# pxwebpy
[](https://github.com/stefur/pxwebpy/actions/workflows/ci.yml)
[](https://github.com/astral-sh/uv)
[](https://github.com/astral-sh/ruff)
Easily get data from the PxWeb API and into either a polars or pandas dataframe.
Pxwebpy parses the PxWeb table data as well as metadata using the json-stat2 response format.
It has been tested with [Statistics Sweden](https://scb.se), [Statistics Finland](https://www.stat.fi), [Statistics Greenland](https://stat.gl) and [Statistics Norway](https://www.ssb.no).
## Example usage
```python
>>> from pxwebpy.table import PxTable
>>> import pandas as pd
# Create a table object, setting up a URL for a table
>>> tbl = PxTable(url="https://api.scb.se/OV0104/v1/doris/sv/ssd/START/HE/HE0110/HE0110A/SamForvInk1")
# Check out the table variables that we can use
>>> tbl.get_table_variables()
{'region': ['Riket',
'Stockholms län',
'Upplands Väsby',
'Vallentuna',
...
'Piteå',
'Haparanda',
'Kiruna'],
'kön': ['män', 'kvinnor', 'totalt'],
'ålder': ['totalt 16+ år',
'16-19 år',
'totalt 20+ år',
'20-64 år',
'65+ år',
'20-24 år',
'25-29 år',
...
'75-79 år',
'80-84 år',
'85+ år'],
'inkomstklass': ['totalt',
'0',
'1-19 tkr',
'20-39 tkr',
...
'600-799 tkr',
'800-999 tkr',
'1000+ tkr'],
'tabellinnehåll': ['Medelinkomst, tkr',
'Medianinkomst, tkr',
'Totalsumma, mnkr',
'Antal personer'],
'år': ['1999',
'2000',
...
'2021',
'2022']}
# Construct a query using a selection of variables we're interested in
>>> tbl.create_query({"tabellinnehåll": ["Medianinkomst, tkr"], "ålder": ["totalt 16+ år"]})
# Now we can get the data
>>> tbl.get_data()
>>> tbl
PxTable(url='https://api.scb.se/OV0104/v1/doris/sv/ssd/START/HE/HE0110/HE0110A/SamForvInk1',
query={'query': [{'code': 'ContentsCode', 'selection': {'filter': 'item', 'values': ['HE0110J8']}}, {'code': 'Alder', 'selection': {'filter': 'item', 'values': ['tot16+']}}], 'response': {'format': 'json-stat2'}},
metadata={'label': 'Sammanräknad förvärvsinkomst, medianinkomst för boende i Sverige hela året, tkr efter ålder, tabellinnehåll och år', 'note': None, 'source': 'SCB', 'updated': '2024-01-12T05:52:00Z'},
fetched=2024-06-16 10:30:34.085020,
dataset=[{'ålder': 'totalt 16+ år', 'tabellinnehåll': 'Medianinkomst, tkr', 'år': '1999', 'value': 159.4}, {'ålder': 'totalt 16+ år', 'tabellinnehåll': 'Medianinkomst, tkr', 'år': '2000', 'value': 165.3}, ...])
# Using the dataset we can then create a Pandas dataframe
>>> df = pd.DataFrame(tbl.dataset)
>>> print(df)
ålder tabellinnehåll år value
0 totalt 16+ år Medianinkomst, tkr 1999 159.4
1 totalt 16+ år Medianinkomst, tkr 2000 165.3
2 totalt 16+ år Medianinkomst, tkr 2001 172.4
3 totalt 16+ år Medianinkomst, tkr 2002 179.4
4 totalt 16+ år Medianinkomst, tkr 2003 185.1
5 totalt 16+ år Medianinkomst, tkr 2004 189.4
6 totalt 16+ år Medianinkomst, tkr 2005 192.9
7 totalt 16+ år Medianinkomst, tkr 2006 198.8
8 totalt 16+ år Medianinkomst, tkr 2007 206.2
9 totalt 16+ år Medianinkomst, tkr 2008 215.1
10 totalt 16+ år Medianinkomst, tkr 2009 218.7
11 totalt 16+ år Medianinkomst, tkr 2010 219.7
12 totalt 16+ år Medianinkomst, tkr 2011 225.0
13 totalt 16+ år Medianinkomst, tkr 2012 233.7
14 totalt 16+ år Medianinkomst, tkr 2013 240.5
15 totalt 16+ år Medianinkomst, tkr 2014 244.8
16 totalt 16+ år Medianinkomst, tkr 2015 253.7
17 totalt 16+ år Medianinkomst, tkr 2016 263.9
18 totalt 16+ år Medianinkomst, tkr 2017 272.0
19 totalt 16+ år Medianinkomst, tkr 2018 279.8
20 totalt 16+ år Medianinkomst, tkr 2019 286.8
21 totalt 16+ år Medianinkomst, tkr 2020 291.9
22 totalt 16+ år Medianinkomst, tkr 2021 301.5
23 totalt 16+ år Medianinkomst, tkr 2022 316.6
```
See [examples](examples/example.py) for more details on how to use pxwebpy.
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