The pandas method is to use the vectorised str.normalize
combined with str.decode
and str.encode
:
In [60]:
df['Country'].str.normalize('NFKD').str.encode('ascii', errors='ignore').str.decode('utf-8')
Out[60]:
0 Aland Islands
1 Aland Islands
2 Albania
3 Albania
4 Albania
Name: Country, dtype: object
So to do this for all str
dtypes:
In [64]:
cols = df.select_dtypes(include=[np.object]).columns
df[cols] = df[cols].apply(lambda x: x.str.normalize('NFKD').str.encode('ascii', errors='ignore').str.decode('utf-8'))
df
Out[64]:
Table Code Country Year City Value
0 240 Aland Islands 2014.0 MARIEHAMN 11437.0 1
1 240 Aland Islands 2010.0 MARIEHAMN 5829.5 1
2 240 Albania 2011.0 Durres 113249.0
3 240 Albania 2011.0 TIRANA 418495.0
4 240 Albania 2011.0 Durres 56511.0
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