@@ -1410,19 +1410,19 @@ def line(
1410
1410
The color for each of the DataFrame's columns. Possible values are:
1411
1411
1412
1412
- A single color string referred to by name, RGB or RGBA code,
1413
- for instance 'red' or '#a98d19'.
1413
+ for instance 'red' or '#a98d19'.
1414
1414
1415
1415
- A sequence of color strings referred to by name, RGB or RGBA
1416
- code, which will be used for each column recursively. For
1417
- instance ['green','yellow'] each column's line will be filled in
1418
- green or yellow, alternatively. If there is only a single column to
1419
- be plotted, then only the first color from the color list will be
1420
- used.
1416
+ code, which will be used for each column recursively. For
1417
+ instance ['green','yellow'] each column's line will be filled in
1418
+ green or yellow, alternatively. If there is only a single column to
1419
+ be plotted, then only the first color from the color list will be
1420
+ used.
1421
1421
1422
1422
- A dict of the form {column name : color}, so that each column will be
1423
- colored accordingly. For example, if your columns are called `a` and
1424
- `b`, then passing {'a': 'green', 'b': 'red'} will color lines for
1425
- column `a` in green and lines for column `b` in red.
1423
+ colored accordingly. For example, if your columns are called `a` and
1424
+ `b`, then passing {'a': 'green', 'b': 'red'} will color lines for
1425
+ column `a` in green and lines for column `b` in red.
1426
1426
1427
1427
**kwargs
1428
1428
Additional keyword arguments are documented in
@@ -1463,23 +1463,23 @@ def line(
1463
1463
>>> lines = df.plot.line()
1464
1464
1465
1465
.. plot::
1466
- :context: close-figs
1466
+ :context: close-figs
1467
1467
1468
- An example with subplots, so an array of axes is returned.
1468
+ An example with subplots, so an array of axes is returned.
1469
1469
1470
- >>> axes = df.plot.line(subplots=True)
1471
- >>> type(axes)
1472
- <class 'numpy.ndarray'>
1470
+ >>> axes = df.plot.line(subplots=True)
1471
+ >>> type(axes)
1472
+ <class 'numpy.ndarray'>
1473
1473
1474
1474
.. plot::
1475
- :context: close-figs
1475
+ :context: close-figs
1476
1476
1477
- Let's repeat the same example, but specifying colors for
1478
- each column (in this case, for each animal).
1477
+ Let's repeat the same example, but specifying colors for
1478
+ each column (in this case, for each animal).
1479
1479
1480
- >>> axes = df.plot.line(
1481
- ... subplots=True, color={"pig": "pink", "horse": "#742802"}
1482
- ... )
1480
+ >>> axes = df.plot.line(
1481
+ ... subplots=True, color={"pig": "pink", "horse": "#742802"}
1482
+ ... )
1483
1483
1484
1484
.. plot::
1485
1485
:context: close-figs
@@ -1521,19 +1521,19 @@ def bar(
1521
1521
The color for each of the DataFrame's columns. Possible values are:
1522
1522
1523
1523
- A single color string referred to by name, RGB or RGBA code,
1524
- for instance 'red' or '#a98d19'.
1524
+ for instance 'red' or '#a98d19'.
1525
1525
1526
1526
- A sequence of color strings referred to by name, RGB or RGBA
1527
- code, which will be used for each column recursively. For
1528
- instance ['green','yellow'] each column's bar will be filled in
1529
- green or yellow, alternatively. If there is only a single column to
1530
- be plotted, then only the first color from the color list will be
1531
- used.
1527
+ code, which will be used for each column recursively. For
1528
+ instance ['green','yellow'] each column's bar will be filled in
1529
+ green or yellow, alternatively. If there is only a single column to
1530
+ be plotted, then only the first color from the color list will be
1531
+ used.
1532
1532
1533
1533
- A dict of the form {column name : color}, so that each column will be
1534
- colored accordingly. For example, if your columns are called `a` and
1535
- `b`, then passing {'a': 'green', 'b': 'red'} will color bars for
1536
- column `a` in green and bars for column `b` in red.
1534
+ colored accordingly. For example, if your columns are called `a` and
1535
+ `b`, then passing {'a': 'green', 'b': 'red'} will color bars for
1536
+ column `a` in green and bars for column `b` in red.
1537
1537
1538
1538
**kwargs
1539
1539
Additional keyword arguments are documented in
@@ -1660,19 +1660,19 @@ def barh(
1660
1660
The color for each of the DataFrame's columns. Possible values are:
1661
1661
1662
1662
- A single color string referred to by name, RGB or RGBA code,
1663
- for instance 'red' or '#a98d19'.
1663
+ for instance 'red' or '#a98d19'.
1664
1664
1665
1665
- A sequence of color strings referred to by name, RGB or RGBA
1666
- code, which will be used for each column recursively. For
1667
- instance ['green','yellow'] each column's bar will be filled in
1668
- green or yellow, alternatively. If there is only a single column to
1669
- be plotted, then only the first color from the color list will be
1670
- used.
1666
+ code, which will be used for each column recursively. For
1667
+ instance ['green','yellow'] each column's bar will be filled in
1668
+ green or yellow, alternatively. If there is only a single column to
1669
+ be plotted, then only the first color from the color list will be
1670
+ used.
1671
1671
1672
1672
- A dict of the form {column name : color}, so that each column will be
1673
- colored accordingly. For example, if your columns are called `a` and
1674
- `b`, then passing {'a': 'green', 'b': 'red'} will color bars for
1675
- column `a` in green and bars for column `b` in red.
1673
+ colored accordingly. For example, if your columns are called `a` and
1674
+ `b`, then passing {'a': 'green', 'b': 'red'} will color bars for
1675
+ column `a` in green and bars for column `b` in red.
1676
1676
1677
1677
**kwargs
1678
1678
Additional keyword arguments are documented in
0 commit comments