Python replace string in Pandas column dataframe replace vs lambda

Question

Why these two are not the same:

df['REFERENCE'] =df['REFERENCE'].astype(str).str.strip().apply(lambda x:x.replace('(','')).apply(lambda x:x.replace(')',''))

df['REFERENCE'] =df['REFERENCE'].astype(str).str.strip().replace('(','')).replace(')',''))

The second one does not give error, but does not substitute '(' by ''.

Cameron Riddell · Accepted Answer · 2020-09-17 22:52:25Z

2

Try:

df['REFERENCE'].astype(str).str.strip().str.replace('(','')).str.replace(')',''))

a Pandas Series (column) has both a Series.replace method and a Series.str.replace replace method. The string accessor .str is necessary to use the string based methods which is what you're expecting.

*Series.replace("foo", "bar") looks in each cell of the Series, and if the value is equal to "foo" it is replaced with "bar". So for this method to work, a value in the Series must be exactly equal to "foo", nothing more, nothing less.

*Series.str.replace("foo", "bar") looks in each cell of the Series, and checks replaces ANY PART of the value that is "foo" with "bar". So in this case, the values inside the Series can be strings that simply contain the string "foo" and it will replace the portion of that string with "bar"

answered Sep 17, 2020 at 22:52

Cameron Riddell

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1 Comment

JFerro Over a year ago

Sooooo good !!!! thanks. Real KEY ISSUE --> accesing the string of the cells!!!

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