`pandas-linker` runs comparison windows over different sortings of a pandas DataFrame and links the rows via assigned UUIDs. This library does not actually do any duplicate detection. Instead it provides a harness to run your own comparison functions on your data.
This library is meant for datasets of a size where comparing every row with every other is undesirable. Instead you can decide on a sorting order of the DataFrame and only compare every row with every other inside a sliding window.
pip install pandas-linker
Let's say you have a DataFrame like this:
[ix] | name | country
0 | Pete | Spain
1 | Mary | USA
2 | Bart | US
3 | Mary | US
and you want to detect similar rows and mark them as such. Here's how to do that:
from pandas_linker import get_linker
def compare_rows(a, b):
''' Example function that decides if two rows represent same entity.'''
return a['name'] in b['name'] or b['name'] in a['name']
# df is a pandas.DataFrame with a unique index
with get_linker(df, field='uid') as linker:
print('Comparing in 10 row window sorted by name')
linker(sort_cols=['name'], window_size=10, cmp=compare_rows)
print('Comparing in 15 row window sorted by country')
linker(sort_cols=['country'], window_size=15, cmp=compare_rows)
After running the linker the process is complete
[ix] | name | country | uid
0 | Pete | Spain | 7509781940fc471cad5dc32944652d70
1 | Mary | USA | 8f8dccd91568472daf740e9160349d6c
2 | Bart | US | 12b55fbe80f64d378193acd727b0e051
3 | Mary | US | 8f8dccd91568472daf740e9160349d6c
Note that both "Mary" rows in the DataFrame have been identified as representing
the same entity and were assigned the same UUID.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.