zfill() to prepending string with 0

Prepending string with '0'
Returns string with filled 0

If we have integer column then we have to first change the object to string dtype by using astype().

import pandas as pd 
my_dict={'NAME':['Ravi','Raju','Alex'],'ID':[1,2,3],
         'MATH':[30,40,50],'ENGLISH':[20,30,40]}
df = pd.DataFrame(data=my_dict)
df['MATH']=df['MATH'].astype(str) # to string dtype 
#print(df.MATH.str.zfill(3))
df['MATH']=df.MATH.str.zfill(3)
print(df)

Output

   NAME  ID MATH  ENGLISH
0  Ravi   1  030       20
1  Raju   2  040       30
2  Alex   3  050       40

Handling special chars , negative numbers and big numbers

Here we have negative number, single negative number, string and more than 3 char numbers. Check the output

my_dict={'NAME':['Ravi','Raju','Alex','King','Queen'],'ID':[1,2,3,4,5],
         'MATH':[-3,-40,5,'abc',6000],'ENGLISH':[20,30,40,50,10]}
df = pd.DataFrame(data=my_dict)
df['MATH']=df['MATH'].astype(str)
df['MATH']=df.MATH.str.zfill(3)
print(df)

Output

    NAME  ID  MATH  ENGLISH
0   Ravi   1   -03       20
1   Raju   2   -40       30
2   Alex   3   005       40
3   King   4   abc       50
4  Queen   5  6000       10

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str.zfill()

Handling special chars , negative numbers and big numbers

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