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.
- ValueError – Every selected except column for
- Returns:
- Horizontal bar graph with buckets specified by
column_for_categories
. Each plot is labeled using the values incolumn_for_categories
and one plot is produced for every other column (or for the columns designated byselect
).
>>> 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') <bar graph with furniture as categories and bars for count and price> >>> furniture_table.barh('Furniture', 'Price') <bar graph with furniture as categories and bars for price> >>> furniture_table.barh('Furniture', make_array(1, 2)) <bar graph with furniture as categories and bars for count and price>