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go.Table provides a Table object for detailed data viewing. The data are arranged in a grid of rows and columns. Most styling can be specified for header, columns, rows or individual cells. Table is using a column-major order, ie. the grid is represented as a vector of column vectors.

Note that Dash provides a different type of DataTable.

Basic Table¶

In [1]:

import plotly.graph_objects as go

fig = go.Figure(data=[go.Table(header=dict(values=['A Scores', 'B Scores']),
                 cells=dict(values=[[100, 90, 80, 90], [95, 85, 75, 95]]))
                     ])
fig.show()

Styled Table¶

In [2]:

import plotly.graph_objects as go

fig = go.Figure(data=[go.Table(
    header=dict(values=['A Scores', 'B Scores'],
                line_color='darkslategray',
                fill_color='lightskyblue',
                align='left'),
    cells=dict(values=[[100, 90, 80, 90], # 1st column
                       [95, 85, 75, 95]], # 2nd column
               line_color='darkslategray',
               fill_color='lightcyan',
               align='left'))
])

fig.update_layout(width=500, height=300)
fig.show()

Use a Pandas Dataframe¶

In [3]:

import plotly.graph_objects as go
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_usa_states.csv')

fig = go.Figure(data=[go.Table(
    header=dict(values=list(df.columns),
                fill_color='paleturquoise',
                align='left'),
    cells=dict(values=[df.Rank, df.State, df.Postal, df.Population],
               fill_color='lavender',
               align='left'))
])

fig.show()

Tables in Dash¶

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & publish apps like this with Dash Enterprise or Plotly Cloud.

Out[4]:

Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.

Changing Row and Column Size¶

In [5]:

import plotly.graph_objects as go

values = [['Salaries', 'Office', 'Merchandise', 'Legal', '<b>TOTAL<br>EXPENSES</b>'], #1st col
  ["Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
  "Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
  "Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
  "Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
  "Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad"]]


fig = go.Figure(data=[go.Table(
  columnorder = [1,2],
  columnwidth = [80,400],
  header = dict(
    values = [['<b>EXPENSES</b><br>as of July 2017'],
                  ['<b>DESCRIPTION</b>']],
    line_color='darkslategray',
    fill_color='royalblue',
    align=['left','center'],
    font=dict(color='white', size=12),
    height=40
  ),
  cells=dict(
    values=values,
    line_color='darkslategray',
    fill=dict(color=['paleturquoise', 'white']),
    align=['left', 'center'],
    font_size=12,
    height=30)
    )
])
fig.show()

Alternating Row Colors¶

In [6]:

import plotly.graph_objects as go

headerColor = 'grey'
rowEvenColor = 'lightgrey'
rowOddColor = 'white'

fig = go.Figure(data=[go.Table(
  header=dict(
    values=['<b>EXPENSES</b>','<b>Q1</b>','<b>Q2</b>','<b>Q3</b>','<b>Q4</b>'],
    line_color='darkslategray',
    fill_color=headerColor,
    align=['left','center'],
    font=dict(color='white', size=12)
  ),
  cells=dict(
    values=[
      ['Salaries', 'Office', 'Merchandise', 'Legal', '<b>TOTAL</b>'],
      [1200000, 20000, 80000, 2000, 12120000],
      [1300000, 20000, 70000, 2000, 130902000],
      [1300000, 20000, 120000, 2000, 131222000],
      [1400000, 20000, 90000, 2000, 14102000]],
    line_color='darkslategray',
    # 2-D list of colors for alternating rows
    fill_color = [[rowOddColor,rowEvenColor,rowOddColor, rowEvenColor,rowOddColor]*5],
    align = ['left', 'center'],
    font = dict(color = 'darkslategray', size = 11)
    ))
])

fig.show()

Row Color Based on Variable¶

In [7]:

import plotly.graph_objects as go

import pandas as pd

colors = ['rgb(239, 243, 255)', 'rgb(189, 215, 231)', 'rgb(107, 174, 214)',
          'rgb(49, 130, 189)', 'rgb(8, 81, 156)']
data = {'Year' : [2010, 2011, 2012, 2013, 2014], 'Color' : colors}
df = pd.DataFrame(data)

fig = go.Figure(data=[go.Table(
  header=dict(
    values=["Color", "<b>YEAR</b>"],
    line_color='white', fill_color='white',
    align='center', font=dict(color='black', size=12)
  ),
  cells=dict(
    values=[df.Color, df.Year],
    line_color=[df.Color], fill_color=[df.Color],
    align='center', font=dict(color='black', size=11)
  ))
])

fig.show()

Cell Color Based on Variable¶

In [8]:

import plotly.graph_objects as go
from plotly.colors import n_colors
import numpy as np
np.random.seed(1)

colors = n_colors('rgb(255, 200, 200)', 'rgb(200, 0, 0)', 9, colortype='rgb')
a = np.random.randint(low=0, high=9, size=10)
b = np.random.randint(low=0, high=9, size=10)
c = np.random.randint(low=0, high=9, size=10)

fig = go.Figure(data=[go.Table(
  header=dict(
    values=['<b>Column A</b>', '<b>Column B</b>', '<b>Column C</b>'],
    line_color='white', fill_color='white',
    align='center',font=dict(color='black', size=12)
  ),
  cells=dict(
    values=[a, b, c],
    line_color=[np.array(colors)[a],np.array(colors)[b], np.array(colors)[c]],
    fill_color=[np.array(colors)[a],np.array(colors)[b], np.array(colors)[c]],
    align='center', font=dict(color='white', size=11)
    ))
])

fig.show()

Reference¶

For more information on tables and table attributes see: https://plotly.com/python/reference/table/.

What About Dash?¶

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter

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