fd191b81e1bc654866807e9a68af769ef006c554,ggplot/stats/stat_hline.py,stat_hline,_calculate,#stat_hline#Any#,14

Before Change

    CREATES = {"yintercept"}

    def _calculate(self, data):
        try:
            y = data.pop("y")
        except KeyError:
            pass

        // yintercept may be one of:
        //   - aesthetic to geom_hline or
        //   - parameter setting to stat_hline
        try:
            yintercept = data.pop("yintercept")
        except KeyError:
            yintercept = self.params["yintercept"]

        // TODO: Enable this when the parameters are passed correctly
        // and uncomment test case
        if hasattr(yintercept, "__call__"):
            try:
                y = y
            except NameError:
                raise Exception(
                    "To compute the intercept, y aesthetic is needed")
            yintercept = yintercept(y)

        yintercept = make_iterable(yintercept)
        new_data = pd.DataFrame({"yintercept": yintercept})
        // Copy the other aesthetics into the new dataframe
        n = len(yintercept)
        for ae in data:
            new_data[ae] = make_iterable_ntimes(data[ae].iloc[0], n)
        return new_data

After Change

    CREATES = {"yintercept"}

    def _calculate(self, data):
        y = pop(data, "y", None)

        // yintercept may be one of:
        //   - aesthetic to geom_hline or
        //   - parameter setting to stat_hline
        yintercept = pop(data, "yintercept", self.params["yintercept"])

        // TODO: Enable this when the parameters are passed correctly
        // and uncomment test case
        if hasattr(yintercept, "__call__"):
            if y is None:
                raise Exception(
                    "To compute the intercept, y aesthetic is needed")
            yintercept = yintercept(y)

        yintercept = make_iterable(yintercept)
        new_data = pd.DataFrame({"yintercept": yintercept})
        // Copy the other aesthetics into the new dataframe
        n = len(yintercept)
        for ae in data:
            new_data[ae] = make_iterable_ntimes(data[ae].iloc[0], n)
        return new_data

Instances