An interactive charting library using Dygraphs for the Jupyter Notebook.
The Jupyter Notebook is an excellent tool for interacting with python and displaying data in real time. While tools like matplotlib can generate static plots in the Jupyter Notebook, interactive javascript plots are often more useful for exploring the data. This module can be readily included in an Jupyter Notebook and then used to generate beautiful time series plots with Dygraphs.
Simple Example
Subplot with Range Selector
Pandas Dataframe Plot
This python module generates javascript that interacts with the Dygraphs library, and passes it to the Jupyter Notebook kernel for execution.
Currently the PyDyGraphs module depends on Pandas to generate a JSON representation of the data for plotting. This required dependancy may be removed with future work. Pandas can be installed via pip.
Run the included example:examples/PyDyGraphTester.ipynb, or paste this code into an Jupyter Notebook to generate an interactive timeseries plot:
# Import pydygraphs and numpy
import dygraphs.graph as dy
import numpy as np
# Forma figure
fig = dy.figure(width = 600, height = 400)
# Generate data for the plot
x = np.array(range(100))
y = [np.sin(np.random.rand(100)),-np.sin(np.random.rand(100))]
# Plot the data on the figure
fig.plot(x,y, color=['navy','magenta'])
fig.title("Figure 1")
fig.xlabel('Series')
fig.ylabel('Value')
# Show the figure in this cell of the notebook
fig.show()
Simply clone this repository and include the dygraphs.graph module in your Jupyter Notebooks. Note: PyDyGraphs only supports Python 3.
Please submit a pull request or issue with any questions you might have!