pandas 编辑两个熊猫列之间的距离
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Edit distance between two pandas columns
提问by Orest Xherija
I have a pandas DataFrame consisting of two columns of strings. I would like to create a third column containing the Edit Distance of the two columns.
我有一个由两列字符串组成的 Pandas DataFrame。我想创建第三列，其中包含两列的编辑距离。
from nltk.metrics import edit_distance
df['edit'] = edit_distance(df['column1'], df['column2'])
For some reason this seems to go to some sort of infinite loop in the sense that it remains unresponsive for quite some time and then I have to terminate it manually.
出于某种原因，这似乎进入了某种无限循环，因为它在很长一段时间内仍然没有响应，然后我必须手动终止它。
Any suggestions are welcome.
欢迎任何建议。
回答by alexis
The nltk's edit_distancefunction is for comparing pairs of strings. If you want to compute the edit distance between corresponding pairs of strings, applyit separately to each row's strings like this:
nltk 的edit_distance功能是比较字符串对。如果要计算相应的字符串对之间的编辑距离，apply可以像这样分别计算每一行的字符串：
results = df.apply(lambda x: edit_distance(x["column1"], x["column2"]), axis=1)
Or like this (probably a little more efficient), to avoid including the irrelevant columns of the dataframe:
或者像这样（可能更有效），以避免包含数据帧的不相关列：
results = df.loc[:, ["column1", "column2"]].apply(lambda x: edit_distance(*x), axis=1)
To add the results to your dataframe, you'd use it like this:
要将结果添加到您的数据框中，您可以像这样使用它：
df["distance"] = df.loc[:, ["column1","column2"]].apply(lambda x: edit_distance(*x), axis=1)
