def choropleth_drug(data: CardLiveData, world: geopandas.GeoDataFrame):
df_geo = data.sample_counts(['geo_area_code',
'geo_area_name_standard']).reset_index()
# Remove N/A from counts so it doesn't mess with colors of map
df_geo = df_geo[~df_geo['geo_area_name_standard'].str.contains('N/A')]
if df_geo.empty or df_geo['count'].sum() == 0:
fig = EMPTY_MAP
else:
fig = px.choropleth(
df_geo,
geojson=world,
locations='geo_area_code',
featureidkey='properties.un_m49_numeric',
color='count',
color_continuous_scale='YlGnBu',
hover_data=['geo_area_name_standard'],
# Off-center to avoid a color fill issue with Antarctica
# where the oceans get filled instead of the continent
center={
'lat': 0,
'lon': 0.01
},
title='Samples by geographic region',
)
fig.update_traces(hovertemplate=(
'<b style="font-size: 125%;">%{customdata[0]}</b><br>'
'<b>Count:</b> %{z}<br>'))
fig.update_layout(
margin={
"r": 0,
"t": 35,
"l": 0,
"b": 0
},
coloraxis_colorbar=dict(
title='Count',
yanchor='middle',
y=0.5,
len=1,
lenmode='fraction',
outlinecolor='black',
outlinewidth=1,
bgcolor='white',
thickness=25,
thicknessmode='pixels',
),
)
return fig
def totals_figure(data: CardLiveData, type_value: str,
color_by_value: str) -> go.Figure:
type_col = TOTALS_COLUMN_SELECT_NAMES[type_value]
color_col = TOTALS_COLUMN_SELECT_NAMES[color_by_value]
if type_col == color_col or color_by_value == 'default':
count_by_columns = [type_col]
else:
count_by_columns = [type_col, color_col]
if data.empty:
fig = EMPTY_FIGURE
else:
totals_df = data.sample_counts(count_by_columns).reset_index()
type_col_name = TOTALS_COLUMN_DATAFRAME_NAMES[type_value]
color_col_name = TOTALS_COLUMN_DATAFRAME_NAMES[color_by_value]
category_orders = order_categories(totals_df,
type_col_name,
by_sum=True,
sum_col='count')
if color_by_value != 'default':
category_orders.update(
order_categories(totals_df,
color_col_name,
by_sum=True,
sum_col='count'))
fig = px.bar(
totals_df,
y=type_col_name,
x='count',
color=color_col_name,
height=get_figure_height(len(totals_df[type_col_name].unique())),
category_orders=category_orders,
labels={
'count': 'Samples count',
'geo_area_name_standard': 'Geographic region',
'lmat_taxonomy': 'Organism',
'rgi_kmer_taxonomy': 'Organism'
},
title=TOTALS_FIGURE_TITLES[type_value],
)
fig.update_layout(font={'size': 14},
yaxis={
'title': '',
'ticksuffix': TICKSPACE
})
return fig