@@ -2310,8 +2310,7 @@ def _plot(data, x=None, y=None, subplots=False,
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Sort column names to determine plot ordering
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secondary_y : boolean or sequence, default False
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Whether to plot on the secondary y-axis
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- If a list/tuple, which columns to plot on secondary y-axis
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- """
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+ If a list/tuple, which columns to plot on secondary y-axis"""
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series_unique = """label : label argument to provide to plot
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secondary_y : boolean or sequence of ints, default False
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If True then y-axis will be on the right"""
@@ -2328,9 +2327,8 @@ def _plot(data, x=None, y=None, subplots=False,
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series_ax = """ax : matplotlib axes object
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If not passed, uses gca()"""
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- df_note = """- If `kind` = 'bar' or 'barh', you can specify relative alignments
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- for bar plot layout by `position` keyword.
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- From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)
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+ df_note = """- If `kind` = 'scatter' and the argument `c` is the name of a dataframe
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+ column, the values of that column are used to color each point.
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- If `kind` = 'hexbin', you can control the size of the bins with the
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`gridsize` argument. By default, a histogram of the counts around each
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`(x, y)` point is computed. You can specify alternative aggregations
@@ -2425,19 +2423,12 @@ def _plot(data, x=None, y=None, subplots=False,
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Notes
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-----
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- If `kind` = 'hexbin', you can control the size of the bins with the
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- `gridsize` argument. By default, a histogram of the counts around each
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- `(x, y)` point is computed. You can specify alternative aggregations
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- by passing values to the `C` and `reduce_C_function` arguments.
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- `C` specifies the value at each `(x, y)` point and `reduce_C_function`
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- is a function of one argument that reduces all the values in a bin to
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- a single number (e.g. `mean`, `max`, `sum`, `std`).
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-
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- If `kind` = 'scatter' and the argument `c` is the name of a dataframe column,
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- the values of that column are used to color each point.
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- See matplotlib documentation online for more on this subject
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+ - If `kind` = 'bar' or 'barh', you can specify relative alignments
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+ for bar plot layout by `position` keyword.
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+ From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)
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%(klass_note)s
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-
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+
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"""
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@Appender (_shared_docs ['plot' ] % _shared_doc_df_kwargs )
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