CODEWITHSUNDEEP
pythonpandasdataframe
Python09
Python09

Reputation: 115

Adding trailing zeros to row values to make sure there are 10 digits

If i have a data frame where max digits in each row is 10 but some IDs are less than 10 because the trailing zeros have been cut off, how do I add trailing zeros in python to make sure there are 10 digits in each row.

ID
1234567689
123456768
12345676

ID
1234567689
1234567680
1234567600

Upvotes: 2

Views: 1329

Answers (4)

Prayson W. Daniel
Prayson W. Daniel

Reputation: 15568

I think f-formatting can do that

X = [1234567689, 12345, 123,]
print([f'{item:0<9}' for item in X])

This only works with Python 3.6+. The idea is to get the value and left pad 9 zeros. In Pandas you can do, the following to maintain your field as numeric

df['ID'] = df['ID'].apply(lambda x: f'{x:0<9'}).astype(int)

Upvotes: 1

NYC Coder
NYC Coder

Reputation: 7594

You can use ljust for this:

df = df['ID'].astype(str).str.ljust(10, '0')
print(df)

0    1234567689
1    1234567680
2    1234567600

Upvotes: 2

Shubham Sharma
Shubham Sharma

Reputation: 71689

Another way is to use, Series.str.ljust:

df['ID'] = df['ID'].str.ljust(width=10, fillchar='0')

Result:

           ID
0  1234567689
1  1234567680
2  1234567600

Upvotes: 1

Celius Stingher
Celius Stingher

Reputation: 18367

You can use str.pad() which I believe works perfect for this scenario:

df['ID'] = df['ID'].str.pad(width=10,side='right',fillchar='0')

In case the dtype of the column is not string, then you can first convert it:

df['ID'] = df['ID'].astype(str).str.pad(width=10,side='right',fillchar='0')

Output:

           ID
0  1234567689
1  1234567680
2  1234567600

Upvotes: 9

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