Why doesn't str.replace replace ALL values in selected pandas dataframe column?-CodePudding

I'm working on a huge file that has names in columns that contain extraneous values (like the "|" key) that I want to remove, but for some reason my str.replace function only seems to apply to some rows in the column.

My column in the dataframe summary looks something like this:

Labels
test|test 1
test 2
test 3
test|test 4
test|test 5
test 6

As you can see, some columns are already how i want them to be, only containing the name "test #", but some have "test|" in front, which I want removed.

My function to remove them is like this:

correction = summary["Labels"].str.replace('test\|', '')

It seems to work for most of the values, but when I check for pipes ("|") in the dataframe (once i merged correction with summary), it says it finds 9330 of them:

found = summary[summary['Labels'].str.contains('|',regex=False)]
print(len(found))
print(found['Labels'].value_counts())

Results
9330
test|test-667     59
test|test-765     40
test|test-1810    39
test|test-685     36
test|test-1077    33
                  ..

Does anyone know why this is, and how i can fix it?

CodePudding user response：

Try str.extract:

df['Labels'] = df['Labels'].str.extract(r'\|(.*)', expand=False) \
                           .combine_first(df['Labels'])
print(df)

# Output
   Labels
0  test 1
1  test 2
2  test 3
3  test 4
4  test 5
5  test 6

CodePudding user response：

You were on the right track. Replace raw string as follows

summary['Labels'] = summary['Labels'].str.replace(r'test\|','', regex=True)



Labels
0  test 1
1  test 2
2  test 4