CODEWITHSUNDEEP
pythonstringpandasdataframe
gabboshow
gabboshow

Reputation: 5559

make upper case and replace space in column dataframe

for a specific column of a pandas dataframe I would like to make the elements all uppercase and replace the spaces

import pandas as pd

df = pd.DataFrame(data=[['AA 123',00],[99,10],['bb 12',10]],columns=['A','B'],index=[0,1,2])

# find elements 'A' that are string
temp1 = [isinstance(s, str) for s in df['A'].values]

# Make upper case and replace any space
temp2 = df['A'][temp1].str.upper()
temp2 = temp2.str.replace(r'\s', '')

# replace in dataframe
df['A'].loc[temp2.index] = temp2.values

I get

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:194: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  self._setitem_with_indexer(indexer, value)

Any suggestion to avoid this warning or any better way to do what I am trying to do?

Upvotes: 0

Views: 3084

Answers (3)

user3483203
user3483203

Reputation: 51165

str.upper with replace 

df['A'] = df.A.str.upper().replace('\s+', '', regex=True).fillna(df['A'])

       A   B
0  AA123   0
1     99  10
2   BB12  10

Upvotes: 2

asongtoruin
asongtoruin

Reputation: 10359

You can simplify this a lot by using numpy.where to select the rows you want to modify:

import pandas as pd
import numpy as np

    df = pd.DataFrame(data=[['AA 123',00],[99,10],['bb 12',10]],columns=['A','B'],index=[0,1,2])


    df['A'] = np.where(df['A'].apply(lambda x: isinstance(x, str)),
                       df['A'].str.upper().str.replace(r'\s', ''),
                       df['A'])

Upvotes: 1

ignoring_gravity
ignoring_gravity

Reputation: 10476

You could replace your last line with

df.loc[temp2.index, 'A'] = temp2.values

Upvotes: 0

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