How To Get The Integer Portion Of A Float Column In Pandas

Suppose I have a dataframe df as shown below qty 0 1.300 1 1.909 Now I want to extract only the integer portion of the qty column and the df should look like qty 0 1

Solution 1:

Convert values to integers by Series.astype:

df['qty'] = df['qty'].astype(int)
print (df)
   qty
0    1
1    1

If not working above is possible use numpy.modf for extract values before .:

a, b = np.modf(df['qty'])
df['qty'] = b.astype(int)
print (df)
   qty
0    1
1    1

Or by split before ., but it should be slow if large DataFrame:

df['qty'] = b.astype(str).str.strip('.').str[0].astype(int)

Or use numpy.floor:

df['qty'] = np.floor(df['qty']).astype(int)

Solution 2:

You can use the method floordiv:

df['col'].floordiv(1).astype(int)

For example:

        col
0  9.748333
1  6.612708
2  2.888753
3  8.913470
4  2.354213

Output:

0916223842Name:col,dtype:int64