You cannot select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Mike Gerber 8d6b97f6b3 🐛 Fix typo in XlsxWriter dependency 3 months ago
.circleci ✔ Test on Python 3.12 4 months ago
.vscode ⚙️ Add VSCode settings 3 years ago
src/mods4pandas Remove direct CSV/Excel support 4 months ago
.editorconfig ⚙️ Add .editorconfig 3 years ago
.gitignore 🧹 .gitignore pyenv's .python-version 12 months ago
LICENSE 📝 modstool: Add LICENSE 5 years ago
README-DEV.md 🐛 Fix tests 4 months ago
README.md Remove direct CSV/Excel support 4 months ago
pyproject.toml ⚙ Migrate to pyproject.toml 4 months ago
requirements-test.txt ✔ Enable/document profiling 11 months ago
requirements.txt 🐛 Fix typo in XlsxWriter dependency 3 months ago

README.md

Extract the MODS/ALTO metadata of a bunch of METS/ALTO files into pandas DataFrames.

Build Status

mods4pandas converts the MODS metadata from METS files into a pandas DataFrame.

Column names are derived from the corresponding MODS elements. Some domain knowledge is used to convert elements to a useful column, e.g. produce sets instead of ordered lists for topics, etc. Parts of the tool are specific to our environment/needs at the State Library Berlin and may need to be changed for your library.

Per-page information (e.g. structure information from the METS structMap) can be converted as well (--output-page-info).

alto4pandas converts the metadata from ALTO files into a pandas DataFrame.

Column names are derived from the corresponding ALTO elements. Some columns contain descriptive statistics (e.g. counts or mean) of the corresponding ALTO elements or attributes.

Usage

mods4pandas /path/to/a/directory/containing/mets_files
alto4pandas /path/to/a/directory/full/of/alto_files

Conversion to other formats

CSV:

python -c 'import pandas as pd; pd.read_parquet("mods_info_df.parquet").to_csv("mods_info_df.csv")'

Excel (requires XlsxWriter):

python -c 'import pandas as pd; pd.read_parquet("mods_info_df.parquet").to_excel("mods_info_df.xlsx"
, engine="xlsxwriter")'

Example

In this example we convert the MODS metadata contained in the METS files in /srv/data/digisam_mets-sample-300 to a pandas DataFrame under mods_info_df.parquet. This file can then be read by your data scientist using pd.read_parquet().

% mods4pandas /srv/data/digisam_mets-sample-300
INFO:root:Scanning directory /srv/data/digisam_mets-sample-300
301it [00:00, 19579.19it/s]
INFO:root:Processing METS files
100%|████████████████████████████████████████| 301/301 [00:01<00:00, 162.59it/s]
INFO:root:Writing DataFrame to mods_info_df.parquet

In the next example we convert the metadata from the ALTO files in the test data directory:

% alto4pandas qurator/mods4pandas/tests/data/alto
Scanning directory qurator/mods4pandas/tests/data/alto
Scanning directory qurator/mods4pandas/tests/data/alto/PPN636777308
Scanning directory qurator/mods4pandas/tests/data/alto/734008031
Scanning directory qurator/mods4pandas/tests/data/alto/PPN895016346
Scanning directory qurator/mods4pandas/tests/data/alto/PPN640992293
Scanning directory qurator/mods4pandas/tests/data/alto/alto-ner
Scanning directory qurator/mods4pandas/tests/data/alto/PPN767883624
Scanning directory qurator/mods4pandas/tests/data/alto/PPN715049151
Scanning directory qurator/mods4pandas/tests/data/alto/749782137
Scanning directory qurator/mods4pandas/tests/data/alto/weird-ns
INFO:alto4pandas:Processing ALTO files
INFO:alto4pandas:Writing DataFrame to alto_info_df.parquet