def make_tables(self):
        # overall promoted link traffic
        impressions = traffic.AdImpressionsByCodename.historical_totals("day")
        clicks = traffic.ClickthroughsByCodename.historical_totals("day")
        data = traffic.zip_timeseries(impressions, clicks)

        columns = [
            dict(color=COLORS.UPVOTE_ORANGE,
                 title=_("total impressions by day"),
                 shortname=_("impressions")),
            dict(color=COLORS.DOWNVOTE_BLUE,
                 title=_("total clicks by day"),
                 shortname=_("clicks")),
        ]

        self.totals = TimeSeriesChart("traffic-ad-totals",
                                      _("ad totals"),
                                      "day",
                                      columns,
                                      data,
                                      self.traffic_last_modified,
                                      classes=["traffic-table"])

        # get summary of top ads
        advert_summary = traffic.AdImpressionsByCodename.top_last_month()
        things = AdvertTrafficSummary.get_things(ad for ad, data
                                                 in advert_summary)
        self.advert_summary = []
        for id, data in advert_summary:
            name = AdvertTrafficSummary.get_ad_name(id, things=things)
            url = AdvertTrafficSummary.get_ad_url(id, things=things)
            self.advert_summary.append(((name, url), data))

def traffic_totals():
    from r2.models import traffic

    impressions = traffic.AdImpressionsByCodename.historical_totals("day")
    clicks = traffic.ClickthroughsByCodename.historical_totals("day")
    traffic_data = traffic.zip_timeseries(impressions, clicks)
    return [(d.date(), v) for d, v in traffic_data]