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DOC: Document the behavior of bar() for categorical x data #29511

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22 changes: 22 additions & 0 deletions 22 lib/matplotlib/axes/_axes.py
Original file line number Diff line number Diff line change
Expand Up @@ -2386,6 +2386,17 @@ def bar(self, x, height, width=0.8, bottom=None, *, align="center",
The x coordinates of the bars. See also *align* for the
alignment of the bars to the coordinates.

Bars are often used for categorical data, i.e. string labels below
the bars. You can provide a list of strings directly to *x*.
``bar(['A', 'B', 'C'], [1, 2, 3])`` is often a shorter and more
convenient notation compared to
``bar(range(3), [1, 2, 3], tick_label=['A', 'B', 'C'])``. They are
equivalent as long as the names are unique. The explicit *tick_label*
notation draws the names in the sequence given. However, when having
duplicate values in categorical *x* data, these values map to the same
numerical x coordinate, and hence the corresponding bars are drawn on
top of each other.

height : float or array-like
The height(s) of the bars.

Expand Down Expand Up @@ -2701,6 +2712,17 @@ def barh(self, y, width, height=0.8, left=None, *, align="center",
The y coordinates of the bars. See also *align* for the
alignment of the bars to the coordinates.

Bars are often used for categorical data, i.e. string labels below
the bars. You can provide a list of strings directly to *y*.
``barh(['A', 'B', 'C'], [1, 2, 3])`` is often a shorter and more
convenient notation compared to
``barh(range(3), [1, 2, 3], tick_label=['A', 'B', 'C'])``. They are
equivalent as long as the names are unique. The explicit *tick_label*
notation draws the names in the sequence given. However, when having
duplicate values in categorical *y* data, these values map to the same
numerical y coordinate, and hence the corresponding bars are drawn on
top of each other.

width : float or array-like
The width(s) of the bars.

Expand Down
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