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Tables in Python

How to make tables in Python with Plotly.

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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.

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()

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()

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()

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.

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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()

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()

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()

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()

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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