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datatiannes = /
wetadata. dataframes = [I
for i in indicators:
Nd = https://fingertips.phe.org.uk/api/all.data/csv/by.indicatet..id?
indicates. ids='+strli)+'&.bild.2062.tvRG.d-402&parent_area_type_id=6'
metadata.url='https://fingertips.phe.org.uk/api/indicator_metadata/csv/bviodicater.id?indicater.ids='+str(j)
di =Rdread-ssuludl
If = dEles[dfl'Area Code °].isin(['E08000026', 'E12000005', 'E92000001'])] #we select data for Coventry, West Midlands region, and England
if not dterapty:
the latest data available
#if data for this indicator is available
if = dtoc(dfICategory Type']. isoull()& (df['Time period Sortable] -max(dfl Time period Sortable']) ]_#we only keep
if not dilest(df'Sex]=='Persons')]empty:
#some indicators are available for 'persons', 'male' and 'female
df = dfloc[(df('Sex'=='Persons'_]_
#if the data is available for 'persons' we only include that data
if not duecl(df('Age']=='All ages') Lempty:
#some indicators have data available for 'all ages and some specific age-
categories
df = dfloc[(dflAge'l=='All ages'11.
#if the data is available for 'all ages' we only include that data
slif not diesi(dflAge'l=='16-64 ys') empty:
df = dEloc[(dfl'Age'l=='16-64 vis')]
#we don't need all columns with data, we only select the following columns
If = dfll'Indicator |Diladicator Navae"Area Code 'Area Name', 'Time Redied" "Time period range Value Lower CI 95.0
loit"oner CI 95.0 linit"Coveared to England value or peccentiles Count" "Deneminater Age Sex'I]
datatrames append(ef)
diametadata = pdread. ssu(metadata ur))
metadata dataframes.append(dimetadata)
df = pd.concat(datafrannes)
dE metadata = pd.concat (metadata dataframes)
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