iplotter 0.1.4

C3.js and plotly.js for iPython/Jupyter notebooks

C3.js and plotly.js charting in ipython/jupyter notebooks

• Installation

• C3.js

• plotly.js

• Usage

• Examples

IPlotter is a simple library for generating interactive charts ipython/jupyter notebooks using C3.js or plotly.js from simple python data structures (dictionaries, lists, etc.)

Installation

To install this package run pip install git+git://github.com/niloch/iplotter.git@master or pip install iplotter

C3.js

C3 is a charting library based on d3 for making interactive and easy to understand charts, graphs, and plots.

Charts can be conveniently declared and bound to DOM elements with animated transitions for hiding/displaying data.

plotly.js

Plotly.js is a charting library based on d3 from plotly. plotly provides native clients in many programming languages including python which can be rendered in an ipython notebook. However, the native python client requires the user to create an account and by default makes all plots public. plotly.js can be used without creating an account and are rendered locally to keep everything private. IPlotter makes use of the plotly.js library for chart rendering instead of the native python client from plotly which performs the rendering on their servers.

Usage

The iplotter module contains the IPlotter class which is initialized with chosen library(‘c3’/’plotly’). The plotter’s functions are called on a dictionary containing the data specifying the chart attributes. There are optional arguments for graph size and filename if needed. The data dictionary must have a structure equivalent to the JSON specifications from C3.js or plotly.js. plotly.js optionally allows specifying the chart layout as a separate dictionary. Plots can be rendered in the ipython notebook and saved to the current directory as html, for later reference.

Examples

C3 Stacked Area Spline Chart

from iplotter.iplotter import IPlotter

plotter = IPlotter('c3')

chart = {
    "data": {
        "columns": [
            ['data1', 300, 350, 300, 0, 0, 120],
            ['data2', 130, 100, 140, 200, 150, 50],
            ['data3', 180, 75, 265, 100, 50, 100]
        ],
        "types": {
            "data1": 'area-spline',
            "data2": 'area-spline',
            "data3": 'area-spline'
        },
        "groups": [['data1', 'data2', 'data3']]
    }
}

plotter.plot(chart)

Plot1

plotly.js Grouped Bar Chart

from iplotter.iplotter import IPlotter

plotter2 = IPlotter('plotly')

trace1 = {
  "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],
  "type": 'bar',
  "name": 'Item 1',
  "marker": {
    "color": 'rgb(49,130,189)',
    "opacity": 0.7,
  }
}

trace2 = {
  "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],
  "type": 'bar',
  "name": 'Item 2',
  "marker": {
    "opacity": 0.7
  }
}

data = [trace1, trace2]

layout = {
  "title": 'Title',
  "xaxis": {
    "tickangle": -45
  },
  "barmode": 'group'
}

plotter2.plot(data,layout)

Plot2

plotly.js HeatMap

from iplotter.iplotter import IPlotter

plotter = IPlotter('plotly')

data = [{
 'colorscale': 'YIGnBu',
 'reversescale': True,
 'type': u'heatmap',
 'x': ['class1', 'class2', 'class3'],
 'y': ['class1', 'class2', 'class3'],
 'z': [[ 0.7,  0.2,  0.1],
        [ 0.2,  0.7,  0.1],
        [ 0.15,  0.27,  0.56]]}]


plotter.plot_and_save(data, w=600, h=600, name='heatmap1', overwrite=True)

Plot3