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Fix for comparison issue in columns_equal when ignore_case=True (Generated by Ana - AI SDE) #329

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Fix for comparison issue in columns_equal when ignore_case=True (Generated by Ana - AI SDE) #329

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7 changes: 5 additions & 2 deletions datacompy/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -749,6 +749,9 @@ def render(filename: str, *fields: Union[int, float, str]) -> str:
return file_open.read().format(*fields)


import pandas as pd
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These should be placed at the top of the file as it doesn't conform to our code quality guidelines.

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Hi @fdosani
Thanks for highlighting this. We will look into this as to why this happened.

BR,
Team Ana

import numpy as np

def columns_equal(
col_1: "pd.Series[Any]",
col_2: "pd.Series[Any]",
Expand Down Expand Up @@ -816,9 +819,9 @@ def columns_equal(
col_2 = col_2.str.strip()

if ignore_case:
if col_1.dtype.kind == "O":
if col_1.dtype == 'object' and col_1.apply(lambda x: isinstance(x, str)).all():
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This seems incorrect. The dtype would return an O not object AFAIK.

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Hi @fdosani

The comment is partially correct. dtype.kind returns 'O' for object types, while dtype itself returns 'object'. Both col_1.dtype.kind == "O" and col_1.dtype == 'object' are valid ways to check for object dtypes. The proposed change adds an extra check to ensure all elements are strings, which may be useful depending on the specific requirements of the comparison.

image

BR,
Team Ana

col_1 = col_1.str.upper()
if col_2.dtype.kind == "O":
if col_2.dtype == 'object' and col_2.apply(lambda x: isinstance(x, str)).all():
col_2 = col_2.str.upper()

if {col_1.dtype.kind, col_2.dtype.kind} == {"M", "O"}:
Expand Down
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