isabella232 / pandas-highcharts

Beautiful charting of pandas.DataFrame with Highcharts

pandas-highcharts

What is it

pandas-highcharts is a Python package which allows you to easily build Highcharts plots with pandas.DataFrame objects.

Motivation

• pandas is the best tool to handle data in Python
• pandas is able to produce matplotlib plots. They work pretty well but have two major drawbacks
  • Not very web friendly
  • Pretty ugly
• Highcharts produce nice, interactive plot in your browser and is very complete

Features

• Same interface as DataFrame.plot
• Following parameters are handled
  • data
  • x
  • y
  • kind
  • figsize
  • use_index
  • title
  • grid
  • legend
  • style
  • logx
  • logy
  • loglog
  • xticks
  • yticks
  • xlim
  • ylim
  • rot
  • fontsize
  • position
  • stacked
  • sort_columns
  • secondary_y
  • mark_right
• Following parameters are not handled (yet) :
  • ax
  • ay
  • subplots
  • sharex
  • sharey
  • layout
  • colormap
  • colorbar
  • layout
  • table
  • yerr
  • xerr
  • kwds
• You can specify those specific highcharts parameters:
  • tooltip
• Static files (highcharts.js) are not embedded

Installation

Install the package using pip

pip install pandas-highcharts

Usage

Import it in your views

import pandas_highcharts
df = ... # create your dataframe here
chart = pandas_highcharts.serialize(df, render_to='my-chart', output_type='json')

In your templates

<div id="my-chart"></div>
<script type="text/javascript">
  new Highcharts.Chart({{chart|safe}});
</script>

Contributing

See CONTRIBUTING.rst for information on how to contribute to pandas-highcharts.

More examples

Some examples are available on nbviewer.

Please read the doc for DataFrame.plot.

For example, with the following dataset:

import pandas as pd
from pandas_highcharts.core import serialize
from pandas.compat import StringIO
dat = """ts;A;B;C
2015-01-01 00:00:00;27451873;29956800;113
2015-01-01 01:00:00;20259882;17906600;76
2015-01-01 02:00:00;11592256;12311600;48
2015-01-01 03:00:00;11795562;11750100;50
2015-01-01 04:00:00;9396718;10203900;43
2015-01-01 05:00:00;14902826;14341100;53"""
df = pd.read_csv(StringIO(dat), sep=';', index_col='ts', parse_dates='ts')

# Basic line plot
chart = serialize(df, render_to="my-chart", title="My Chart")
# Basic column plot
chart = serialize(df, render_to="my-chart", title="Test", kind="bar")
# Basic column plot
chart = serialize(df, render_to="my-chart", title="Test", kind="barh")
# Plot C on secondary axis
chart = serialize(df, render_to="my-chart", title="Test", secondary_y = ["C"])
# Plot on a 1000x700 div
chart = serialize(df, render_to="my-chart", title="Test", figsize = (1000, 700))