Make change in dataframe inplace

Question

I apologize for asking such a basic question, but I’ve been stuck at this point for almost a week.

I have the dataframe below, there are anomalies in the name column, but I have been able to fix a part of it using the code below

names = ['a', 'an', 'my', 'by', 'mad', 'very', 'just', 'quite', 'one', 'actually', 'life', 'light', 'officially','his', 'old', 'this', 'all','the']

archive[archive['name'].isin(names) & archive['text'].str.contains('named')]['text'].str.split('named').str[1].str.split('.').str[0]

I get the output below:

1853             Wylie
1955               Kip
2034     Jacob (Yacōb)
2066             Rufus
2116             Spork
2125          Cherokee
2128             Hemry
2146           Alphred
2161           Alfredo
2191             Leroi
2204             Berta
2218              Chuk
2235           Alfonso
2249            Cheryl
2255           Jessiga
2264             Klint
2273              Kohl
2304              Pepe
2311         Octaviath
2314              Johm
Name: text, dtype: object

But I was to apply the changes that I have made to be applied but I’m not sure how to go about it. Any help please?

Asked By: Amazing-Grace Umoren

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Answer 1

IIUC, you can conditionally assign the split text column the name column with .loc

m = archive['name'].isin(names) & archive['text'].str.contains('named')
archive.loc[m, 'name'] = archive['text'].str.split('named').str[1].str.split('.').str[0]

Answered By: Ynjxsjmh

Make change in dataframe inplace

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