Pandas get decimal fractional number part from float in a dataframe

Question

How to extract the decimal number part from a float (float64) in a dataframe? (a very common scenario but I can 't find a solution in StackOverFlow)

Note: be careful with the 196.09, I need 09, not 9.

Sample DataFrame:

    dollars Count
0   56.46   2
1   196.09  3
2   78.12   2

Expected result is the 2 decimal digits:

    decimal
0   46
1   09
2   12

Answer 1

Alternative 1

An alternative would be to convert dollars to string, then use a regex to extract everything after the .:

df['decimal'] = df.dollars.astype(str).str.extract('\.(.*)').astype(int)

>>> df
   dollars  Count  decimal
0    56.46      2       46
1   196.69      3       69
2    78.12      2       12

Alternative 2

Or, you could subtract dollars from the int part of dollars, and multiply by 100:

df['decimal'] = (df.dollars.sub(df.dollars.astype(int))).mul(100).astype(int)

>>> df
   dollars  Count  decimal
0    56.46      2       46
1   196.69      3       68
2    78.12      2       12

---

Edit: based on the edit to OP's question, it seems that the decimal parts need to be displayed to 2 decimal points (e.g. it would need to be 09 instead of 9). In this case, It has to be displayed as a string, and not an int. The first method I outlined above would still work if you omit astype(int):

df['decimal'] = df.dollars.astype(str).str.extract('\.(.*)')

>>> df
   dollars  Count decimal
0    56.46      2      46
1   196.09      3      09
2    78.12      2      12

Or, this could be done after the fact using zfill, if we already have the decimal part as an int:

df['decimal'] = df['decimal'].astype(str).str.zfill(2)