Pandas variable creation using multiple If-else

Question

Need help with Pandas multiple IF-ELSE statements. I have a test dataset (titanic) as follows:

ID  Survived    Pclass  Name    Sex Age
1   0   3   Braund  male          


        

Answer 1

Instead of looping through the rows using df.iterrows (which is relatively slow), you can assign the desired values to the Prediction column in one assignment:

In [27]: df['Prediction'] = ((df['Sex']=='female') | ((df['Pclass']==1) & (df['Age']<18))).astype('int')

In [29]: df['Prediction']
Out[29]: 
0    0
1    1
2    1
3    1
4    0
5    0
6    0
7    0
Name: Prediction, dtype: int32

---

For your first approach, remember that df['Prediction'] represents an entire column of df, so df['Prediction']=1 assigns the value 1 to each row in that column. Since df['Prediction']=0 was the last assignment, the entire column ended up being filled with zeros.

For your second approach, note that you need to use & not and to perform an elementwise logical-and operation on two NumPy arrays or Pandas NDFrames. Thus, you could use

In [32]: np.where(df['Sex']=='female', 1, np.where((df['Pclass']==1)&(df['Age']<18), 1, 0))
Out[32]: array([0, 1, 1, 1, 0, 0, 0, 0])

though I think it is much simpler to just use | for logical-or and & for logical-and:

In [34]: ((df['Sex']=='female') | ((df['Pclass']==1) & (df['Age']<18)))
Out[34]: 
0    False
1     True
2     True
3     True
4    False
5    False
6    False
7    False
dtype: bool