Binarize integer in a pandas dataframe

Question

I have a pandas dataframe and want to add a new column. For all values in 'number' which are smaller than 15 I want to add 1, for all values which are greater, 0. I tried different methods, but I don't receive the desired result.Especially, because I have problems with the structure. Here is what I wanna do:

number   binary
12       1
89       0
12       1
56       0
62       0
2        1
657      0
5        1
73       0

Answer 1

In [6]: (df['number'] < 15).astype(int)
Out[6]:
0    1
1    0
2    1
3    0
4    0
5    1
6    0
7    1
8    0
Name: number, dtype: int32

In [7]: df['binary'] = (df['number'] < 15).astype(int)

In [8]: df
Out[8]:
   number  binary
0      12       1
1      89       0
2      12       1
3      56       0
4      62       0
5       2       1
6     657       0
7       5       1
8      73       0

Answer 2

You can convert it to boolean then multiply by 1.

import pandas as pd
df = pd.DataFrame({'number': [12, 89, 12, 56, 62, 2, 657, 5, 73]})
df['binary'] = (df.number < 15)*1