1.1.1.3. pymacies_arg.extractor module

PymaciesArg.

An extension that registers all pharmacies in Argentina.

class pymacies_arg.extractor.UrlExtractor(name, url)[source]

Bases: object

Collapse your data into a single data frame.

Parameters

  • name (str) – The name of data (in this case, pharmacies) to extract.

  • url (str) – Describe the url such that allows then data.

Returns

  • An instance of UrlExtractor containing two methods named

  • extract() and trasform() for all the information of

  • pharmacies in Córdoba.

Examples

>>> import pathlib
>>> from pymacies_arg import UrlExtractor, Transform, trasform_raws
>>> name="pharmacies"
>>> url="http://datos.salud.gob.ar/dataset\
... /39117f8f-e2bc-4571-a572-15a6ce7ea9e1\
... /resource/19338ea7-a492-4af3-b212-18f8f4af9184\
... /download/establecimientos-farmacias-enero-2021.csv"
>>> url_extractor=UrlExtractor(name=name, url=url)
>>> url_extractor.__repr__()
'<Extractor for Name: farmacias, URL: <long_url>>'
>>> base_file_dir=pathlib.Path("/path/to/project")
>>> path_to_csv = url_extractor.extract(
... date_str="2022-03-28", base_file_dir=base_file_dir)
>>> path_to_csv
PosixPath('/path/to/project/data/pharmacies/2022-03/pharmacies-28-03-2022.csv')
>>> import pandas as pd
>>> df = pd.read_csv(path_to_csv)
>>> data_transform = Transform()
>>> data_transform.transform(df)
                   id  ...  web
0      70260072329721  ...  NaN
1      70100352324743  ...  NaN
2      70064412318286  ...  NaN
3      70340492347884  ...  NaN
4      70140142334991  ...  NaN
...               ...  ...  ...
13672  70460212355713  ...  NaN
13673  70421472354613  ...  NaN
13674  70940142195567  ...  NaN
13675  70420702154608  ...  NaN
13676  70064272320083  ...  NaN

[13677 rows x 11 columns] >>> trasform_raws(date_str, file_paths, province, base_file_dir)

extract(date_str: str, base_file_dir: pathlib.Path) → str[source]

Extract your data into a single csv file.

Inspect the .csv and extract with data related whit pharmmacies.

Parameters

date_str (str) – The date on run with format YYYY-mm-dd.

Returns

file_path – The destination location for your csv file.

Return type

str

file_path_crib = 'data/{category}/{year}-{month:02d}/{category}-{day:02d}-{month:02d}-{year}.csv'