Adding White Spaces after strings in pandas dataframe: TypeError: string indices must be integers

Question

I am trying to create a new column based on the length of a string and adding whites spaces to end of the string.

data={ 'Fruit':['Apple','Mango','Watermelon'],
'Color':['Red','Yellow','Green']
}
df = pd.DataFrame(data)
df['length']=df['Fruit'].str.len()
df['Fruit_color']=df.apply(lambda row: row['Fruit']+ (' '* row[length])+row['color'])

i get the error “TypeError: string indices must be integers”?

When i change the code only to this

df['white_space']=df.apply(lambda row:  (' '* row[length])) 
i get KeyError: ('length', 'occurred at index Fruit')

How do i avoid these errors to get the desired result

Regards, Ren.

whats your desired output?

Umar.H
– Umar.H

2019-07-31 19:57:15 +00:00
Commented Jul 31, 2019 at 19:57 — Umar.H
– Umar.H, Commented Jul 31, 2019 at 19:57
apply(lambda row: ..., axis=1).

Quang Hoang
– Quang Hoang

2019-07-31 19:57:51 +00:00
Commented Jul 31, 2019 at 19:57 — Quang Hoang
– Quang Hoang, Commented Jul 31, 2019 at 19:57
typo in length? df['lenght'] = ...

Alexander
– Alexander

2019-07-31 20:00:37 +00:00
Commented Jul 31, 2019 at 20:00 — Alexander
– Alexander, Commented Jul 31, 2019 at 20:00

BENY · Accepted Answer · 2019-07-31 20:05:25Z

2

We do not need to use apply

df['Fruit']+ df['lenght'].map(lambda x : ' '*x)+df['Color']
Out[689]: 
0                Apple     Red
1             Mango     Yellow
2    Watermelon          Green
dtype: object

Fix your code : 1 type , 2 adding ''

df.apply(lambda row: row['Fruit']+ (' '* row['lenght'])+row['Color'],axis=1)

answered Jul 31, 2019 at 20:05

BENY

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Comments

Juan C · Accepted Answer · 2019-07-31 20:06:55Z

1

If you really want to use apply:

df['Fruit_color'] = df.apply(lambda x: x['Fruit'] + ' '*x['length'] + x['Color'], axis=1)
                                                            ^^                       ^^

Be careful of quoting column names, else Python will think you're calling a variable. Also be careful of spelling your variable names right, you used both length and lenght

answered Jul 31, 2019 at 20:06

Juan C

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Comments

piRSquared · Accepted Answer · 2019-07-31 20:32:42Z

1

Comprehension

zip(*map(df.get, df)) is another way to do df.itertuples(index=False)

[f'{f}{" " * l}{c}' for f, c, l in zip(*map(df.get, df))]

['Apple     Red', 'Mango     Yellow', 'Watermelon          Green']

As a new column

df.assign(New=[f'{f}{" " * l}{c}' for f, c, l in zip(*map(df.get, df))])

        Fruit   Color  length                        New
0       Apple     Red       5              Apple     Red
1       Mango  Yellow       5           Mango     Yellow
2  Watermelon   Green      10  Watermelon          Green

Without the need for an intermediate step of assigning length

df.assign(New=[f'{f}{" " * len(f)}{c}' for f, c in zip(df.Fruit, df.Color)])

        Fruit   Color                        New
0       Apple     Red              Apple     Red
1       Mango  Yellow           Mango     Yellow
2  Watermelon   Green  Watermelon          Green

edited Jul 31, 2019 at 20:32

answered Jul 31, 2019 at 20:12

piRSquared

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2 Comments

Juan C Over a year ago

Could you care to explain this part please:*map(df.get, df)) ? I almost understand it, but I'm not quite sure what it is doing

piRSquared Over a year ago

I added a blurb about it

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