timeseries.py 文件源码

def plot_facet(self, data, color, **kwargs):
        x = kwargs.get("x")
        y = kwargs.get("y")
        levels_x = kwargs.get("levels_x")
        levels_y = kwargs.get("levels_y")

        #num = []
        #date = []
        #time = data[self._time_column]
        #num = data[self._time_column].apply(self.convert_to_datetime)
        #date = data[self._time_column].apply(self.convert_to_timeseries)
        #if pd.isnull(num).sum() <= pd.isnull(date).sum():
            #data[self._time_column] = num
        #else:
            #data[self._time_column] = date

        #data.dropna(inplace=True)
        #if len(self._groupby) == 2:
            #ct = pd.crosstab(data[self._time_column], data[self._groupby[0]])
            #ct = ct.reindex_axis(self._levels[0], axis=1).fillna(0)
            #ct = ct[pd.notnull(ct.index)]
        #else:
            #ct = pd.crosstab(
                #data[self._time_column],
                #pd.Series([""] * len(self._table[self._time_column]), name=""))

        ## percentage area plot:
        ## if there is only one grouping variable (the time column),
        ## the cross table produces a Series, not a data frame. It
        ## isn't really very informative to plot it, but we provide
        ## for this special case anyway_
        #if type(ct) == pd.Series:
            #ct = ct.apply(lambda x: 100)
        #else:
            #ct = ct.apply(lambda x: (100 * x) / sum(x), axis=1)
        #ct.plot(kind="area", ax=plt.gca(), stacked=True, color=self.get_palette(), **kwargs)