Pandas – converting yes : no to True : False failing

My best efforts to convert a column with ‘yes’ ‘no’ values to True, False or 1 , 0 are failing. The column is ‘subscribed’.

df.subscribed.unique() returns
array(['no', 'yes'], dtype=object)

Tried the following. None of them worked:

df.subscribed = df.subscribed.astype(int)
df.subscribed.map(dict(yes=1, no=0))
df.replace({'subscribed': {'yes': 1, 'no': 0}})
d = {'yes': True, 'no': False}
df['subscribed'].map(d)

Answer

As EdChum points out you need to assign back to the df.

df = pd.DataFrame({'subscribed':np.random.choice(['yes','no'], 10)})
print(df)

Input:

  subscribed
0        yes
1        yes
2        yes
3         no
4         no
5        yes
6         no
7         no
8         no
9        yes

df =df.replace({'subscribed': {'yes': True, 'no': False}})
print(df)

Output:

   subscribed
0        True
1        True
2        True
3       False
4       False
5        True
6       False
7       False
8       False
9        True