05220d53e8e12f2c9a82c1dc6d7d7cbfee130d60,pandastable/plotting.py,PlotViewer,plot2D,#PlotViewer#,195

Before Change

                    "pie": ["colormap", "legend", "kind","subplots"],
                    "hexbin": ["alpha", "colormap", "grid", "linewidth"],
                    "bootstrap": ["grid"],
                    "bar": ["alpha", "colormap", "grid", "legend", "linewidth", "subplots",
                            "sharey", "stacked", "rot", "kind"],
                    "barh": ["alpha", "colormap", "grid", "legend", "linewidth", "subplots",
                            "stacked", "rot", "kind"],
                    "histogram": ["alpha", "linewidth","grid","stacked","subplots","colormap",
                             "sharey","rot","bins", "logx", "logy"],
                    "heatmap": ["colormap","rot"],
                    "area": ["alpha","colormap","grid","linewidth","legend","stacked",
                             "kind","rot","logx"],
                    "density": ["alpha", "colormap", "grid", "legend", "linestyle",
                                 "linewidth", "marker", "subplots", "rot", "kind"],
                    "boxplot": ["rot", "grid", "logy"],
                    "scatter_matrix":["alpha", "linewidth", "marker", "grid", "s"],
                    }

        from pandas.tools import plotting
        data = self.data
        if self._checkNumeric(data) == False:
            self.showWarning("no numeric data to plot")
            return
        //get all options from the mpl options object
        kwds = self.mplopts.kwds
        kind = kwds["kind"]
        by = kwds["by"]
        by2 = kwds["by2"]

        //valid kwd args for this plot type
        kwargs = dict((k, kwds[k]) for k in valid[kind] if k in kwds)
        self.fig.clear()
        self.ax = ax = self.fig.add_subplot(111)

        if by != "":
            //groupby needs to be handled per group so we can add all the axes to
            //our figure correctly
            if by not in data.columns:
                self.showWarning("the grouping column must be in selected data")
                return
            if by2 != "" and by2 in data.columns:
                by = [by,by2]
            g = data.groupby(by)
            if len(g) >25:
                self.showWarning("too many groups to plot")
                return
            self.ax.set_visible(False)
            kwargs["subplots"] = False
            size = len(g)
            nrows = round(np.sqrt(size),0)
            ncols = np.ceil(size/nrows)
            i=1
            for n,df in g:
                ax = self.fig.add_subplot(nrows,ncols,i)
                kwargs["legend"] = False //remove axis legends
                d=df.drop(by,1) //remove grouping columns
                self._doplot(d, ax, kind, False, kwargs)
                ax.set_title(n)
                handles, labels = ax.get_legend_handles_labels()
                i+=1
            self.fig.legend(handles, labels, "lower right")
            self.fig.subplots_adjust(left=0.1, right=0.9, top=0.9, bottom=0.1, hspace=.25)
            axs = self.fig.get_axes()
            //self.canvas.draw()
        else:
            axs = self._doplot(data, ax, kind, kwds["subplots"], kwargs)

        if type(axs) is np.ndarray:
            self.ax = axs.flat[0]
        elif type(axs) is list:
            self.ax = axs[0]
        self.fig.suptitle(kwds["title"])
        if kwds["xlabel"] != "":
            self.ax.set_xlabel(kwds["xlabel"])

After Change

                    "pie": ["colormap", "legend", "kind","subplots"],
                    "hexbin": ["alpha", "colormap", "grid", "linewidth"],
                    "bootstrap": ["grid"],
                    "bar": ["alpha", "colormap", "grid", "legend", "linewidth", "subplots",
                            "sharey",  "logy", "stacked", "rot", "kind"],
                    "barh": ["alpha", "colormap", "grid", "legend", "linewidth", "subplots",
                            "stacked", "rot", "kind"],
                    "histogram": ["alpha", "linewidth","grid","stacked","subplots","colormap",
                             "sharey","rot","bins", "logx", "logy"],
                    "heatmap": ["colormap","rot"],
                    "area": ["alpha","colormap","grid","linewidth","legend","stacked",
                             "kind","rot","logx"],
                    "density": ["alpha", "colormap", "grid", "legend", "linestyle",
                                 "linewidth", "marker", "subplots", "rot", "kind"],
                    "boxplot": ["rot", "grid", "logy"],
                    "scatter_matrix":["alpha", "linewidth", "marker", "grid", "s"],
                    }

        from pandas.tools import plotting
        data = self.data
        if self._checkNumeric(data) == False:
            self.showWarning("no numeric data to plot")
            return
        //get all options from the mpl options object
        kwds = self.mplopts.kwds
        kind = kwds["kind"]
        by = kwds["by"]
        by2 = kwds["by2"]

        //valid kwd args for this plot type
        kwargs = dict((k, kwds[k]) for k in valid[kind] if k in kwds)
        self.fig.clear()
        self.ax = ax = self.fig.add_subplot(111)

        if by != "":
            //groupby needs to be handled per group so we can add all the axes to
            //our figure correctly
            if by not in data.columns:
                self.showWarning("the grouping column must be in selected data")
                return
            if by2 != "" and by2 in data.columns:
                by = [by,by2]
            g = data.groupby(by)
            if len(g) >25:
                self.showWarning("too many groups to plot")
                return
            self.ax.set_visible(False)
            kwargs["subplots"] = False
            size = len(g)
            nrows = round(np.sqrt(size),0)
            ncols = np.ceil(size/nrows)
            i=1
            for n,df in g:
                ax = self.fig.add_subplot(nrows,ncols,i)
                kwargs["legend"] = False //remove axis legends
                d=df.drop(by,1) //remove grouping columns
                self._doplot(d, ax, kind, False, kwargs)
                ax.set_title(n)
                handles, labels = ax.get_legend_handles_labels()
                i+=1
            self.fig.legend(handles, labels, "lower right")
            self.fig.subplots_adjust(left=0.1, right=0.9, top=0.9,
                                     bottom=0.1, hspace=.25)
            axs = self.fig.get_axes()
            //self.canvas.draw()
        else:
            axs = self._doplot(data, ax, kind, kwds["subplots"], kwargs)

        if type(axs) is np.ndarray:
            self.ax = axs.flat[0]
        elif type(axs) is list:
            self.ax = axs[0]
        self.fig.suptitle(kwds["title"])
        if kwds["xlabel"] != "":
            self.ax.set_xlabel(kwds["xlabel"])

Instances