How to use str.replace to replace multiple pairs at once?

user_12749240 0
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Currently I am using the following code to make replacements which is a little cumbersome:

df1['CompanyA'] = df1['CompanyA'].str.replace('.','')
df1['CompanyA'] = df1['CompanyA'].str.replace('-','')
df1['CompanyA'] = df1['CompanyA'].str.replace(',','')
df1['CompanyA'] = df1['CompanyA'].str.replace('ltd','limited')
df1['CompanyA'] = df1['CompanyA'].str.replace('&','and')
df1['Address1A'] = df1['Address1A'].str.replace('.','')
df1['Address1A'] = df1['Address1A'].str.replace('-','')
df1['Address1A'] = df1['Address1A'].str.replace('&','and')
df1['Address1A'].str.replace(r'\brd\b', 'road')
df1['Address2A'] = df1['Address2A'].str.replace('.','')
df1['Address2A'] = df1['Address2A'].str.replace('-','')
df1['Address2A'] = df1['Address2A'].str.replace('&','and')
df1['Address2A'].str.replace(r'\brd\b', 'road')

In order to make changing on the fly easier my ideal scenario would be something like:

df1['CompanyA'] = df1['CompanyA'].str.replace(('&','and'), ('.', ''), ('-','')....)
df1['Address1A'] = df1['Address1A'].str.replace(('&','and'), ('.', ''), ('-','')....)
df1['Address2A'] = df1['Address2A'].str.replace(('&','and'), ('.', ''), ('-','')....)

This is so I could just input/change what I wanted to replace for a particular column without having to adjust multiple lines of code.

Is this possible at all?

pandas python replace string
5 Answers

You can create a dictionary and pass it to the function replace() without needing to chain or name the function so many times.

replacers = {',':'','.':'','-':'','ltd':'limited'} #etc....
df1['CompanyA'] = df1['CompanyA'].replace(replacers)
user_118970070

you could chain the replacings:

df1['CompanyA'] = df1['CompanyA'].str.replace('.','').replace('-','').replace(',','').replace('ltd','limited').replace('&','and')
...
user_9251250

Replace function accepts values as dictionaries as well. You can do something like this:

df1.replace({'CompanyA' : { '&' : 'and', '.': '' , '-': ''}},regex=True)
user_126903440

You can use a dictionary to map the characters for each column:

to_replace = {'.': '',
              ',': '',
              'foo': 'bar'
             }

for k, v in to_replace.items():
    df1['CompanyA'] = df1['CompanyA'].str.replace(k, v)
user_128818440

most likely you use pd.Dataframe so i suggest to make universal remover

def remover(row, replaces):
    for k,v in replacers.items():
        if k in row:
            row = row.replace(k, v)
    return row      


replacers = {',' : "",
         '.':'',
         '-':'',
         'ltd':'limited'
        }

for column in df.columns:
    df[column] = df[column].apply(lambda row: remover(row, replacers))

or you can specify specific column names to modify

user_52522980
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