11 fetch preprocess gdp #16

Juan-Mateos · 2021-11-23T09:43:52Z

Closes #7
Closes #12
Closes #11

georgerichardson · 2021-11-30T11:21:02Z

I got the following error log when I cloned the repo and ran make install from the pip install xlrd command

ERROR: Could not find a version that satisfies the requirement xldr (from industrial-taxonomy[dev]) (from versions: none)
ERROR: No matching distribution found for xldr

georgerichardson

General comments

Is there a need to have population data gathered from the GDP and population flows separately? Is this to get GPD per capita per year later?
Minor: inconsitencies with whitespace between lines. Have noted a few
Should we document the shapes of the data outputs from the flows either in the docstring or in the readme?

What I did

cloned the respository and ran make install on this branch from scratch
ran python industrial_taxonomy/pipeline/sic/flow.py --production run
ran python industrial_taxonomy/pipeline/official/gdp/flow.py run
Did not finish. See xlrd error in industrial_taxonomy/pipeline/official/utils.py below
ran python industrial_taxonomy/pipeline/official/nomis/flow.py run
Finished running
Example output for nomis_dict

{'date': 2019,
 'geography_name': 'Tower Hamlets',
 'geography_code': 'E09000030',
 'variable': 'Economic activity rate - aged 16-64',
 'value': 74.2,
 'source': 'aps'},
{'date': 2019,
 'geography_name': 'Tower Hamlets',
 'geography_code': 'E09000030',
 'variable': 'Employment rate - aged 16-64',
 'value': 71.4,
 'source': 'aps'},
{'date': 2019,
 'geography_name': 'Tower Hamlets',
 'geography_code': 'E09000030',
 'variable': '% with NVQ4+ - aged 16-64',
 'value': 60.5,
 'source': 'aps'},
{'date': 2019,
 'geography_name': 'Tower Hamlets',
 'geography_code': 'E09000030',
 'variable': '% with other qualifications (NVQ) - aged 16-64',
 'value': 8.3,
 'source': 'aps'},
{'date': 2019,
 'geography_name': 'Tower Hamlets',
 'geography_code': 'E09000030',
 'variable': '% with no qualifications (NVQ) - aged 16-64',
 'value': 9.7,
 'source': 'aps'},

ran python industrial_taxonomy/pipeline/official/population/flow.py run\
Finished running
Example output for pop_est

...
 'N09000006': 117337,
'N09000007': 146452,
'N09000008': 139443,
'N09000009': 148953,
'N09000010': 181669}

georgerichardson · 2021-11-30T11:51:39Z

industrial_taxonomy/pipeline/official/utils.py

+    return response.content
+
+
+def excel_to_df(content: bytes, sheets: int, skiprows: int):


This throws ImportError: Missing optional dependency 'openpyxl'. Use pip or conda to install openpyxl I think because pandas now defaults to using openpyxl to open .xlsx files. I think you either need to specify the engine or add openpyxl to requirements.txt

Separately, I'm not sure I see the value in this function as it's just a very thin wrapper around pd.read_excel that removes access to some parameters.

georgerichardson · 2021-11-30T11:59:27Z

README.md

@@ -12,8 +12,6 @@

 ## Features

-### Pipeline
-
 Read instructions to reproduce the pipeline in `industrial_taxonomy/pipeline/README.md`.


Add equivalents for nomis, gdp and population?

georgerichardson · 2021-11-30T12:50:03Z

industrial_taxonomy/pipeline/official/gdp/flow.py

+
+        # Create dfs for the sheets with relevant information (population and GVA)
+        self._pop_raw, self._gva_raw = [
+            excel_to_df(gdp_table, sheets=sh, skiprows=1) for sh in [7, 8]


More of a general question as to whether these kinds of hard coded variables should be kept in a config file?

georgerichardson · 2021-11-30T13:10:43Z

industrial_taxonomy/pipeline/official/nomis/flow.py

+_APS_URL = "https://www.nomisweb.co.uk/api/v01/dataset/NM_17_5.data.csv?geography=1811939329...1811939332,1811939334...1811939336,1811939338...1811939497,1811939499...1811939501,1811939503,1811939505...1811939507,1811939509...1811939517,1811939519,1811939520,1811939524...1811939570,1811939575...1811939599,1811939601...1811939628,1811939630...1811939634,1811939636...1811939647,1811939649,1811939655...1811939664,1811939667...1811939680,1811939682,1811939683,1811939685,1811939687...1811939704,1811939707,1811939708,1811939710,1811939712...1811939717,1811939719,1811939720,1811939722...1811939730&date=2019-12&variable=18,45,290,335,344&measures=20599,21001,21002,21003"
+_ASHE_URL = "https://www.nomisweb.co.uk/api/v01/dataset/NM_30_1.data.csv?geography=1811939329...1811939332,1811939334...1811939336,1811939338...1811939497,1811939499...1811939501,1811939503,1811939505...1811939507,1811939509...1811939517,1811939519,1811939520,1811939524...1811939570,1811939575...1811939599,1811939601...1811939628,1811939630...1811939634,1811939636...1811939647,1811939649,1811939655...1811939664,1811939667...1811939680,1811939682,1811939683,1811939685,1811939687...1811939704,1811939707,1811939708,1811939710,1811939712...1811939717,1811939719,1811939720,1811939722...1811939730&date=latest&sex=8&item=2&pay=7&measures=20100,20701"


Minor: could split into multiline

georgerichardson · 2021-11-30T14:06:04Z

industrial_taxonomy/pipeline/official/nomis/flow.py

+@project(name="industrial_taxonomy")
+class NomisTables(FlowSpec):
+    """Flow to collect APS / ASHE data from NOMIS
+    Attributes:


Suggested change

Attributes:

Attributes:

georgerichardson · 2021-11-30T14:10:33Z

industrial_taxonomy/pipeline/official/nomis/utils.py

+        value_column: value column
+        source: data source
+        indicator_column: column that contains the indicator
+    Returns:


Suggested change

Returns:

Returns:

georgerichardson · 2021-11-30T14:11:25Z

industrial_taxonomy/pipeline/official/population/flow.py

+from metaflow import FlowSpec, project, step
+from metaflow.decorators import StepDecorator
+
+URL = (


Maybe a more specific name?

georgerichardson · 2021-11-30T14:12:49Z

industrial_taxonomy/pipeline/official/population/flow.py

+    "https://www.ons.gov.uk/file?uri=/peoplepopulationandcommunity/populationandmigration/populationestimates/",
+    "datasets/populationestimatesforukenglandandwalesscotlandandnorthernireland/",
+    "mid2020/ukpopestimatesmid2020on2021geography.xls",


If the comma separation from these is removed then no need for self.url = "".join(URL) below

georgerichardson · 2021-11-30T14:20:48Z

industrial_taxonomy/pipeline/official/gdp/flow.py

+    "https://www.ons.gov.uk/file?uri=/economy/grossdomesticproductgdp/datasets/",
+    "regionalgrossdomesticproductlocalauthorities/1998to2019/",
+    "regionalgrossdomesticproductlocalauthorities.xlsx",


If the comma separation from these is removed then no need for self.url = "".join(URL) below

georgerichardson · 2021-11-30T14:25:45Z

industrial_taxonomy/pipeline/official/gdp/utils.py

+        .rename(columns={x: str(x) for x in range(1998, 2020)})
+    )
+
+    _table.columns = [re.sub(" ", "_", col.lower()) for col in _table.columns]


I think in general it's preferable to use Python string functions (in this case .replace()) over regex to avoid added complexity and for speed, although in this case it hardly makes a difference :D

Juan-Mateos · 2021-11-30T16:05:32Z

Thanks for the review! I have:

Added openpyxl to requirements
Added instructions to README
Put hardcoded variables (excel sheets / year ranges) at the top of the script
Made URL names more informative, split into multiline, removed commas
Inserted whitespace before Attributes, Arguments and Returns
Replaced regex with .replace()

Juan-Mateos · 2021-11-30T21:13:08Z

And then I added the getters.

bishax

There's a lot of minor comments here but this is much easier to read, review, and use than on previous projects 😄

One difficulty I ran into was in running the getters...
it looks like the last time you ran LocalGdpData and NomisTables you ran them with --production and --datastore local which means that when it came for me to load the data, it failed because it was trying to load a local path from your machine.
Don't combine --datastore local and --production - I've just added an issue to metaflow_extensions to explore whether it's possible to make metaflow raise a warning when this happens.
I've rerun the flows with --production and S3 datastore so that the getters work for everyone again.

bishax · 2021-12-01T08:45:07Z

industrial_taxonomy/__init__.py

@@ -16,7 +16,6 @@ def get_yaml_config(file_path: Path) -> Optional[dict]:
    if file_path.exists():
        with open(file_path, "rt") as f:
            return yaml.load(f.read(), Loader=yaml.FullLoader)
-    return None


I think this somehow got removed when merging in dev

Still need to add this back in

bishax · 2021-12-01T08:48:40Z

industrial_taxonomy/getters/official.py

+@lru_cache()
+def get_run(flow: str):
+    """Last successful run executed with `--production`.
+
+    Arguments:
+        flow: the official data flow we want to get
+    """
+    runs = Flow(flow).runs("project_branch:prod")
+    try:
+        return next(filter(lambda run: run.successful, runs))
+    except StopIteration as exc:
+        raise MetaflowNotFound("Matching run not found") from exc


Note: #25 adds this as a general util and refactors existing uses - as this PR will probably merge first I can refactor in #25

https://github.com/nestauk/industrial_taxonomy/pull/25/files#diff-00b2db5bbabdce7be9d5602c61e3c8d66ac8628e428e6149234027c25230320d

bishax · 2021-12-01T08:53:27Z

industrial_taxonomy/getters/official.py

@@ -0,0 +1,109 @@
+# Data getters for official data


Don't forget to run flake8, it will flag up a lot of minor things to fix...

❯ flake8 industrial_taxonomy industrial_taxonomy/getters/official.py:4:1: F401 'typing.Dict' imported but unused industrial_taxonomy/getters/official.py:4:1: F401 'typing.Optional' imported but unused industrial_taxonomy/getters/official.py:6:1: F401 'metaflow.Run' imported but unused industrial_taxonomy/getters/official.py:15:1: DAR201 Missing "Returns" in Docstring: - return industrial_taxonomy/getters/official.py:15:1: DAR401 Missing exception(s) in Raises section: -r MetaflowNotFound industrial_taxonomy/getters/official.py:27:1: DAR201 Missing "Returns" in Docstring: - return industrial_taxonomy/getters/official.py:43:1: DAR201 Missing "Returns" in Docstring: - return industrial_taxonomy/getters/official.py:59:1: DAR201 Missing "Returns" in Docstring: - return industrial_taxonomy/getters/official.py:80:1: DAR201 Missing "Returns" in Docstring: - return industrial_taxonomy/pipeline/official/utils.py:5:1: F401 'pandas as pd' imported but unused industrial_taxonomy/pipeline/official/population/utils.py:2:1: F401 'pandas as df' imported but unused industrial_taxonomy/pipeline/official/population/flow.py:4:1: F401 'metaflow.decorators.StepDecorator' imported but unused industrial_taxonomy/pipeline/official/population/flow.py:7:112: B950 line too long (111 > 80 characters) industrial_taxonomy/pipeline/official/nomis/utils.py:14:1: DAR101 Missing parameter(s) in Docstring: - **kwargs industrial_taxonomy/pipeline/official/nomis/flow.py:6:1: F401 'metaflow.decorators.StepDecorator' imported but unused industrial_taxonomy/pipeline/official/nomis/flow.py:12:90: B950 line too long (89 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:13:101: B950 line too long (100 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:14:101: B950 line too long (100 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:15:102: B950 line too long (101 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:16:109: B950 line too long (108 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:17:113: B950 line too long (112 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:18:90: B950 line too long (89 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:22:90: B950 line too long (89 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:23:114: B950 line too long (113 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:24:112: B950 line too long (111 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:25:114: B950 line too long (113 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:26:110: B950 line too long (109 > 80 characters) industrial_taxonomy/pipeline/official/nomis/flow.py:27:111: B950 line too long (110 > 80 characters) industrial_taxonomy/pipeline/official/gdp/utils.py:4:1: F401 're' imported but unused

bishax · 2021-12-01T09:00:44Z

industrial_taxonomy/getters/official.py

+
+@lru_cache()
+def get_run(flow: str):
+    """Last successful run executed with `--production`.


Here flake8 raises the following:

industrial_taxonomy/getters/official.py:15:1: DAR201 Missing "Returns" in Docstring: - return industrial_taxonomy/getters/official.py:15:1: DAR401 Missing exception(s) in Raises section: -r MetaflowNotFound

This might seem a bit anal but is useful to have this info for complex functions that may be used across modules.

For simpler functions with:

Obvious function name

A small number of obvious parameter names like this (suggest that flow_name is better than flow as it's less likely someone using it erroneously thinks they need to pass in a metaflow.Flow object)

Type annotations (suggest adding -> Run for the return type)

our flake8 config allows you to write a one-line docstring and not get nagged for Args/Returns/Raises

bishax · 2021-12-01T09:01:54Z

industrial_taxonomy/getters/official.py

@@ -0,0 +1,109 @@
+# Data getters for official data


For a top-level description use doc-string style rather than a # comment.
Anyone building API documentation with tools like Sphinx will then get a module-level docstring

bishax · 2021-12-01T09:48:18Z

industrial_taxonomy/pipeline/official/gdp/utils.py

+    _table = (
+        table.dropna(
+            axis=0, subset=["LA code"]  # We are dropping bottom rows without a LA code
+        )
+        .rename(columns={"2019\n[note 3]": "2019"})
+        .rename(columns={x: str(x) for x in YEAR_RANGE})
+    )
+
+    _table.columns = [col.lower().replace(" ", "_") for col in _table.columns]
+
+    return _table


pandas-fu tip: rename can take a function too...

Suggested change

_table = (

table.dropna(

axis=0, subset=["LA code"] # We are dropping bottom rows without a LA code

)

.rename(columns={"2019\n[note 3]": "2019"})

.rename(columns={x: str(x) for x in YEAR_RANGE})

)

_table.columns = [col.lower().replace(" ", "_") for col in _table.columns]

return _table

return (

table.dropna(axis=0, subset=["LA code"])

.rename(columns={"2019\n[note 3]": "2019"})

.rename(columns={x: str(x) for x in YEAR_RANGE})

.rename(columns=lambda s: s.lower().replace(" ", "_"))

)```

bishax · 2021-12-01T09:52:41Z

industrial_taxonomy/pipeline/official/nomis/utils.py

+    value_column: str,
+    source: str,
+    indicator_column: str = "MEASURES_NAME",
+    **kwargs,


kwargs isn't used

Suggested change

**kwargs,

bishax · 2021-12-01T09:58:34Z

industrial_taxonomy/pipeline/official/nomis/utils.py

+        .rename(columns=str.lower)
+        .assign(
+            date=lambda df: [  # We parse APS dates returned in format "y-m"
+                d if type(d) == int else int(d.split("-")[0]) for d in df["date"]


[Not requesting the change but] it may have been a better choice to separate things out a little more if the logic between processing APS and ASHE differs rather than having conditional logic embedded deep within the processing

bishax · 2021-12-01T09:59:41Z

industrial_taxonomy/pipeline/official/population/flow.py

+    def transform(self):
+        """Transform the population table"""
+
+        from utils import clean_popest


Inconsistent from L28

bishax · 2021-12-01T10:32:25Z

industrial_taxonomy/getters/official.py

+    )
+
+
+def nomis():


Q: from a user perspective - would it be better to have a getter for each indicator? i.e. will they be used all together or not?

Juan-Mateos · 2021-12-03T08:54:59Z

bishax

For flake8 I get (I think you added the run arg after running flake8 so missed these)

industrial_taxonomy/getters/official.py:23:1: DAR101 Missing parameter(s) in Docstring: - run
industrial_taxonomy/getters/official.py:44:1: DAR101 Missing parameter(s) in Docstring: - run
industrial_taxonomy/getters/official.py:89:1: DAR101 Missing parameter(s) in Docstring: - run

There's then 1 comment around the fact that there's a few itl1_regions still around.

On the pandas imports, I had to work around the same issue in #25 as follows (follow link)...

industrial_taxonomy/industrial_taxonomy/pipeline/glass_house/flow.py

Line 19 in 84cc4da

try: # Hack for type-hints on attributes

There is an import within flow steps as well as a top-level import within a try-except block that ignores ImportErrors that may happen when executing the flow in a remote environment like Batch before it has installed pandas (it has to run the file to understand the structure of the flow and the dependencies it needs).
Flow-level type annotations are of the form so that static analysis tools like flake8 and mypy can still resolve the imports but at runtime we don't get an error on Batch because the object DataFrame doesn't exist (because we got an ImportError above and so DataFrame isn't defined)

class MyFlow(FlowSpec):
  some_data_artifact: "DataFrame"

After the above, then:

Re-run the flows with --production
Get latest changes from dev

Then all good from me.

bishax · 2021-12-03T09:41:21Z

industrial_taxonomy/getters/official.py

+            Name: itl1_region, dtype: str, NUTS1 region (e.g. Scotland, South East etc)
+            Name: la_code, dtype: str, local authority code
+            Name: la_name, dtype: str, local authority name
+            Name: year dtype: int, year (ranges between 1998 and 2019
+            Name: gva dtype: float, £M Gross value added
+
+    """
+
+    if run is None:
+        run = get_run("LocalGdpData")
+
+    return pd.DataFrame(run.data.gva).melt(
+        id_vars=["itl1_region", "la_code", "la_name"], var_name="year", value_name="gva"
+    )
+
+
+def population_lad(run: Optional[Run] = None):
+    """get the population in a local authority
+
+    Returns:
+        Columns:
+            Name: itl1_region, dtype: str, NUTS1 region (e.g. Scotland, South East etc)
+            Name: la_code, dtype: str, local authority code
+            Name: la_name, dtype: str, local authority name
+            Name: year dtype: int, year (ranges between 1998 and 2019
+            Name: pop dtype: float, population
+
+    """
+
+    if run is None:
+        run = get_run("LocalGdpData")
+
+    return pd.DataFrame(run.data.pop).melt(
+        id_vars=["itl1_region", "la_code", "la_name"], var_name="year", value_name="pop"
+    )
+
+
+def gva_pc_lad():
+    """Get the GVA per capita in a local authority
+
+    Returns:
+        Columns:
+            Name: nuts1_name, dtype: str, NUTS1 region (e.g. Scotland, South East etc)
+            Name: la_code, dtype: str, local authority code
+            Name: la_name, dtype: str, local authority name
+            Name: year dtype: int, year (ranges between 1998 and 2019
+            Name: gva_pc dtype: float, GDP per capita
+
+    """
+
+    gva = gva_lad()
+    pop = population_lad()
+
+    return (
+        gva.merge(pop, on=["itl1_region", "la_code", "la_name", "year"])
+        .assign(gva_pc=lambda df: (1e6 * df["gva"] / df["pop"]).round(2))
+        .rename(columns={"itl1_region": "nuts1_name"})
+        .drop(axis=1, labels=["gva", "pop"])
+    )


itl1_region is renamed to nuts1_name for only 1 out of 3 getters

bishax · 2021-12-03T09:59:52Z

industrial_taxonomy/__init__.py

@@ -16,7 +16,6 @@ def get_yaml_config(file_path: Path) -> Optional[dict]:
    if file_path.exists():
        with open(file_path, "rt") as f:
            return yaml.load(f.read(), Loader=yaml.FullLoader)
-    return None


Still need to add this back in

Juan-Mateos · 2021-12-03T11:03:51Z

I did the following:

Fix new flake8 problems
Include the typing import 'hack' in the gdp and nomis flows
Change itl1_region names in all getters.
Added None to industrial_taxonomy/__init__.py.
Re-ran all the flows
Tested the getters

bishax and others added 18 commits November 15, 2021 15:10

Setup Nesta Data Science cookiecutter

7cb5b60

Do not create bucket on make init - already exists

838e6f6

added a couple of background documents

4c968c3

Add pragmatic flake8 config

2843d29

Phrasing change to nudge towards rebase

8af724b

fixup! Add pragmatic flake8 config

9a60bab

Make project default to 'project:industrial_taxonomy' metaflow namespace

3ca3447

added xlrd to requirements

167b7be

added scripts with sic preprocessing flow and utils

e9cf871

added sic lookup getter

f4035a1

added instructions to readme

6943b12

added script with utilities to fetch official data

1e030b7

added scripts to fetch and process gdp data

9466005

added the openpyxl requirement

c4cf499

added type hints to gdp flow

4bbd42a

removed gdp specific method from excel_to_df function

c926220

added dropna to process function

9e707f2

added script to fetch and process population estimates

1df0313

Juan-Mateos marked this pull request as draft November 23, 2021 09:44

Juan Mateos-Garcia added 2 commits November 23, 2021 12:20

utils to process nomis data

c861fd9

added flow to collect nomis - aps and ashe - data

0fddf29

Juan-Mateos marked this pull request as ready for review November 23, 2021 12:26

Juan-Mateos requested review from georgerichardson and bishax November 23, 2021 12:27

Juan-Mateos changed the base branch from dev to 0_setup_cookiecutter November 23, 2021 13:06

Base automatically changed from 0_setup_cookiecutter to dev November 29, 2021 15:47

Merge branch 'dev' into 11_fetch_preprocess_gdp

ffb109a

georgerichardson suggested changes Nov 30, 2021

View reviewed changes

added openpyxl to requirements

c33036b

Juan Mateos-Garcia added 5 commits November 30, 2021 15:33

Removed the excel_to_df function

23b2790

Replaced excel_to_df with pandas function

bdc1113

Replaced excel_to_df from population flow

c56b41c

added details to pipeline readme

2f3a5a5

various fixes to flows

a34945a

Juan Mateos-Garcia added 2 commits November 30, 2021 21:11

fixed bug in one of the variables being read

8a37546

added getters for official data

2d08e93

bishax reviewed Dec 1, 2021

View reviewed changes

address AB review comments

1f19cdc

Juan-Mateos requested a review from bishax December 3, 2021 08:55

bishax reviewed Dec 3, 2021

View reviewed changes

Juan Mateos-Garcia added 2 commits December 3, 2021 10:59

addressed AB review comments

2c72203

added return None

8c7950b

bishax approved these changes Dec 3, 2021

View reviewed changes

georgerichardson approved these changes Dec 3, 2021

View reviewed changes

Juan-Mateos merged commit c4890b5 into dev Dec 3, 2021

Juan-Mateos deleted the 11_fetch_preprocess_gdp branch December 3, 2021 12:45

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11 fetch preprocess gdp #16

11 fetch preprocess gdp #16

Juan-Mateos commented Nov 23, 2021 •

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		return response.content


		def excel_to_df(content: bytes, sheets: int, skiprows: int):

		_APS_URL = "https://www.nomisweb.co.uk/api/v01/dataset/NM_17_5.data.csv?geography=1811939329...1811939332,1811939334...1811939336,1811939338...1811939497,1811939499...1811939501,1811939503,1811939505...1811939507,1811939509...1811939517,1811939519,1811939520,1811939524...1811939570,1811939575...1811939599,1811939601...1811939628,1811939630...1811939634,1811939636...1811939647,1811939649,1811939655...1811939664,1811939667...1811939680,1811939682,1811939683,1811939685,1811939687...1811939704,1811939707,1811939708,1811939710,1811939712...1811939717,1811939719,1811939720,1811939722...1811939730&date=2019-12&variable=18,45,290,335,344&measures=20599,21001,21002,21003"
		_ASHE_URL = "https://www.nomisweb.co.uk/api/v01/dataset/NM_30_1.data.csv?geography=1811939329...1811939332,1811939334...1811939336,1811939338...1811939497,1811939499...1811939501,1811939503,1811939505...1811939507,1811939509...1811939517,1811939519,1811939520,1811939524...1811939570,1811939575...1811939599,1811939601...1811939628,1811939630...1811939634,1811939636...1811939647,1811939649,1811939655...1811939664,1811939667...1811939680,1811939682,1811939683,1811939685,1811939687...1811939704,1811939707,1811939708,1811939710,1811939712...1811939717,1811939719,1811939720,1811939722...1811939730&date=latest&sex=8&item=2&pay=7&measures=20100,20701"

11 fetch preprocess gdp #16

11 fetch preprocess gdp #16

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Juan-Mateos commented Nov 23, 2021 • edited by bishax Loading

georgerichardson commented Nov 30, 2021 • edited Loading

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Juan-Mateos commented Nov 30, 2021

Juan-Mateos commented Nov 30, 2021

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Juan-Mateos commented Dec 3, 2021 • edited Loading

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Juan-Mateos commented Dec 3, 2021 • edited Loading

Juan-Mateos commented Nov 23, 2021 •

edited by bishax

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georgerichardson commented Nov 30, 2021 •

edited

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Juan-Mateos commented Dec 3, 2021 •

edited

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Juan-Mateos commented Dec 3, 2021 •

edited

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