I have data that contains 'None ...' string at random places. I am trying to replace a cell in the dataframe with empty character only when it begin with 'None ..'. Here is what I tried, but I get errors like 'KeyError'.
df = pd.DataFrame({'id': [1,2,3,4,5],
'sub': ['None ... ','None ... test','math None ...','probability','chemistry']})
df.loc[df['sub'].str.replace('None ...','',1), 'sub'] = '' # getting key error
output looking for: (I need to replace entire value in cell if 'None ...' is starting string. Notice, 3rd row shouldn't be replaced because 'None ...' is not starting character)
id sub
1
2
3 math None ...
4 probability
5 chemistry
You can use the below to identify the cells to replace and then assign them an empty value:
df.loc[df['sub'].str.startswith("None"), 'sub'] = ""
df.head()
id sub
0 1
1 2
2 3 math None ...
3 4 probability
4 5 chemistry
df['sub'] = df['sub'].str.replace('[\w\s]*?(None \.\.\.)[\s\w]*?','',1)
Out:
sub
id
1
2 test
3
4 probability
5 chemistry
Look at startswith
, then after we find the row need to be replaced we using replace
df['sub']=df['sub'].mask(df['sub'].str.startswith('None ... '),'')
df
Out[338]:
id sub
0 1
1 2
2 3 math None ...
3 4 probability
4 5 chemistry
You can simpy replace 'None ...' and by using a regular expression you can apply this replacement only for strings that start with None.
df['sub'] = df['sub'].str.replace(r'^None \.\.\.*','',1)
the output looks like this:
id sub
0 1
1 2 test
2 3 math None ...
3 4 probability
4 5 chemistry
First, you are using the sub strings as index, that is why you received key error.
Second you can do this by: df['sub']=df['sub'].apply(lambda x: '' if x.find('None')==0 else x)
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