def graph_caller(ylabel,
date_selected,
premade_df,
title,
ylog=False,
yrange=None,
hue='state'):
'''
Calls h.line_plotter(). Created to avoid repetitive code.
input
-----
yrange: tuple
None or tuple. If tuple, indicates the min and max values for y axis
'''
if not yrange:
st.plotly_chart(
h.line_plotter(
"date",
ylabel,
date_selected,
dataset=premade_df,
hue=hue,
ylog=ylog,
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"state": ""
},
title=title,
),
use_container_width=False,
)
else:
st.plotly_chart(
h.line_plotter(
"date",
ylabel,
date_selected,
dataset=premade_df,
hue=hue,
ylog=ylog,
range_y=yrange,
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"state": ""
},
title=title,
),
use_container_width=False,
)
def graph_caller(
ylabel, date_selected, premade_df, title, ylog=False, perc_range=False
):
"""
Calls h.line_plotter(). Created to avoid repetitive code.
"""
if perc_range:
st.info('The CDC [has not defined](https://www.cdc.gov/coronavirus/2019-ncov/communication/vaccination-toolkit.html) a threshold for herd immunity against COVID19, however 70% is cited by the [Mayoclinic](https://www.mayoclinic.org/diseases-conditions/coronavirus/in-depth/herd-immunity-and-coronavirus/art-20486808).')
fig = h.line_plotter(
"date",
ylabel,
date_selected,
dataset=premade_df,
hue="state",
ylog=ylog,
range_y=(0, 100),
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"state": "",
},
title=title,
)
fig.add_hline(y=70, line_dash='dot', line_color='red', annotation_text='Herd immunity')
st.plotly_chart(fig, use_container_width=False)
else:
st.plotly_chart(
h.line_plotter(
"date",
ylabel,
date_selected,
dataset=premade_df,
hue="state",
ylog=ylog,
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"state": "",
},
title=title,
),
use_container_width=False,
)
def graph_caller(
ylabel, date_selected, premade_df, title, ylog=False, perc_range=False
):
"""
Calls h.line_plotter(). Created to avoid repetitive code.
"""
if perc_range:
st.plotly_chart(
h.line_plotter(
"date",
ylabel,
date_selected,
dataset=premade_df,
hue="location",
ylog=ylog,
range_y=(0, 100),
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"location": "",
},
title=title,
),
use_container_width=False,
)
else:
st.plotly_chart(
h.line_plotter(
"date",
ylabel,
date_selected,
dataset=premade_df,
hue="location",
ylog=ylog,
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"location": "",
},
title=title,
),
use_container_width=False,
)
def graph_new_doses(ylabel, date_selected, premade_df, title):
"""
Sole function to graph new doses and call functions to add annotations to the graph
Source for annotations: https://plotly.com/python/reference/layout/annotations
"""
fig = px.line(
data_frame=premade_df,
x="date",
y=ylabel,
range_x=date_selected,
labels={
ylabel: h.ylabel_format(ylabel, ylog=False),
"state": "",
"date": "",
},
color="state",
title="New doses administered per million"
)
unique_states = premade_df["state"].unique()
st.plotly_chart(fig)
def overview(yesterday, dataframe):
'''
Show who's winning the vaccine wars
'''
choose = st.sidebar.radio("", options = ["Fully vaccinated", "Partially vaccinated"]).lower()
top_df = dataframe[dataframe.date.apply(lambda x: True if x.date() == yesterday else False)]
color = None
sort = st.checkbox("Sort by region")
if sort:
color = 'region'
if "fully" in choose:
col = 'all_doses_vaccinated_per_hundred'
res = top_df.sort_values(col, ascending=False)
title='Fully vaccinated population'
description = "__Description:__ Percent of population who are fully vaccinated, whether through one (ex: JJ) or two (ex: Pfizer) doses"
elif "partially" in choose:
col = 'one_dose_vaccinated_per_hundred'
res = top_df.sort_values(col, ascending=False)
title='At least one dose administered'
description = "__Description:__ Percent of population who are only partially vaccinated (ex: one dose of Pfizer)"
res = res[~res['state'].str.contains('Puerto')]
fig = px.bar(
data_frame = res,
x='state',
y=col,
color=color,
range_y=(0,100),
title=title,
labels={
col:h.ylabel_format(col, ylog=False),
'state':'',
'region':'Region'
}
)
fig.add_hline(y=70, line_dash='dot', line_color='red', annotation_text='Herd immunity')
st.plotly_chart(fig)
st.write("")
st.write(description)
def graph_new_doses(ylabel, date_selected, premade_df, title):
"""
Sole function to graph new doses and call functions to add annotations to the graph
Source for annotations: https://plotly.com/python/reference/layout/annotations
"""
info_box = st.empty()
show_annot = st.checkbox("Show annotations",value=True)
fig = px.line(
data_frame=premade_df,
x="date",
y=ylabel,
range_x=date_selected,
labels={
ylabel: h.ylabel_format(ylabel, ylog=False),
"location": "",
"date": "",
},
color="location",
title="New doses administered per million"
)
unique_locations = premade_df["location"].unique()
if show_annot:
all_annotations = h.get_annotation_data(unique_locations, label='vax', conn=news_cnx)
if not all_annotations:
st.plotly_chart(fig)
else:
for country in all_annotations.keys():
h.annotation_creator( # add annotations to the graph
fig=fig, ylabel=ylabel, df=premade_df, annotation_settings=all_annotations[country]
)
info_box.info("__Tip__: Move cursor over annotations for more details")
st.plotly_chart(fig)
else:
info_box.info("__Tip__: Move cursor over annotations for more details")
st.plotly_chart(fig)
def graph_caller(ylabel,
date_selected,
premade_df,
title,
show_annot=False,
ylog=False,
yrange=None,
hue='location'):
'''
Calls h.line_plotter(). Created to avoid repetitive code.
input
-----
yrange: tuple
None or tuple. If tuple, indicates the min and max values for y axis
'''
if not yrange: # no limit on the y axis
fig = h.line_plotter( # h.lineplotter returns a tuple with 1 item, the fig
"date",
ylabel,
date_selected,
dataset=premade_df,
hue=hue,
ylog=ylog,
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"location": ""
},
title=title,
),
else: # y axis is limited by tuple
fig = h.line_plotter( # h.lineplotter returns a tuple with 1 item, the fig
"date",
ylabel,
date_selected,
dataset=premade_df,
hue=hue,
ylog=ylog,
range_y=yrange,
labels={
ylabel: h.ylabel_format(ylabel, ylog),
"date": "",
"location": ""
},
title=title,
),
if show_annot:
all_locations = premade_df['location'].unique()
all_annotations = h.get_annotation_data(all_locations,
label='cases',
conn=news_cnx)
if not all_annotations: # all_annotations is None, dont call annotation creator
st.plotly_chart(fig[0])
else:
for country in all_annotations.keys():
h.annotation_creator(
fig[0],
ylabel,
df=premade_df,
annotation_settings=all_annotations[country])
st.plotly_chart(fig[0])
else:
st.plotly_chart(fig[0])