Sorry for the basic question.
In the Python text cleaning process, change the contents one by one as shown below
df['sentence'] = df["sentence"].str.replace ("ballpoint pen", "pen")
df['sentence'] = df["sentence"].str.replace ("sign pen", "pen")
df['sentence'] = df["sentence"].str.replace ("Magic", "Pen")
I'd like to load the file and do it like processing the disused words as below.
stopwords = []
f = open('/content/khaiii/rsc/src/incompatible.txt')
lines = f.readlines()
for line in lines:
line = line.strip()
stopwords.append(line)
f.close()
df['sentence'] = df['sentence'].apply(lambda x : [item for item in x if item not in stopwords])
Is there a way?
python replace
Replacement list = []
# Read the file, and create a replacement list.
with open (word list file pass, "r") as f:
for line in f:
Before, after, = line.split('\t')
Replacement list.append(before changing, after changing)
# Call up a pair of words in the list, and perform a replacement.
For before and after molding In Replacement List:
df["Content"] = df["Content"].str.replace (before molding, after molding)
This is how you do it. When reading a file, check the encoding of the file carefully. If there's a useless line change at the end of the file, you'll have to take care of it.
I don't know if you understand me well because I'm short-sighted.
I think I can do it like this, so I'm leaving it
with open('/content/khaiiii/rsc/src/disambiguation)txt', 'r') as f:
lines = f.readlines()
stopwords = [line.strip() for line in lines]
for fd in df['sentence']:
if fd in stopwords:
break
for in ['ball pen', 'sign pen', 'magic']:
fd = fd.replace (r, 'pen')
Or
fd = str(df['sentence'])
if fd not in stopword:
for in ['ball pen', 'sign pen', 'magic']:
fd = fd.replace(r, 'pen')
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