How to add leading zero formatting to string in Pandas?

Question

Objective: To format ['Birth Month'] with leading zeros

Currently, I have this code:

import pandas as pd
import numpy as np

df1=pd.DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])])
df1['Birth Year']= np.random.randint(1905,1995, len(df1))
df1['Birth Month']= str(np.random.randint(1,12, len(df1))).zfill(2)
df1

Which produces a list of values in ['Birth Month'] which is not what I need:

    A   B   Birth Year  Birth Month
0   1   4   1912        [4 5 9]
1   2   5   1989        [4 5 9]
2   3   6   1921        [4 5 9]

Instead, I am looking for values and formatting like the following in ['Birth Month']:

    A   B   Birth Year  Birth Month
0   1   4   1912        04
1   2   5   1989        12
2   3   6   1921        09

EdChum · Accepted Answer · 2015-11-11 13:45:40Z

10

Cast the dtype of the series to str using astype and use vectorised str.zfill to pad with 0:

In [212]:
df1=pd.DataFrame.from_items([('A', [1, 2, 3]), ('B', [4, 5, 6])])
df1['Birth Year']= np.random.randint(1905,1995, len(df1))
df1['Birth Month']= pd.Series(np.random.randint(1,12, len(df1))).astype(str).str.zfill(2)
df1

Out[212]:
   A  B  Birth Year Birth Month
0  1  4        1940          09
1  2  5        1945          04
2  3  6        1962          03

All you did was assign a scalar value (which is why every row is the same) and convert the element to a str of a list:

In [217]:
df1['Birth Month'].iloc[0]

Out[217]:
'[3 6 9]'

You can see the result of the assignment here broken down:

In [213]:
(np.random.randint(1,12, len(df1)))

Out[213]:
array([5, 7, 4])

In [214]:
str(np.random.randint(1,12, len(df1))).zfill(2)

Out[214]:
'[2 9 5]'

edited Nov 11, 2015 at 13:45

answered Nov 11, 2015 at 13:40

EdChum

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3 Comments

Student Over a year ago

EdChum - using your code I ran into an AttributeError: 'StringMethods' object has no attribute 'zfill'. I am using Python 2.7.10.

EdChum Over a year ago

What version of pandas are you using?

Student Over a year ago

EdChum - I updated pandas to the current version and your solution worked perfectly. Thank you.

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