datascience.tables.Table.barh

Table.barh(column_for_categories=None, select=None, overlay=True, width=6, **vargs)[source]

Plot horizontal bar charts for the table.

Args:
column_for_categories (str): A column containing y-axis categories
used to create buckets for bar chart.
Kwargs:
overlay (bool): create a chart with one color per data column;
if False, each will be displayed separately.
vargs: Additional arguments that get passed into plt.barh.
See http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.barh for additional arguments that can be passed into vargs.
Raises:
ValueError – Every selected except column for column_for_categories
must be numerical.
Returns:
Horizontal bar graph with buckets specified by column_for_categories. Each plot is labeled using the values in column_for_categories and one plot is produced for every other column (or for the columns designated by select).
>>> t = Table().with_columns(
...     'Furniture', make_array('chairs', 'tables', 'desks'),
...     'Count', make_array(6, 1, 2),
...     'Price', make_array(10, 20, 30)
...     )
>>> t
Furniture | Count | Price
chairs    | 6     | 10
tables    | 1     | 20
desks     | 2     | 30
>>> furniture_table.barh('Furniture') # doctest: +SKIP
<bar graph with furniture as categories and bars for count and price>
>>> furniture_table.barh('Furniture', 'Price') # doctest: +SKIP
<bar graph with furniture as categories and bars for price>
>>> furniture_table.barh('Furniture', make_array(1, 2)) # doctest: +SKIP
<bar graph with furniture as categories and bars for count and price>