I have a problem making capital letters inside a column. How do you write upper case str instead of lower case? and not do it manually.
import pandas as pd
cc =[1, 2, 3, 4]
aaa = ['ala', 'babcia', 'koty', 'foki']
df = pd.DataFrame({'ID': cc, 'AAA': aaa })
The target look of my data frame:
You can use the .upper() function in pandas along with list comprehension:
aaa = ['ala', 'babcia', 'koty', 'foki']
aaa = [x.upper() for x in aaa]
you can use pandas str upper method for this :
df['AAA'] = df['AAA'].str.upper()
df
ID AAA
0 1 ALA
1 2 BABCIA
2 3 KOTY
3 4 FOKI
Thought I'd do a performance test on the answers and some other solutions, so I created this dataframe:
df = pd.DataFrame(np.arange(1000000).reshape(1000000,1)).applymap(lambda x: np.random.choice(list('abcdefghijklm')))
In terms of performance, Nathan's and Nandan's were similar and the best solution if you don't define a function, because they had similar execution time:
221 ms ± 5.92 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
Sammy's was slower by 20% or so, but easiest to remember:
df['AAA'] = df['AAA'].str.upper()
281 ms ± 14.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
If you wanted a 15% performance increase from the top 2 answers, you could further use one of the answers in a function... I created a million row dataframe with one lowercase letter.
def upper(df, col):
[x.upper() for x in df[col]]
return
%timeit upper(df, 'AAA')
177 ms ± 3.24 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)