def tracker_reach_ts(ts1, ts2, t):
"""
Timeseries area plot for two time-series
Args:
ts1: timeseries 1
ts2: timeseries 2
t: x-axis (time)
Returns: hmtl output of an interactive timeseries plot
"""
trace0 = scatter(x=t,
y=ts1,
name="Domain Reach",
color=cliqz_colors["purple"])
trace1 = scatter(x=t, y=ts2, name="Page Reach", color=cliqz_colors["blue"])
layout = go.Layout(margin=set_margins(t=30), height=300)
# makes sure that whichever is smallest
# will be on top (displaying color correctly)
if mean(ts1) > mean(ts2):
data = [trace0, trace1]
else:
data = [trace1, trace0]
fig = dict(data=data, layout=layout)
return div_output(fig)
def overview_reach(companies):
data = []
annotations = []
for c in companies:
color = random_color()
ts = [datetime.strptime(t["ts"], "%Y-%m") for t in c["history"]]
name = c["overview"]["id"].capitalize()
y = [t['reach']*100 for t in c["history"]]
data.append(
scatter(
x=ts,
y=y,
fill=False,
name=name,
color=color
)
)
annotations.append(
overview_label(text=name, x=ts[-1], y=y[-1], color=color)
)
layout = go.Layout(
dict(
yaxis=dict(
title="Percentage of sites where company can track",
titlefont=dict(
size=12,
color="#666666"
)),
margin=set_margins(r=90),
legend=dict(
x=0,
y=50,
orientation="h"
),
# annotations=annotations
)
)
fig = dict(data=data, layout=layout)
return div_output(fig)