mad-ssb

Turn municipal-level tables exported from Statistics Norway (Statistikkbanken / SSB) into tidy pandas.DataFrames that are ready for data analysis.

SSB Excel exports are formatted for humans rather than for computation: they start with a banner of title/metadata rows, end with footnotes, lay out data horizontally (one column per year) and encode missing values as the strings '.' and '..'. mad-ssb returns a single long-format table, adds a municipal ID number column, as well as does other basic clean up tasks to get to a decent starting point for creating SSB datasets for analysis.

Installation

pip install mad-ssb

or with uv:

uv add mad-ssb

Requires Python 3.11+ and pandas 3.0+.

Quick start

>>> from mad_ssb import read_ssb
>>> df = read_ssb("municipal_table.xlsx")
>>> df.head()
    MID  year  outcome
0  0301  2010      123
1  0301  2011      456
2  0302  2010       78

• Data columns (years) are stacked into a single year/outcome pair.
• The municipal ID is extracted into its own MID column.
• Optional: rename the index (metadata) columns with non_year_col_names, e.g. read_ssb(path, non_year_col_names=["region"]). Use dtype="float" when the table contains decimals or NA that integers cannot hold.

How it works

mad-ssb is a small pipeline of composable helpers (all exposed as public API):

License

MIT