String Modification On Pandas DataFrame Subset

Question

I'm having a hard time updating a string value in a subset of Pandas data frame

In the field action, I am able to modify the action column using regular expressions with:

df['action'] = df.action.str.replace('([^a-z0-9\._]{2,})','')

However, if the string contains a specific word, I don't want to modify it, so I tried to only update a subset like this:

df[df['action'].str.contains('TIME')==False]['action'] = df[df['action'].str.contains('TIME')==False].action.str.replace('([^a-z0-9\._]{2,})','')

and also using .loc like:

df.loc('action',df.action.str.contains('TIME')==False) = df.loc('action',df.action.str.contains('TIME')==False).action.str.replace('([^a-z0-9\._]{2,})','')

but in both cases, nothing gets updated. Is there a better way to achieve this?

Could you provide a sample dataframe, sample input and desired output? — MachineLearner
– MachineLearner, Commented Apr 15, 2020 at 17:47

Ben.T · Accepted Answer · 2020-04-15 17:48:57Z

1

you can do it with loc but you did it the way around with column first while it should be index first, and using [] and not ()

mask_time = ~df['action'].str.contains('TIME') # same as df.action.str.contains('TIME')==False
df.loc[mask_time,'action'] = df.loc[mask_time,'action'].str.replace('([^a-z0-9\._]{2,})','')

example:

#dummy df
df = pd.DataFrame({'action': ['TIME 1', 'ABC 2']})
print (df)
   action
0  TIME 1
1   ABC 2

see the result after using above method:

   action
0  TIME 1
1       2

answered Apr 15, 2020 at 17:48

Ben.T

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1 Comment

Sam CD Over a year ago

That worked, also helped me understand a little better how .loc works. Thanks!

Rola · Accepted Answer · 2020-04-15 18:10:13Z

1

Try this it should work, I found it here

df.loc[df.action.str.contains('TIME')==False,'action'] = df.action.str.replace('([^a-z0-9\._]{2,})','')

answered Apr 15, 2020 at 18:10

Rola

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