)', 'rgba(222,45,38,0.8)',
               'rgba(204,204,204,1)', 'rgba(204,204,204,1)',
               'rgba(204,204,204,1)']),
)

data = [trace0]
layout = go.Layout(
    title='Least Used Feature',
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='color-bar')

Out[9]:

Customizing Individual Bar Widths¶

In [10]:

import plotly.plotly as py
import plotly.graph_objs as go

trace0 = go.Bar(
    x=[1, 2, 3, 5.5, 10],
    y=[10, 8, 6, 4, 2],
    width = [0.8, 0.8, 0.8, 3.5, 4]
)

data = [trace0]

fig = go.Figure(data=data)
py.iplot(fig, filename='width-bar')

Out[10]:

Customizing Individual Bar Base¶

In [11]:

import plotly.plotly as py
import plotly.graph_objs as go

data = [
    go.Bar(
        x = ['2016','2017','2018'],
        y = [500,600,700],
        base = [-500,-600,-700],
        marker = dict(
          color = 'red'
        ),
        name = 'expenses'
    ),
    go.Bar(
        x = ['2016','2017','2018'],
        y = [300,400,700],
        base = 0,
        marker = dict(
          color = 'blue'
        ),
        name = 'revenue'
    )
]


fig = go.Figure(data=data)
py.iplot(fig, filename='base-bar')

Out[11]:

Colored and Styled Bar Chart¶

In [12]:

import plotly.plotly as py
import plotly.graph_objs as go

trace1 = go.Bar(
    x=[1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
       2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012],
    y=[219, 146, 112, 127, 124, 180, 236, 207, 236, 263,
       350, 430, 474, 526, 488, 537, 500, 439],
    name='Rest of world',
    marker=dict(
        color='rgb(55, 83, 109)'
    )
)
trace2 = go.Bar(
    x=[1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
       2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012],
    y=[16, 13, 10, 11, 28, 37, 43, 55, 56, 88, 105, 156, 270,
       299, 340, 403, 549, 499],
    name='China',
    marker=dict(
        color='rgb(26, 118, 255)'
    )
)
data = [trace1, trace2]
layout = go.Layout(
    title='US Export of Plastic Scrap',
    xaxis=dict(
        tickfont=dict(
            size=14,
            color='rgb(107, 107, 107)'
        )
    ),
    yaxis=dict(
        title='USD (millions)',
        titlefont=dict(
            size=16,
            color='rgb(107, 107, 107)'
        ),
        tickfont=dict(
            size=14,
            color='rgb(107, 107, 107)'
        )
    ),
    legend=dict(
        x=0,
        y=1.0,
        bgcolor='rgba(255, 255, 255, 0)',
        bordercolor='rgba(255, 255, 255, 0)'
    ),
    barmode='group',
    bargap=0.15,
    bargroupgap=0.1
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='style-bar')

Out[12]:

Waterfall Bar Chart¶

In [13]:

import plotly.plotly as py
import plotly.graph_objs as go

x_data = ['Product<br>Revenue', 'Services<br>Revenue',
          'Total<br>Revenue', 'Fixed<br>Costs',
          'Variable<br>Costs', 'Total<br>Costs', 'Total']
y_data = [400, 660, 660, 590, 400, 400, 340]
text = ['$430K', '$260K', '$690K', '$-120K', '$-200K', '$-320K', '$370K']

# Base
trace0 = go.Bar(
    x=x_data,
    y=[0, 430, 0, 570, 370, 370, 0],
    marker=dict(
        color='rgba(1,1,1, 0.0)',
    )
)
# Revenue
trace1 = go.Bar(
    x=x_data,
    y=[430, 260, 690, 0, 0, 0, 0],
    marker=dict(
        color='rgba(55, 128, 191, 0.7)',
        line=dict(
            color='rgba(55, 128, 191, 1.0)',
            width=2,
        )
    )
)
# Costs
trace2 = go.Bar(
    x=x_data,
    y=[0, 0, 0, 120, 200, 320, 0],
    marker=dict(
        color='rgba(219, 64, 82, 0.7)',
        line=dict(
            color='rgba(219, 64, 82, 1.0)',
            width=2,
        )
    )
)
# Profit
trace3 = go.Bar(
    x=x_data,
    y=[0, 0, 0, 0, 0, 0, 370],
    marker=dict(
        color='rgba(50, 171, 96, 0.7)',
        line=dict(
            color='rgba(50, 171, 96, 1.0)',
            width=2,
        )
    )
)
data = [trace0, trace1, trace2, trace3]
layout = go.Layout(
    title='Annual Profit- 2015',
    barmode='stack',
    paper_bgcolor='rgba(245, 246, 249, 1)',
    plot_bgcolor='rgba(245, 246, 249, 1)',
    showlegend=False
)

annotations = []

for i in range(0, 7):
    annotations.append(dict(x=x_data[i], y=y_data[i], text=text[i],
                                  font=dict(family='Arial', size=14,
                                  color='rgba(245, 246, 249, 1)'),
                                  showarrow=False,))
    layout['annotations'] = annotations

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='waterfall-bar-profit')

Out[13]:

Bar Chart with Relative Barmode¶

In [14]:

x = [1, 2, 3, 4]

trace1 = {
  'x': x,
  'y': [1, 4, 9, 16],
  'name': 'Trace1',
  'type': 'bar'
};
trace2 = {
  'x': x,
  'y': [6, -8, -4.5, 8],
  'name': 'Trace2',
  'type': 'bar'
};
trace3 = {
  'x': x,
  'y': [-15, -3, 4.5, -8],
  'name': 'Trace3',
  'type': 'bar'
 }
 
trace4 = {
  'x': x,
  'y': [-1, 3, -3, -4],
  'name': 'Trace4',
  'type': 'bar'
 }
 
data = [trace1, trace2, trace3, trace4];
layout = {
  'xaxis': {'title': 'X axis'},
  'yaxis': {'title': 'Y axis'},
  'barmode': 'relative',
  'title': 'Relative Barmode'
};
py.iplot({'data': data, 'layout': layout}, filename='barmode-relative')

Out[14]:

Horizontal Bar Charts¶

See examples of horizontal bar charts here.

Dash Example¶

Dash is an Open Source Python library which can help you convert plotly figures into a reactive, web-based application. Below is a simple example of a dashboard created using Dash. Its source code can easily be deployed to a PaaS.

In [1]:

from IPython.display import IFrame
IFrame(src= "https://dash-simple-apps.plotly.host/dash-barplot/", width="100%", height="650px", frameBorder="0")

Out[1]:

In [2]:

from IPython.display import IFrame
IFrame(src= "https://dash-simple-apps.plotly.host/dash-barplot/code", width="80%", height=500, frameBorder="0")

Out[2]:

Reference¶

See https://plotly.com/python/reference/#bar for more information and chart attribute options!

In [4]:

from IPython.display import display, HTML

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" />'))
display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))

#! pip install git+https://github.com/plotly/publisher.git --upgrade
import publisher
publisher.publish(
    'bars.ipynb', 'python/bar-charts/', 'Python Bar Charts | plotly',
    'How to make Bar Charts in Python with Plotly.',
    title = 'Bar Charts | plotly',
    name = 'Bar Charts',
    thumbnail='thumbnail/bar.jpg', language='python',
    page_type='example_index', has_thumbnail='true', display_as='basic', order=4,
    ipynb= '~notebook_demo/186')

Collecting git+https://github.com/plotly/publisher.git
  Cloning https://github.com/plotly/publisher.git to /private/var/folders/s5/vjqn03zs7nn8zs_fwzcf14r40000gn/T/pip-req-build-uj6kwvwa
Building wheels for collected packages: publisher
  Building wheel for publisher (setup.py) ... done
  Stored in directory: /private/var/folders/s5/vjqn03zs7nn8zs_fwzcf14r40000gn/T/pip-ephem-wheel-cache-gf3f4eb5/wheels/99/3e/a0/fbd22ba24cca72bdbaba53dbc23c1768755fb17b3af0f33966
Successfully built publisher
Installing collected packages: publisher
  Found existing installation: publisher 0.13
    Uninstalling publisher-0.13:
      Successfully uninstalled publisher-0.13
Successfully installed publisher-0.13
You are using pip version 19.0.3, however version 19.1.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.