@@ -866,20 +866,20 @@ def line(self, x=None, y=None, **kwargs):
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Either the location or the label of the columns to be used.
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By default, it will use the remaining DataFrame numeric columns.
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color : str, int, array_like, or dict, optional
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- The color of each line for each row . Possible values are:
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+ The color for each of the DataFrame's columns . Possible values are:
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- A single color string referred to by name, RGB or RGBA code,
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for instance 'red' or '#a98d19'.
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- A sequence of color strings referred to by name, RGB or RGBA
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- code, which will be used for each line for each row recursively. For
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- instance ['green','yellow'] all lines for each row will be filled in green
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- or yellow, alternatively.
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+ code, which will be used for each column recursively. For
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+ instance ['green','yellow'] each column's line will be coloured in
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+ green or yellow, alternatively.
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- - A dict of the form {column name : color}, so that each row's lines will be
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+ - A dict of the form {column name : color}, so that each column will be
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colored accordingly. For example, if your columns are called `a` and `b`,
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- then passing {'a': 'green', 'b': 'red'} will color the lines for column
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- `a` in green and lines for column `b` in red.
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+ then passing {'a': 'green', 'b': 'red'} will color lines for column `a` in
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+ green and lines for column `b` in red.
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**kwargs
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Keyword arguments to pass on to :meth:`DataFrame.plot`.
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@@ -961,17 +961,17 @@ def bar(self, x=None, y=None, **kwargs):
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Allows plotting of one column versus another. If not specified,
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all numerical columns are used.
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color : str, int, array_like, or dict, optional
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- The color of each bar for each row . Possible values are:
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+ The color for each of the DataFrame's columns . Possible values are:
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- A single color string referred to by name, RGB or RGBA code,
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for instance 'red' or '#a98d19'.
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- A sequence of color strings referred to by name, RGB or RGBA
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- code, which will be used for each bar for each row recursively. For
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- instance ['green','yellow'] all bars for each row will be filled in green
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- or yellow, alternatively.
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+ code, which will be used for each column recursively. For
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+ instance ['green','yellow'] each column's bar will be filled in
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+ green or yellow, alternatively.
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- - A dict of the form {column name : color}, so that each row's bars will be
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+ - A dict of the form {column name : color}, so that each column will be
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colored accordingly. For example, if your columns are called `a` and `b`,
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then passing {'a': 'green', 'b': 'red'} will color bars for column `a` in
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green and bars for column `b` in red.
@@ -1026,7 +1026,7 @@ def bar(self, x=None, y=None, **kwargs):
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>>> axes = df.plot.bar(rot=0, subplots=True)
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>>> axes[1].legend(loc=2) # doctest: +SKIP
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- If we don't like the default colours, we can specify how we 'd
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+ If you don't like the default colours, you can specify how you 'd
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like each column to be colored.
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.. plot::
@@ -1070,17 +1070,17 @@ def barh(self, x=None, y=None, **kwargs):
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y : label or position, default All numeric columns in dataframe
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Columns to be plotted from the DataFrame.
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color : str, int, array_like, or dict, optional
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- The color of each bar for each row . Possible values are:
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+ The color for each of the DataFrame's columns . Possible values are:
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- A single color string referred to by name, RGB or RGBA code,
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for instance 'red' or '#a98d19'.
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- A sequence of color strings referred to by name, RGB or RGBA
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- code, which will be used for each bar for each row recursively. For
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- instance ['green','yellow'] all bars for each row will be filled in green
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- or yellow, alternatively.
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+ code, which will be used for each column recursively. For
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+ instance ['green','yellow'] each column's bar will be filled in
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+ green or yellow, alternatively.
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- - A dict of the form {column name : color}, so that each row's bars will be
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+ - A dict of the form {column name : color}, so that each column will be
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colored accordingly. For example, if your columns are called `a` and `b`,
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then passing {'a': 'green', 'b': 'red'} will color bars for column `a` in
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green and bars for column `b` in red.
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