@@ -14,9 +14,9 @@ def table(ax, data, rowLabels=None, colLabels=None, **kwargs):
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----------
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ax : Matplotlib axes object
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data : DataFrame or Series
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- data for table contents
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- kwargs : keywords, optional
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- keyword arguments which passed to matplotlib.table.table.
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+ Data for table contents.
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+ ** kwargs
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+ Keyword arguments to be passed to matplotlib.table.table.
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If `rowLabels` or `colLabels` is not specified, data index or column
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name will be used.
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@@ -82,7 +82,7 @@ def scatter_matrix(
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density_kwds = None ,
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hist_kwds = None ,
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range_padding = 0.05 ,
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- ** kwds
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+ ** kwargs
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):
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"""
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Draw a matrix of scatter plots.
@@ -91,28 +91,26 @@ def scatter_matrix(
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----------
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frame : DataFrame
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alpha : float, optional
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- amount of transparency applied
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+ Amount of transparency applied.
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figsize : (float,float), optional
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- a tuple (width, height) in inches
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+ A tuple (width, height) in inches.
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ax : Matplotlib axis object, optional
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grid : bool, optional
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- setting this to True will show the grid
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+ Setting this to True will show the grid.
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diagonal : {'hist', 'kde'}
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- pick between 'kde' and 'hist' for
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- either Kernel Density Estimation or Histogram
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- plot in the diagonal
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+ Pick between 'kde' and 'hist' for either Kernel Density Estimation or
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+ Histogram plot in the diagonal.
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marker : str, optional
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- Matplotlib marker type, default '.'
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- hist_kwds : other plotting keyword arguments
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- To be passed to hist function
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- density_kwds : other plotting keyword arguments
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- To be passed to kernel density estimate plot
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- range_padding : float, optional
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- relative extension of axis range in x and y
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- with respect to (x_max - x_min) or (y_max - y_min),
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- default 0.05
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- kwds : other plotting keyword arguments
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- To be passed to scatter function
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+ Matplotlib marker type, default '.'.
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+ hist_kwds : keywords
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+ Keyword arguments to be passed to hist function.
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+ density_kwds : keywords
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+ Keyword arguments to be passed to kernel density estimate plot.
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+ range_padding : float, default 0.05
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+ Relative extension of axis range in x and y with respect to
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+ (x_max - x_min) or (y_max - y_min).
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+ **kwargs
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+ Keyword arguments to be passed to scatter function.
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Returns
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-------
@@ -136,7 +134,7 @@ def scatter_matrix(
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density_kwds = density_kwds ,
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hist_kwds = hist_kwds ,
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range_padding = range_padding ,
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- ** kwds
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+ ** kwargs
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)
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@@ -215,8 +213,8 @@ def radviz(frame, class_column, ax=None, color=None, colormap=None, **kwds):
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@deprecate_kwarg (old_arg_name = "data" , new_arg_name = "frame" )
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def andrews_curves (
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- frame , class_column , ax = None , samples = 200 , color = None , colormap = None , ** kwds
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- ):
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+ frame , class_column , ax = None , samples = 200 , color = None , colormap = None ,
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+ ** kwargs ):
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"""
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Generate a matplotlib plot of Andrews curves, for visualising clusters of
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multivariate data.
@@ -233,17 +231,17 @@ def andrews_curves(
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Parameters
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----------
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frame : DataFrame
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- Data to be plotted, preferably normalized to (0.0, 1.0)
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+ Data to be plotted, preferably normalized to (0.0, 1.0).
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class_column : Name of the column containing class names
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ax : matplotlib axes object, default None
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samples : Number of points to plot in each curve
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color : list or tuple, optional
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- Colors to use for the different classes
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+ Colors to use for the different classes.
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colormap : str or matplotlib colormap object, default None
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Colormap to select colors from. If string, load colormap with that name
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from matplotlib.
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- kwds : keywords
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- Options to pass to matplotlib plotting method
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+ **kwargs
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+ Options to pass to matplotlib plotting method.
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Returns
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-------
@@ -257,7 +255,7 @@ def andrews_curves(
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samples = samples ,
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color = color ,
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colormap = colormap ,
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- ** kwds
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+ ** kwargs
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)
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@@ -327,7 +325,7 @@ def parallel_coordinates(
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axvlines = True ,
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axvlines_kwds = None ,
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sort_labels = False ,
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- ** kwds
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+ ** kwargs
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):
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"""
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Parallel coordinates plotting.
@@ -336,30 +334,29 @@ def parallel_coordinates(
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----------
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frame : DataFrame
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class_column : str
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- Column name containing class names
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+ Column name containing class names.
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cols : list, optional
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- A list of column names to use
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+ A list of column names to use.
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ax : matplotlib.axis, optional
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- matplotlib axis object
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+ Matplotlib axis object.
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color : list or tuple, optional
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- Colors to use for the different classes
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+ Colors to use for the different classes.
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use_columns : bool, optional
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- If true, columns will be used as xticks
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+ If true, columns will be used as xticks.
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xticks : list or tuple, optional
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- A list of values to use for xticks
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+ A list of values to use for xticks.
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colormap : str or matplotlib colormap, default None
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Colormap to use for line colors.
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axvlines : bool, optional
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- If true, vertical lines will be added at each xtick
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+ If true, vertical lines will be added at each xtick.
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axvlines_kwds : keywords, optional
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- Options to be passed to axvline method for vertical lines
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- sort_labels : bool, False
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- Sort class_column labels, useful when assigning colors
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+ Options to be passed to axvline method for vertical lines.
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+ sort_labels : bool, default False
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+ Sort class_column labels, useful when assigning colors.
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.. versionadded:: 0.20.0
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-
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- kwds : keywords
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- Options to pass to matplotlib plotting method
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+ **kwargs
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+ Options to pass to matplotlib plotting method.
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Returns
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-------
@@ -388,7 +385,7 @@ def parallel_coordinates(
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axvlines = axvlines ,
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axvlines_kwds = axvlines_kwds ,
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sort_labels = sort_labels ,
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- ** kwds
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+ ** kwargs
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)
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@@ -411,23 +408,23 @@ def lag_plot(series, lag=1, ax=None, **kwds):
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return plot_backend .lag_plot (series = series , lag = lag , ax = ax , ** kwds )
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- def autocorrelation_plot (series , ax = None , ** kwds ):
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+ def autocorrelation_plot (series , ax = None , ** kwargs ):
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"""
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Autocorrelation plot for time series.
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Parameters
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----------
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series : Time series
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ax : Matplotlib axis object, optional
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- kwds : keywords
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- Options to pass to matplotlib plotting method
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+ **kwargs
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+ Options to pass to matplotlib plotting method.
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Returns
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-------
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class:`matplotlib.axis.Axes`
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"""
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plot_backend = _get_plot_backend ("matplotlib" )
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- return plot_backend .autocorrelation_plot (series = series , ax = ax , ** kwds )
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+ return plot_backend .autocorrelation_plot (series = series , ax = ax , ** kwargs )
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def tsplot (series , plotf , ax = None , ** kwargs ):
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