CODEWITHSUNDEEP
pythonpandas
raspberry_door
raspberry_door

Reputation: 199

Apply SequenceMatcher to DataFrame

I'm new to pandas and Python in general, so I'm hoping someone can help me with this simple question. I have a large dataframe m with several million rows and seven columns, including an ITEM_NAME_x and ITEM_NAME_y. I want to compare ITEM_NAME_x and ITEM_NAME_y using SequenceMatcher.ratio(), and add a new column to the dataframe with the result.

I've tried to come at this several ways, but keep running into errors:

>>> m.apply(SequenceMatcher(None, str(m.ITEM_NAME_x), str(m.ITEM_NAME_y)).ratio(), axis=1)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Python33\lib\site-packages\pandas\core\frame.py", line 4416, in apply
return self._apply_standard(f, axis)
  File "C:\Python33\lib\site-packages\pandas\core\frame.py", line 4491, in _apply_standard
raise e
  File "C:\Python33\lib\site-packages\pandas\core\frame.py", line 4480, in _apply_standard
results[i] = func(v)
TypeError: ("'float' object is not callable", 'occurred at index 0')

Could someone help me fix this?

Upvotes: 1

Views: 4884

Answers (1)

alko
alko

Reputation: 48357

You have to apply a function, not a float which expression SequenceMatcher(None, str(m.ITEM_NAME_x), str(m.ITEM_NAME_y)).ratio() is.

Working demo (a draft):

import difflib
from functools import partial
import pandas as pd

def apply_sm(s, c1, c2): 
    return difflib.SequenceMatcher(None, s[c1], s[c2]).ratio()

df = pd.DataFrame({'A': {1: 'one'}, 'B': {1: 'two'}})
print df.apply(partial(apply_sm, c1='A', c2='B'), axis=1)

output:

1    0.333333
dtype: float64

Upvotes: 4

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