C3.js and plotly.js for iPython/Jupyter notebooks
Project description
C3.js and plotly.js charting in ipython/jupyter notebooks
iplotter is a simple package 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 clasess for both JavaScript Libraries. The plotter’s functions take a dictionary parameter 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 C3Plotter
plotter = C3Plotter()
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 PlotlyPlotter
plotter = PlotlyPlotter()
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'
}
plotter.plot(data,layout)
Plot2
plotly.js HeatMap
from iplotter.iplotter import PlotlyPlotter
plotter = PlotlyPlotter()
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
Multple Charts
Saving multiple charts to one file or displaying multiple charts in one iframe can be achieved by concatenating html strings returned by the render function, and the head attribute which contains the script tags for loading the JavasScript libraries.
from iplotter.iplotter import PlotlyPlotter
from IPython.display import HTML
plotter = PlotlyPlotter()
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 = {
"labels": ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
"values": [19, 14, 22, 14, 16, 19, 15, 14, 10, 12, 12, 16],
"type": 'pie',
"name": 'Item 2',
"marker": {
"opacity": 0.7
}
}
charts = [
[trace1],
[trace2]
]
# plotter.head will return the html string containing script tags for loading the plotly.js/C3.js libraries
multiple_plot_html = plotter.head
for i, chart in enumerate(charts):
multiple_plot_html += plotter.render(data=chart, name="chart_"+str(i))
# Write multiple plots to file
with open("multiple_plots.html", 'w') as outfile:
outfile.write(multiple_plot_html)
# display multiple plots in iframe
HTML(plotter.iframe.format(multiple_plot_html, 600, 900))
Plot4
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for iplotter-0.1.6-py2.py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 1604630308e0a048553238bb50200bb70baf95a8fa6a4a0d986ec970f1aa5541 |
|
| MD5 | bcb34c7b6a7c6f817c23644f35dd7064 |
|
| BLAKE2b-256 | d9b53b395f036106e535f31dc268ae22960413e6378f78470b61ded00d1aee28 |
