Skip to main content

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

Project description

https://travis-ci.org/gtnx/pandas-highcharts.svg?branch=master https://coveralls.io/repos/gtnx/pandas-highcharts/badge.svg

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))

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pandas-highcharts-0.5.2.tar.gz (10.3 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page