How to shift numeric Values or non-numeric from a Column in Pandas

Question

while reading through the Pandas shift method, i was just doing some test to see if a Column in Pandas dataFrame having mixed vales like number and names and i want to segregate that in order to get the number to be aligned to a separate new column while dropping /removing them From original column.

a) Below is mine DataFrame:

>>> df
        Name  OXA
0    SAN 109  Yes
1   KENI 122   No
2  REEMA 455  Yes

b) I tried with shift to move number to a new DataFrame(Nums):

>>> df['Nums'] = df['Name'].shift(-1)

>>> df
        Name  OXA       Nums
0    SAN 109  Yes   KENI 122
1   KENI 122   No  REEMA 455
2  REEMA 455  Yes        NaN

The above Creates the New column as Nums but not getting the desired result.

c) My Desired output will be :

        Name  OXA      Nums
0       SAN   Yes      109
1       KENI  No       122
2       REEMA Yes      455

OR and vice versa

        Name  OXA     NUMS
0       109  Yes      SAN
1       122  No       KENI
2       455  Yes      REEMA

I see your answer and maybe need [this](https://stackoverflow.com/a/48600345/2901002) — jezrael, Oct 26 '18 at 06:05

jezrael · Accepted Answer · 2018-10-22T06:58:43.237

I believe you need extract for extracting column by regex - [a-zA-Z]+ for match one or more characters, then \s* for zero or more whitespaces and \d+ for one or more digits:

df[['Name','Nums']]  = df['Name'].str.extract('([a-zA-Z]+)\s*(\d+)')
print (df)
    Name  OXA Nums
0    SAN  Yes  109
1   KENI   No  122
2  REEMA  Yes  455

df[['NUMS','Name']]  = df['Name'].str.extract('([a-zA-Z]+)\s*(\d+)')
print (df)
  Name  OXA   NUMS
0  109  Yes    SAN
1  122   No   KENI
2  455  Yes  REEMA

If there is always whitespace separator is possible use split:

df[['Name','Nums']]  = df['Name'].str.split(expand=True)
print (df)
    Name  OXA Nums
0    SAN  Yes  109
1   KENI   No  122
2  REEMA  Yes  455

How to shift numeric Values or non-numeric from a Column in Pandas

1 Answers1