| Name | plotly-chart-generator JSON |
| Version |
0.4.0
JSON |
| download |
| home_page | |
| Summary | Quickly display basic Plotly charts based on data inside a Pandas dataframe. |
| upload_time | 2023-08-21 08:40:33 |
| maintainer | |
| docs_url | None |
| author | Preben Hesvik |
| requires_python | >=3.11,<4.0 |
| license | "MIT" |
| keywords |
chart
plotly
pandas
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
======================
Plotly Chart Generator
======================
.. image:: https://img.shields.io/pypi/l/plotly_chart_generator :alt: PyPI - License
Description
-----------
This package allows the user to quickly generate plotly charts with customized
styling and formatting from Pandas dataframes and other data structures with as
little as one line of code.
The following chart types can be created:
* Bar charts (from dataframe)
* Line charts (from dataframe)
* Scatter charts (from dictionary)
* Pie charts (from lists, numpy arrays, Pandas series)
* Histograms (from lists, numpy arrays, Pandas series)
* Dot charts (from dataframe)
* Box charts (from lists, numpy arrays, Pandas series)
* Sunburst charts (from lists, numpy arrays, Pandas series)
* Scatter charts subplots (from dictionary)
* Pie chats subplots (from dictionary)
Chart examples are available at https://github.com/PrebenHesvik/Plotly-Chart-Generator
Installation
------------
.. code:: python
pip install plotly_chart_generator
Usage
-----
.. code:: python
from plotly_chart_generator.display_chart import display_chart
from plotly_chart_generator.bar_chart import bar_chart
from plotly_chart_generator.chart_styles import chart_styles
# create data
index = ['Product A', 'Product B', 'Product C']
values = {'Products': [37.5, 40.2, 27.8]}
data = pd.DataFrame(data=values, index=index).transpose()
# layout
layout = chart_styles(
width=500,
height=600,
title='Product sales (millions)',
title_size=16,
xaxis_ticksize=14)
# set colors
idmax = data.idxmax(axis=1)[0]
max_val_idx = data.columns.get_loc(idmax)
colors = ['lightslategray',] * len(data.values[0])
colors[max_val_idx] = 'crimson'
# traces
traces = bar_chart(
df=data,
bar_width=0.4,
textpos='inside',
linewidth=1,
marker_color=colors)
display_chart(traces=traces, layout=layout)
Disclaimer
----------
Most of the descriptions of arguments have been copied form the Plotly Figure
Reference Guide at https://plotly.com/python/reference/
Raw data
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