Replace A Character In A Python Dataframe Column

The simple dataframe replace shown below is not working. The NewPhone column contains the same value as the original column. import pandas as pd SF = pd.read_csv(r'xxx.csv') SF['Ne

Solution 1:

replace looks for exact matches (by default unless you pass regex=True but you will need to escape the parentheses - see @piRSquared's answer), you want str.replace:

SF['NewPhone'] = SF['Phone'].str.replace("(",'xxx')

which will replace all occurrences of the passed in string with the new string

Example:

In[20]:
df = pd.DataFrame({'phone':['(999)-63266654']})
df

Out[20]: 
            phone
0  (999)-63266654

In[21]:    
df['phone'].str.replace("(",'xxx')

Out[21]: 
0    xxx999)-63266654
Name: phone, dtype: object

If we try replace then no match occurs:

In[22]:
df['phone'].replace("(",'xxx')

Out[22]: 
0    (999)-63266654Name: phone, dtype: object

See @piRSquared's answer for how to get replace to work as expected (I don't want to cannibalise his answer)

Solution 2:

The Series.replace method takes a regex argument that is False by default. Set it to True. Also, if the string to be replaced is interpreted as a regex pattern, we'll need to escape the opening parenthesis.

df.phone.replace("\(", 'xxx', regex=True)

0    xxx999)-63266654
Name: phone, dtype: object

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Setup from @EdChum

df = pd.DataFrame({'phone':['(999)-63266654']})