Plotly Library Functions in Python

Plotly is a library use for data visualization. Users can visualize and analyse the data online. This library is use for developing interactive graphs and charts. It is Free and open source plotting library that allows nearly about 40 unique chart and plot types, covering a huge range of algebraic, economical, geographical 3 -Dimensional and scientific user cases. Plotly library of python is develops on the top of Plotly JS.

Installation

pip install plotly

Package Structure

Plotly package has three main modules are Following :-

1. plotly.tools
2. plotly.plotly
3. plotly.graph_objs

Plotly tools

This module contains many helpful functions facilitating and enhancing the Plotly is knows as plotly.tools

Plotly graph object

This module is the most important module that contains all of the class definitions for the objects is knows as plotly.graph_objs.

There are following graph object

• Figure,
• Data,
• Layout,
• Different graph traces

Scatter Plot

Scatter plot represent values for two different numeric variable is knows as Scatter Plot.

Example of Scatter Plot

importnumpy as np
importplotly
importplotly.graph_objects as go
importplotly.offline as pyo
fromplotly.offline importinit_notebook_mode
init_notebook_mode(connected=True)
x =np.random.randint(low=2, high=53, size=154)0.1 y =np.random.randint(low=2, high=53, size=154)0.1
fig =go.Figure(data=go.Scatter(x=x, y=y, mode=’markers’))
fig.show()

Output of Scatter Plot

Bar charts

Bar charts are use to compare different groups of data and make inferences is knows as Bar charts

Example of Bar charts

importnumpy as np

importplotly

importplotly.graph_objects as goo

importplotly.offline as pyo

fromplotly.offline importinit_notebook_mode

init_notebook_mode(connected =True)

countries=[‘India’, ‘canada’ , ‘Australia’,’Brazil’, ‘Mexico’,’Russia’ , ‘Germany’,’Switzerland’,  ‘Texas’]

responding y for each

fig =go.Figure([go.Bar(x=countries,

 y=[80,70,60,50, 40,50,60,70,80])])

fig.show()

Output of Bar charts

Pie chart

A pie chart represents the distribution of different variables among total is knows as Pie chart.

Example of pie chart

import numpy as np

import plotly

import plotly.graph_objects as go

import plotly.offline as pyo

from plotly.offline import init_notebook_mode

init_notebook_mode(connected = True

countries=[‘India’, ‘canada’,’Australia’,’Brazil’,’Mexico’,’Russia’,’Germany’,’Switzerland’,’Texas’]

values = [4505, 2507, 1053, 550,3205, 1507, 1250, 595, 3496]

fig = go.Figure(data=[go.Pie(labels=countries,values=values)])

fig.show()

Output of pie chart

Histogram

This plots the continuous distribution of variable as series of bars is knows as Histogram.

Example of Histogram

import numpy as np

import plotly

import plotly.graph_objects as go

import plotly.offline as pyo

from plotly.offline import init_notebook_mode

init_notebook_mode(connected = True)

np.random.seed(41)

x = np.random.randn(252)

fig = go.Figure(data=[go.Histogram(x=x)])

fig.show()

Output of Histogram

Box plot

This plot is the representation of a statistical summary. Minimum, First Quartile, Median, Third Quartile, Maximum is knows as Box Plot

Example of Box Plot

import numpy as np

import plotly

import plotly.graph_objects as go

import plotly.offline as pyo

from plotly.offline import init_notebook_mode

init_notebook_mode(connected = True)

np.random.seed(40)

y = np.random.randn(52)

y1 = np.random.randn(52)

fig = go.Figure()

fig.add_trace(go.Box(y=y))

fig.add_trace(go.Box(y=y1))

fig.show()

Output of Box Plot

Online and Offline Plotting

Online Plotting

The online plot are save in your plot.ly account. Online plots are generate by two methods

• py.plot()
• py.iplot()

Example of Online Plotting

import plotly
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
import math

xpoints = np.arange(0, math.pi*2, 0.05)
ypoints = np.sin(xpoints)
trace0 = go.Scatter(
   x = xpoints, y = ypoints
)
data = [trace0]
py.plot(data, filename = 'Sine wave', auto_open=True)

Output of Online Plotting

Offline Plotting

The offline Plot is generate graphs offline and save in local machine. plotly.offline.plot() function creates a standalone HTML. Use plotly.offline.iplot() when working offline in a Jupyter Notebook.

Note − Plotly’s version 1.9.4+ is need

Scatter traces

Example of two scatter traces

import numpy as np
import math
xpoints = np.arange(0, math.pi*2, 0.05)
y1 = np.sin(xpoints)
y2 = np.cos(xpoints)
trace0 = go.Scatter(
   x = xpoints,
   y = y1,
   name='Sine'
)
trace1 = go.Scatter(
   x = xpoints,
   y = y2,
   name = 'cos'
)
data = [trace0, trace1]
layout = go.Layout(title = "Sine and cos", xaxis = {'title':'angle'}, yaxis = {'title':'value'})
what = go.Figure(data = data, layout = layout)
iplot(what)

Output of scatter traces

Format Axis and Ticks

Example

layout = go.Layout(
   title = "Sine and cos",
   xaxis = dict(
      title = 'angle',
      showgrid = True,
      zeroline = True,
      showline = True,
      showticklabels = True,
      gridwidth = 2
   ),
   yaxis = dict(
      showgrid = True,
      zeroline = True,
      showline = True,
      gridcolor = '#bdbdbd',
      gridwidth = 3,
      zerolinecolor = '#969696',
      zerolinewidth = 3,
      linecolor = '#636363',
      linewidth = 3,
      title = 'VALUE',
      titlefont = dict(
         family = 'Arial, sans-serif',
         size = 17,
         color = 'lightgrey'
      ),
      showticklabels = True,
      tickangle = 50,
      tickfont = dict(
      family = 'Old Standard TT, serif',
      size = 15,
      color = 'black'
      ),
      tickmode = 'linear',
      tick0 = 0.0,
      dtick = 0.27
   )
)

Output

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To know more about plotly Library Function please Wikipedia click here.

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