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Figure Factory Tables in Python/v3

How to make tables in Python with Plotly's Figure Factory.


Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.

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Version Check

Note: Tables are available in version 1.9.2+
Run pip install plotly --upgrade to update your Plotly version

In [3]:
import plotly
plotly.__version__
Out[3]:
'2.4.1'

Simple Table

In [4]:
import plotly.plotly as py
import plotly.figure_factory as ff

data_matrix = [['Country', 'Year', 'Population'],
               ['United States', 2000, 282200000],
               ['Canada', 2000, 27790000],
               ['United States', 2005, 295500000],
               ['Canada', 2005, 32310000],
               ['United States', 2010, 309000000],
               ['Canada', 2010, 34000000]]

table = ff.create_table(data_matrix)
py.iplot(table, filename='simple_table')
Out[4]:
In [5]:
import plotly.plotly as py
import plotly.figure_factory as ff

data_matrix = [['User', 'Language', 'Chart Type', '# of Views'],
               ['<a href="https://plotly.com/~empet/folder/home">empet</a>',
                '<a href="https://plotly.com/python/">Python</a>',
                '<a href="https://plotly.com/~empet/8614/">Network Graph</a>',
                298],
               ['<a href="https://plotly.com/~Grondo/folder/home">Grondo</a>',
                '<a href="https://plotly.com/matlab/">Matlab</a>',
                '<a href="https://plotly.com/~Grondo/42/">Subplots</a>',
                356],
               ['<a href="https://plotly.com/~Dreamshot/folder/home">Dreamshot</a>',
                '<a href="https://help.plot.ly/tutorials/">Web App</a>',
                '<a href="https://plotly.com/~Dreamshot/6575/_2014-us-city-populations/">Bubble Map</a>',
                262],
               ['<a href="https://plotly.com/~FiveThirtyEight/folder/home">FiveThirtyEight</a>',
                '<a href="https://help.plot.ly/tutorials/">Web App</a>',
                '<a href="https://plotly.com/~FiveThirtyEight/30/">Scatter</a>',
                692],
               ['<a href="https://plotly.com/~cpsievert/folder/home">cpsievert</a>',
                '<a href="https://plotly.com/r/">R</a>',
                '<a href="https://plotly.com/~cpsievert/1130/">Surface</a>',
                302]]

table = ff.create_table(data_matrix)
py.iplot(table, filename='linked_table')
Out[5]:

Use LaTeX

In [6]:
import plotly.plotly as py
import plotly.figure_factory as ff

data_matrix = [['Name', 'Equation'],
               ['Pythagorean Theorem', '$a^{2}+b^{2}=c^{2}$'],
               ['Euler\'s Formula', '$F-E+V=2$'],
               ['The Origin of Complex Numbers', '$i^{2}=-1$'],
               ['Einstein\'s Theory of Relativity', '$E=m c^{2}$']]

table = ff.create_table(data_matrix)
py.iplot(table, filename='latex_table')
Out[6]:

Use a Panda's Dataframe

In [7]:
import plotly.plotly as py
import plotly.figure_factory as ff

import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv')
df_sample = df[100:120]

table = ff.create_table(df_sample)
py.iplot(table, filename='pandas_table')
Out[7]:

Modify Row Height

The default row height is 30 pixels. Set height_constant if you'd like to change the height of each row.

In [8]:
import plotly.plotly as py
import plotly.figure_factory as ff

data_matrix = [['Country', 'Year', 'Population'],
               ['United States', 2000, 282200000],
               ['Canada', 2000, 27790000],
               ['United States', 2005, 295500000],
               ['Canada', 2005, 32310000],
               ['United States', 2010, 309000000],
               ['Canada', 2010, 34000000]]

table = ff.create_table(data_matrix, height_constant=20)
py.iplot(table, filename='size_row_table')
Out[8]:

Custom Table Colors

A custom colorscale should be a list[list]:
[[0, 'Header_Color'],[.5, 'Odd_Row_Color'],[1, 'Even_Row_Color']]

In [9]:
import plotly.plotly as py
import plotly.figure_factory as ff

import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv')
df_sample = df[400:410]

colorscale = [[0, '#4d004c'],[.5, '#f2e5ff'],[1, '#ffffff']]

table = ff.create_table(df_sample, colorscale=colorscale)
py.iplot(table, filename='color_table')
Out[9]:

Custom Font Colors

In [10]:
import plotly.plotly as py
import plotly.figure_factory as ff

text = [['Team', 'Rank'], ['A', 1], ['B', 2], ['C', 3], ['D', 4], ['E', 5], ['F', 6]]

colorscale = [[0, '#272D31'],[.5, '#ffffff'],[1, '#ffffff']]
font=['#FCFCFC', '#00EE00', '#008B00', '#004F00', '#660000', '#CD0000', '#FF3030']

table = ff.create_table(text, colorscale=colorscale, font_colors=font)
table.layout.width=250
py.iplot(table, filename='font_table')
Out[10]:

Change Font Size

In [11]:
import plotly.plotly as py
import plotly.figure_factory as ff

data_matrix = [['Country', 'Year', 'Population'],
               ['United States', 2000, 282200000],
               ['Canada', 2000, 27790000],
               ['United States', 2005, 295500000],
               ['Canada', 2005, 32310000],
               ['United States', 2010, 309000000],
               ['Canada', 2010, 34000000]]

table = ff.create_table(data_matrix, index=True)

# Make text size larger
for i in range(len(table.layout.annotations)):
    table.layout.annotations[i].font.size = 20

py.iplot(table, filename='index_table')
Out[11]:

Tables with Graphs

In [12]:
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.figure_factory as ff

# Add table data
table_data = [['Team', 'Wins', 'Losses', 'Ties'],
              ['Montréal<br>Canadiens', 18, 4, 0],
              ['Dallas Stars', 18, 5, 0],
              ['NY Rangers', 16, 5, 0],
              ['Boston<br>Bruins', 13, 8, 0],
              ['Chicago<br>Blackhawks', 13, 8, 0],
              ['LA Kings', 13, 8, 0],
              ['Ottawa<br>Senators', 12, 5, 0]]
# Initialize a figure with FF.create_table(table_data)
figure = ff.create_table(table_data, height_constant=60)

# Add graph data
teams = ['Montréal Canadiens', 'Dallas Stars', 'NY Rangers',
         'Boston Bruins', 'Chicago Blackhawks', 'LA Kings', 'Ottawa Senators']
GFPG = [3.54, 3.48, 3.0, 3.27, 2.83, 2.45, 3.18]
GAPG = [2.17, 2.57, 2.0, 2.91, 2.57, 2.14, 2.77]
# Make traces for graph
trace1 = go.Scatter(x=teams, y=GFPG,
                    marker=dict(color='#0099ff'),
                    name='Goals For<br>Per Game',
                    xaxis='x2', yaxis='y2')
trace2 = go.Scatter(x=teams, y=GAPG,
                    marker=dict(color='#404040'),
                    name='Goals Against<br>Per Game',
                    xaxis='x2', yaxis='y2')

# Add trace data to figure
figure['data'].extend(go.Data([trace1, trace2]))

# Edit layout for subplots
figure.layout.xaxis.update({'domain': [0, .5]})
figure.layout.xaxis2.update({'domain': [0.6, 1.]})
# The graph's yaxis MUST BE anchored to the graph's xaxis
figure.layout.yaxis2.update({'anchor': 'x2'})
figure.layout.yaxis2.update({'title': 'Goals'})
# Update the margins to add a title and see graph x-labels. 
figure.layout.margin.update({'t':50, 'b':100})
figure.layout.update({'title': '2016 Hockey Stats'})

# Plot!
py.iplot(figure, filename='subplot_table')
Out[12]:
In [13]:
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.figure_factory as FF

# Add table data
table_data = [['Team', 'Wins', 'Losses', 'Ties'],
              ['Montréal<br>Canadiens', 18, 4, 0],
              ['Dallas Stars', 18, 5, 0],
              ['NY Rangers', 16, 5, 0],
              ['Boston<br>Bruins', 13, 8, 0],
              ['Chicago<br>Blackhawks', 13, 8, 0],
              ['Ottawa<br>Senators', 12, 5, 0]]
# Initialize a figure with FF.create_table(table_data)
figure = FF.create_table(table_data, height_constant=60)

# Add graph data
teams = ['Montréal Canadiens', 'Dallas Stars', 'NY Rangers',
         'Boston Bruins', 'Chicago Blackhawks', 'Ottawa Senators']
GFPG = [3.54, 3.48, 3.0, 3.27, 2.83, 3.18]
GAPG = [2.17, 2.57, 2.0, 2.91, 2.57, 2.77]
# Make traces for graph
trace1 = go.Bar(x=teams, y=GFPG, xaxis='x2', yaxis='y2',
                marker=dict(color='#0099ff'),
                name='Goals For<br>Per Game')
trace2 = go.Bar(x=teams, y=GAPG, xaxis='x2', yaxis='y2',
                marker=dict(color='#404040'),
                name='Goals Against<br>Per Game')

# Add trace data to figure
figure['data'].extend(go.Data([trace1, trace2]))

# Edit layout for subplots
figure.layout.yaxis.update({'domain': [0, .45]})
figure.layout.yaxis2.update({'domain': [.6, 1]})
# The graph's yaxis2 MUST BE anchored to the graph's xaxis2 and vice versa
figure.layout.yaxis2.update({'anchor': 'x2'})
figure.layout.xaxis2.update({'anchor': 'y2'})
figure.layout.yaxis2.update({'title': 'Goals'})
# Update the margins to add a title and see graph x-labels. 
figure.layout.margin.update({'t':75, 'l':50})
figure.layout.update({'title': '2016 Hockey Stats'})
# Update the height because adding a graph vertically will interact with
# the plot height calculated for the table
figure.layout.update({'height':800})

# Plot!
py.iplot(figure, filename='subplot_table_vertical')
Out[13]:
In [14]:
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.figure_factory as ff

# Add table data
table_data = [['Prominence', 'Percent', 'RGB Value'],
              [1, '38%', 'rgb(56, 75, 126)'],
              [2, '27%', 'rgb(18, 36, 37)'],
              [3, '18%', 'rgb(34, 53, 101)'],
              [4, '10%', 'rgb(36, 55, 57)'],
              [5, '7%', 'rgb(6, 4, 4)']]
# Initialize a figure with ff.create_table(table_data)
figure = ff.create_table(table_data, height_constant=60)

# Add graph data
trace1={'labels': ['1st', '2nd', '3rd', '4th', '5th'],
        'values': [38, 27, 18, 10, 7],
        'type': 'pie',
        'name': 'Starry Night',
        'marker': {'colors': ['rgb(56, 75, 126)',
                              'rgb(18, 36, 37)',
                              'rgb(34, 53, 101)',
                              'rgb(36, 55, 57)',
                              'rgb(6, 4, 4)']},
            'domain': {'x': [0, 1],
                       'y': [.4, 1]},
            'hoverinfo':'label+percent+name',
            'textinfo':'none'
        }

# Add trace data to figure
figure['data'].extend(go.Data([trace1]))

# Edit layout for subplots
figure.layout.yaxis.update({'domain': [0, .30]})
# The graph's yaxis2 MUST BE anchored to the graph's xaxis2 and vice versa
# Update the margins to add a title and see graph x-labels. 
figure.layout.margin.update({'t':75, 'l':50})
figure.layout.update({'title': 'Starry Night'})
# Update the height because adding a graph vertically will interact with
# the plot height calculated for the table
figure.layout.update({'height':800})

# Plot!
py.iplot(figure)
Out[14]:

Reference

In [15]:
help(ff.create_table)

Help on function create_table in module plotly.figure_factory._table:

create_table(table_text, colorscale=None, font_colors=None, index=False, index_title='', annotation_offset=0.45, height_constant=30, hoverinfo='none', **kwargs)
    BETA function that creates data tables

    :param (pandas.Dataframe | list[list]) text: data for table.
    :param (str|list[list]) colorscale: Colorscale for table where the
        color at value 0 is the header color, .5 is the first table color
        and 1 is the second table color. (Set .5 and 1 to avoid the striped
        table effect). Default=[[0, '#66b2ff'], [.5, '#d9d9d9'],
        [1, '#ffffff']]
    :param (list) font_colors: Color for fonts in table. Can be a single
        color, three colors, or a color for each row in the table.
        Default=['#000000'] (black text for the entire table)
    :param (int) height_constant: Constant multiplied by # of rows to
        create table height. Default=30.
    :param (bool) index: Create (header-colored) index column index from
        Pandas dataframe or list[0] for each list in text. Default=False.
    :param (string) index_title: Title for index column. Default=''.
    :param kwargs: kwargs passed through plotly.graph_objs.Heatmap.
        These kwargs describe other attributes about the annotated Heatmap
        trace such as the colorscale. For more information on valid kwargs
        call help(plotly.graph_objs.Heatmap)

    Example 1: Simple Plotly Table
    ```
    import plotly.plotly as py
    from plotly.figure_factory import create_table

    text = [['Country', 'Year', 'Population'],
            ['US', 2000, 282200000],
            ['Canada', 2000, 27790000],
            ['US', 2010, 309000000],
            ['Canada', 2010, 34000000]]

    table = create_table(text)
    py.iplot(table)
    ```

    Example 2: Table with Custom Coloring
    ```
    import plotly.plotly as py
    from plotly.figure_factory import create_table

    text = [['Country', 'Year', 'Population'],
            ['US', 2000, 282200000],
            ['Canada', 2000, 27790000],
            ['US', 2010, 309000000],
            ['Canada', 2010, 34000000]]

    table = create_table(text,
                         colorscale=[[0, '#000000'],
                                     [.5, '#80beff'],
                                     [1, '#cce5ff']],
                         font_colors=['#ffffff', '#000000',
                                    '#000000'])
    py.iplot(table)
    ```
    Example 3: Simple Plotly Table with Pandas
    ```
    import plotly.plotly as py
    from plotly.figure_factory import create_table

    import pandas as pd

    df = pd.read_csv('http://www.stat.ubc.ca/~jenny/notOcto/STAT545A/examples/gapminder/data/gapminderDataFiveYear.txt', sep='  ')
    df_p = df[0:25]

    table_simple = create_table(df_p)
    py.iplot(table_simple)
    ```