semvec/pypi-packages huggingface dataset:
gviz-data-table 2.0.0
Python API for Google Visualization
License: BSD
Requires Python: >=3.8
Keywords: charting graph Google Visualisation

Introduction
============

Gviz Data Table is a simple Python library for converting Python data types
to the Google Visualization Data Table JSON format.
https://developers.google.com/chart/interactive/docs/reference

The Google Visualization Library itself is a Javascript library that provides
interactive charts that work in pretty much any browser. The libraries cover
most use cases including tables, as well as charts, so you can have a chart
and a table of the same data.

Gviz Data Table is designed primarily for use with data sources such as
databases. Usage is supposed to be minimal: you provide a schema, that is a
list of columns, and the rows of data. A column must have a name and Python
data type. It can also have a label which will be used for display, otherwise
the name will be used.

Each row is a sequence of cells. Although columns are explicit row names are
always the first cell in a row. Like columns, cells can also have labels.
Gviz Data Table will validate each cell to make sure that data conforms to
type specified in the schema and will map Python types to their JSON
equivalent but it does not coerce any data, i.e. if a column has type `int`
and a cell's data is a string containing numerical characters only this will
still raise an exception.

Gviz Data Table handles data conversion only. You will need to add the
necessary Javascript to an web page in order for any charts or table to be
drawn. Tables, columns and cells can all have options which are just
dictionaries. As there is no further definition of options no validation of
their items occurs. Unknown items will simply be ignored.

Gviz Data Table is composed of: one container class ``Table``; two data
classes, ``Cell`` and ``Column`` and one JSON encoder. Application code should
probably only ever need to use Table and the encoder.

Usage
-----

Tables can be initialised with a schema or these can be added imperatively.
Once one row has been added to a table no more columns can be added. Once all
the rows have been added. The table can be converted into JSON using the
encoder.

Example
*******

Let's say we have data representing the names and salaries of people

====== ======
Name   Salary
====== ======
Jim       50
Bob       80
====== ======

This could be coded in Gviz Data Table like this:

   .. code-block:: python

      from gviz_data_table import Table

      table = Table()
      table.add_column('name', str, "Name")
      table.add_column('salary', int, "Salary")
      table.append(["Jim", 50])
      table.append(["Bob", 80])

This can be encoded into JSON using the encoder:

   .. code-block:: python

      from gviz_data_table import encode

      encode(table)

It can also be directly encoded

   .. code-block:: python

      table.encode()

And also used as a static data source for asynchronous loading from Javascript

   .. code-block:: python

      table.source()