Bar Charts in Python
How to make Bar Charts in Python with Plotly.
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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]:
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]:
Dash Example¶
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]:
Find the dash app source code here.
Reference¶
See https://plot.ly/python/reference/#bar for more information and chart attribute options!
