def concat_ngdp_vis(year, geo):
nominal_gdp = alt.Chart(
eco, title="Total GDP").mark_bar().transform_aggregate(
groupby=['Geography', 'Year'], GDP='sum(Nominal GDP)').encode(
x=alt.X('sum(GDP):Q',
title='CA$ (MM)',
axis=alt.Axis(titleFontSize=20,
grid=False,
ticks=False,
labels=False)),
y=alt.Y('Geography:O',
sort='-x',
title=None,
axis=alt.Axis(labelFontSize=20,
ticks=False,
grid=False)),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography', equal=geo)).transform_filter(
alt.FieldEqualPredicate(
field='Year', equal=year)).properties(
height=200, width=400).mark_text(
dx=-175, color='darkblue',
size=40).encode(text=alt.Text(
'sum(GDP):Q', format=('$,')))
nominal_gdp_gr = alt.Chart(
eco_gr, title="Growth rate").mark_bar().transform_aggregate(
groupby=['Geography', 'Year'], GDP='sum(Nominal GDP)').encode(
x=alt.X('sum(GDP):Q',
title='Yearly %',
axis=alt.Axis(titleFontSize=20,
grid=False,
ticks=False,
labels=False)),
y=alt.Y('Geography:O',
sort='-x',
title=None,
axis=alt.Axis(grid=False, ticks=False, labels=False)),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography', equal=geo)).transform_filter(
alt.FieldEqualPredicate(
field='Year', equal=year)).properties(
height=200, width=400).mark_text(
dx=-175, color='darkblue',
size=40).encode(text=alt.Text(
'sum(GDP):Q', format=('.2%')))
nominal_gdp_evo = alt.Chart(eco, title="GDP evolution").mark_area(
point=alt.OverlayMarkDef(filled=False, fill='darkblue')).encode(
x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('sum(Nominal GDP):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=('$,f')),
title=None),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('sum(Nominal GDP):Q', format=('$,'), title='GDP')
]).transform_filter(
alt.FieldEqualPredicate(field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2000, year]))
nominal_gdp_rank = alt.Chart(
eco, title="Contribution by province/territory").mark_bar().encode(
x=alt.X('sum(Nominal GDP):Q',
title='CA$ (MM)',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
format=('$,f'))),
y=alt.Y('Geography:O',
sort='-x',
axis=alt.Axis(labelFontSize=18),
title=None),
color=alt.condition((alt.datum.Geography == geo) |
(alt.datum.Geography == 'Canada'),
alt.value('darkblue'), alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('sum(Nominal GDP):Q', format=('$,'), title='GDP')
]).transform_filter(
alt.FieldEqualPredicate(field='Year', equal=year))
nominal_gdp_gr_evo = alt.Chart(eco_gr, title="GDP growth rates").mark_bar(
point=alt.OverlayMarkDef(filled=False, fill='darkblue'),
size=16).encode(x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('sum(Nominal GDP):Q',
axis=alt.Axis(tickCount=3,
grid=False,
ticks=False,
format=('%')),
title=None),
color=alt.condition((alt.datum.Year == year),
alt.value('darkblue'),
alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography',
title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('sum(Nominal GDP):Q',
format=('.2%'),
title='Growth rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2000, year]))
nominal_gdp_gr_rank = alt.Chart(
eco_gr, title="By province/territory").mark_bar().encode(
x=alt.X('sum(Nominal GDP):Q',
title=None,
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
format=('%'))),
y=alt.Y('Geography:O',
sort='-x',
axis=alt.Axis(labelFontSize=18),
title=None),
color=alt.condition((alt.datum.Geography == geo) |
(alt.datum.Geography == 'Canada'),
alt.value('darkblue'), alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('sum(Nominal GDP):Q',
format=('.2%'),
title='Growth rate')
]).transform_filter(
alt.FieldEqualPredicate(field='Year', equal=year))
w = 300
h = 200
nominal_gdp = nominal_gdp.properties(width=w, height=h)
nominal_gdp_gr = nominal_gdp_gr.properties(width=w, height=h)
nominal_gdp_evo = nominal_gdp_evo.properties(width=w, height=h)
nominal_gdp_rank = nominal_gdp_rank.properties(width=w, height=h)
nominal_gdp_gr_evo = nominal_gdp_gr_evo.properties(width=w, height=h)
nominal_gdp_gr_rank = nominal_gdp_gr_rank.properties(width=w, height=h)
ngdp_summary = (nominal_gdp | nominal_gdp_gr)
ngdp_total = (nominal_gdp_evo | nominal_gdp_rank)
ngdp_gr = (nominal_gdp_gr_evo | nominal_gdp_gr_rank)
ngdp_vis = ((ngdp_summary & ngdp_total)
& ngdp_gr).configure_view(strokeOpacity=0).configure_axis(
domain=False).configure_title(fontSize=30)
return ngdp_vis.to_html()
def concat_employment_vis(year, geo):
er_evo = alt.Chart(eco, title="Unemployment rate evolution").mark_area(
point=alt.OverlayMarkDef(filled=False, fill='darkblue')).encode(
x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(Unemployment rate):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=('%')),
title=None),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(Unemployment rate):Q',
format=('.2%'),
title='Unemployment rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography', equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2000, year])).properties(height=430)
er_rank = alt.Chart(
eco,
title="Unemployment rate by province/territory").mark_bar().encode(
x=alt.X('average(Unemployment rate):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=('%')),
title=None),
y=alt.Y('Geography:O',
sort='-x',
axis=alt.Axis(labelFontSize=18),
title=None),
color=alt.condition((alt.datum.Geography == geo) |
(alt.datum.Geography == 'Canada'),
alt.value('darkblue'), alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(Unemployment rate):Q',
format=('.2%'),
title='Unemployment rate')
]).transform_filter(
alt.FieldEqualPredicate(field='Year', equal=year))
er_ind_rank = alt.Chart(
labour, title="Unemployment rate by industry").mark_bar().encode(
x=alt.X('Unemployment rate:Q',
axis=alt.Axis(tickCount=3,
grid=False,
ticks=False,
format=('%')),
title=None),
y=alt.Y('Industry:O',
sort='-x',
axis=alt.Axis(labelFontSize=18),
title=None),
color=alt.value('lightblue'),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('Industry'),
alt.Tooltip('Unemployment rate:Q',
format=('.2%'),
title='Unemployment rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Year', equal=year)).transform_filter(
alt.FieldEqualPredicate(field='Geography', equal=geo))
w = 300
h = 200
# nominal_gdp = nominal_gdp.properties(
# width=w,
# height=h
# )
#
# nominal_gdp_gr = nominal_gdp_gr.properties(
# width=w,
# height=h
# )
#
# nominal_gdp_evo = nominal_gdp_evo.properties(
# width=w,
# height=h
# )
er_ind_rank = er_ind_rank.properties(width=w, height=h)
er_rank = er_rank.properties(width=w, height=h)
er_evo = er_evo.properties(width=w, height=h)
employment_plot = ((er_evo | er_rank) & er_ind_rank).configure_view(
strokeOpacity=0).configure_axis(domain=False).configure_title(
fontSize=30)
return employment_plot.to_html()
def main():
#st.write(pd.value_counts(dados_covid["resultadoTeste"]))
st.sidebar.title('HACKATHON 1')
st.sidebar.subheader('Análise dados COVID-19')
filtro_coluna = st.sidebar.selectbox(
'Selecione o filtro', ('Dados Gerais', 'Idade', 'Sexo', 'Sintomas'))
if filtro_coluna:
if filtro_coluna == 'Dados Gerais':
st.write(dados_covid.head(1000))
if st.checkbox("Mostrar colunas"):
st.write(dados_covid.count())
if filtro_coluna == 'Sexo':
st.subheader('Sexo por resultado do teste')
sexo_barras = alt.Chart(dados_covid, width=200).mark_bar().encode(
alt.X('sexo:O', axis=alt.Axis(title='')),
alt.Y('count():Q'),
alt.Column('resultadoTeste:O'),
color=alt.Color('sexo:N',
scale=alt.Scale(range=["#EA98D2", "#659CCA"])),
tooltip='count()').interactive()
st.altair_chart(sexo_barras)
# count_sexo = pd.value_counts(dados_covid['sexo'])color=alt.Color('gender:N', scale=alt.Scale(range=["#EA98D2", "#659CCA"]))
# st.write(count_sexo)
# st.bar_chart(count_sexo)
if filtro_coluna == 'Idade':
st.markdown('Describe da coluna Idade')
st.write(dados_covid.idade.describe())
st.subheader('Idade por resultado teste')
idade_barras = alt.Chart(dados_covid, width=200).mark_bar().encode(
alt.X('idade', bin=alt.Bin(maxbins=20)),
alt.Y('count():Q'),
alt.Column('resultadoTeste:O'),
color='resultadoTeste',
tooltip=['idade', 'count()']).transform_filter(
alt.FieldRangePredicate(field='idade',
range=[0, 120])).interactive()
st.altair_chart(idade_barras, use_container_width=True)
idade_line = alt.Chart(dados_covid, width=600).mark_line().encode(
x='idade', y='count():Q',
color='resultadoTeste:O').transform_filter(
alt.FieldRangePredicate(field='idade', range=[0, 100]))
st.altair_chart(idade_line)
if filtro_coluna == 'Sintomas':
st.subheader('Sintomas relatados')
sintomas = dados_covid.columns[4:]
df_sintomas = dados_covid[sintomas].sum().reset_index()
df_sintomas.columns = ['sintoma', 'count']
st.write(df_sintomas)
sintomas_bar = alt.Chart(df_sintomas, width=700).mark_bar().encode(
x='sintoma', y='count', tooltip=['count']).interactive()
st.write("\n\n")
st.altair_chart(sintomas_bar)
st.subheader('Sintomas por resultado do teste')
grouped = dados_covid.groupby(['resultadoTeste'])[sintomas].sum()
st.write(grouped)
st.write("\n\n\n")
st.bar_chart(grouped)
select = st.multiselect(
"Selecione combinação de sintomas apresentados",
dados_covid.columns[4:].tolist(),
default=["Febre"])
df_select = countsintomas(select, sintomas)
df_select
# st.write("Numero de ocorrências: ", len(df_select.index))
st.write(df_select.groupby(['resultadoTeste'])[sintomas].sum())
st.markdown(
'->Número de pessoas que aprensentaram apenas os sintomas selecionados'
)
st.sidebar.subheader('Grupo 1')
st.sidebar.markdown('Daniel Santos Pereira')
st.sidebar.markdown('Fernando Henrique De Brito Borges')
st.sidebar.markdown('Gláucio Ribeiro Santos')
st.sidebar.markdown('Rafael Rodrigues dos Santos')
def concat_earnings_vis(year, geo):
all_ear_evo = alt.Chart(eco, title="All industries").mark_area(
point=alt.OverlayMarkDef(filled=False, fill='darkblue')).encode(
x=alt.X('Year',
title='CA$',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(All industries):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=('$,f')),
title=None),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(All industries):Q',
format=('$,'),
title='Earnings')
]).transform_filter(
alt.FieldEqualPredicate(field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2002, year]))
all_ear_gr_evo = alt.Chart(eco_gr, title="Growth rates").mark_bar(
point=alt.OverlayMarkDef(filled=False, fill='darkblue'),
size=16).encode(x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(All industries):Q',
axis=alt.Axis(tickCount=3,
grid=False,
ticks=False,
format=('%')),
title=None),
color=alt.condition((alt.datum.Year == year),
alt.value('darkblue'),
alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography',
title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(All industries):Q',
format=('.2%'),
title='Growth rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2002, year]))
goods_ear_evo = alt.Chart(eco, title="Goods-producing sector").mark_area(
point=alt.OverlayMarkDef(filled=False, fill='darkblue')).encode(
x=alt.X('Year',
title='CA$',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(Goods-producing sector):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=('$,f')),
title=None),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(Goods-producing sector):Q',
format=('$,'),
title='Earnings')
]).transform_filter(
alt.FieldEqualPredicate(field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2002, year]))
goods_ear_gr_evo = alt.Chart(eco_gr, title="Growth rates").mark_bar(
point=alt.OverlayMarkDef(filled=False, fill='darkblue'),
size=16).encode(x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(Goods-producing sector):Q',
axis=alt.Axis(tickCount=3,
grid=False,
ticks=False,
format=('%')),
title=None),
color=alt.condition((alt.datum.Year == year),
alt.value('darkblue'),
alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography',
title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(Goods-producing sector):Q',
format=('.2%'),
title='Growth rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2002, year]))
serv_ear_evo = alt.Chart(eco, title="Service-producing").mark_area(
point=alt.OverlayMarkDef(filled=False, fill='darkblue')).encode(
x=alt.X('Year',
title='CA$',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(Service-producing sector):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=('$,f')),
title=None),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(Service-producing sector):Q',
format=('$,'),
title='Earnings')
]).transform_filter(
alt.FieldEqualPredicate(field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2002, year]))
serv_ear_gr_evo = alt.Chart(eco_gr, title="Growth rates").mark_bar(
point=alt.OverlayMarkDef(filled=False, fill='darkblue'),
size=16).encode(x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(Service-producing sector):Q',
axis=alt.Axis(tickCount=3,
grid=False,
ticks=False,
format=('%')),
title=None),
color=alt.condition((alt.datum.Year == year),
alt.value('darkblue'),
alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography',
title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(Service-producing sector):Q',
format=('.2%'),
title='Growth rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2002, year]))
w = 300
h = 200
serv_ear_gr_evo = serv_ear_gr_evo.properties(width=w, height=h)
serv_ear_evo = serv_ear_evo.properties(width=w, height=h)
goods_ear_gr_evo = goods_ear_gr_evo.properties(width=w, height=h)
goods_ear_evo = goods_ear_evo.properties(width=w, height=h)
all_ear_gr_evo = all_ear_gr_evo.properties(width=w, height=h)
all_ear_evo = all_ear_evo.properties(width=w, height=h)
all_ear = (all_ear_evo | all_ear_gr_evo)
goods_ear = (goods_ear_evo | goods_ear_gr_evo)
serv_ear = (serv_ear_evo | serv_ear_gr_evo)
earnings_plot = ((all_ear & serv_ear) & goods_ear).configure_view(
strokeOpacity=0).configure_axis(domain=False).configure_title(
fontSize=30)
return earnings_plot.to_html()
def concat_cpi_vis(year, geo):
all_cpi_evo = alt.Chart(eco, title="CPI all-items evolution").mark_area(
point=alt.OverlayMarkDef(filled=False, fill='darkblue')).encode(
x=alt.X('Year',
title='2002=100',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(All-items):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=(',.0f')),
title=None),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(All-items):Q',
format=('.0f'),
title='CPI')
]).transform_filter(
alt.FieldEqualPredicate(field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2000, year]))
all_cpi_gr = alt.Chart(eco_gr, title="Growth rates").mark_bar(
point=alt.OverlayMarkDef(filled=False, fill='darkblue'),
size=16).encode(x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('sum(All-items):Q',
axis=alt.Axis(tickCount=3,
grid=False,
ticks=False,
format=('%')),
title=None),
color=alt.condition((alt.datum.Year == year),
alt.value('darkblue'),
alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography',
title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('sum(All-items):Q',
format=('.2%'),
title='Growth rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2000, year]))
gasoline_cpi_evo = alt.Chart(
eco, title="CPI gasoline evolution").mark_area(
point=alt.OverlayMarkDef(filled=False, fill='darkblue')).encode(
x=alt.X('Year',
title='2002=100',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('average(Gasoline):Q',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
ticks=False,
format=(',.0f')),
title=None),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(Gasoline):Q', title='CPI')
]).transform_filter(
alt.FieldEqualPredicate(field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2000, year]))
gasoline_cpi_gr = alt.Chart(eco_gr, title="Growth rates").mark_bar(
point=alt.OverlayMarkDef(filled=False, fill='darkblue'),
size=16).encode(x=alt.X('Year',
title='Year',
axis=alt.Axis(tickCount=5,
titleFontSize=20,
grid=False,
ticks=False,
format='Y')),
y=alt.Y('sum(Gasoline):Q',
axis=alt.Axis(tickCount=3,
grid=False,
ticks=False,
format=('%')),
title=None),
color=alt.condition((alt.datum.Year == year),
alt.value('darkblue'),
alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography',
title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('sum(Gasoline):Q',
format=('.2%'),
title='Growth rate')
]).transform_filter(
alt.FieldEqualPredicate(
field='Geography',
equal=geo)).transform_filter(
alt.FieldRangePredicate(
'Year', [2000, year]))
cpi_rank = alt.Chart(
eco, title="CPI all-items by province/territory").mark_bar().encode(
x=alt.X('average(All-items):Q',
title='2002=100',
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
format=(',.0f'))),
y=alt.Y('Geography:O',
sort='-x',
axis=alt.Axis(labelFontSize=18),
title=None),
color=alt.condition((alt.datum.Geography == geo) |
(alt.datum.Geography == 'Canada'),
alt.value('darkblue'), alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(All-items):Q', title='CPI')
]).transform_filter(
alt.FieldEqualPredicate(field='Year', equal=year))
cpi_gr_rank = alt.Chart(
eco_gr, title="Growth rate by province/territory").mark_bar().encode(
x=alt.X('average(All-items):Q',
title=None,
axis=alt.Axis(tickCount=3,
titleFontSize=20,
grid=False,
format=('%'))),
y=alt.Y('Geography:O',
sort='-x',
axis=alt.Axis(labelFontSize=18),
title=None),
color=alt.condition((alt.datum.Geography == geo) |
(alt.datum.Geography == 'Canada'),
alt.value('darkblue'), alt.value('lightblue')),
tooltip=[
alt.Tooltip('Geography', title='Province/territory'),
alt.Tooltip('Year'),
alt.Tooltip('average(All-items):Q',
format=('.2%'),
title='CPI')
]).transform_filter(
alt.FieldEqualPredicate(field='Year', equal=year))
w = 300
h = 200
all_cpi_evo = all_cpi_evo.properties(width=w, height=h)
all_cpi_gr = all_cpi_gr.properties(width=w, height=h)
gasoline_cpi_evo = gasoline_cpi_evo.properties(width=w, height=h)
gasoline_cpi_gr = gasoline_cpi_gr.properties(width=w, height=h)
cpi_rank = cpi_rank.properties(width=w, height=h)
cpi_gr_rank = cpi_gr_rank.properties(width=w, height=h)
all_cpi = (all_cpi_evo | all_cpi_gr)
gasoline_cpi = (gasoline_cpi_evo | gasoline_cpi_gr)
rank_cpi = (cpi_rank | cpi_gr_rank)
cpi_plot = ((all_cpi & gasoline_cpi)
& rank_cpi).configure_view(strokeOpacity=0).configure_axis(
domain=False).configure_title(fontSize=30)
return cpi_plot.to_html()