Convert Wort Python Pandas Datenrahmen in Zero One Data Frame

Question

Eingang

userID col1 col2 col3 col4 col5 col6 col7 col8 col9    
1 Java c c++ php python perl html hadoop nodejs   
2 nodejs c# c++ oops css html angular java php   
3 php python html java angular hadoop c nodejs c#   
4 python php css perl hadoop c nodejs c# html    
5 perl css python hadoop c nodejs c# java php   
6 Java python css  perl nodejs c# java php hadoop   
7 javascript java perl nodejs angular php mysql hadoop html    
8 angular mysql mongodb cs hadoop angular oops html perl    
9 nodejs hadoop mysql mongodb angular oops html python java 

Wunsch Ausgang

userID Java C C++ php python perl html hadoop nodejs oops mysql mongo 
1 1 1 1 1 1 1 1 1 1 0 0 0 
2 1 0 1 1 0 0 1 0 1 0 0 0 
3 1 1 0 1 1 1 1 1 1 0 0 0 
4 0 0 0 0 1 1 1 0 1 1 1 1 

Answer 1

Verwenden get_dummies + groupby von Spaltennamen und Aggregat max:

df = pd.get_dummies(df.set_index('userID'), prefix='', prefix_sep='') 
df = df.groupby(level=0, axis=1).max().reset_index() 
print (df) 
    userID Java angular c c# c++ cs css hadoop html java javascript \ 
0  1  1  0 1 0 1 0 0  1  1  0   0 
1  2  0  1 0 1 1 0 1  0  1  1   0 
2  3  0  1 1 1 0 0 0  1  1  1   0 
3  4  0  0 1 1 0 0 1  1  1  0   0 
4  5  0  0 1 1 0 0 1  1  0  1   0 
5  6  1  0 0 1 0 0 1  1  0  1   0 
6  7  0  1 0 0 0 0 0  1  1  1   1 
7  8  0  1 0 0 0 1 0  1  1  0   0 
8  9  0  1 0 0 0 0 0  1  1  1   0 

    mongodb mysql nodejs oops perl php python 
0  0  0  1  0  1 1  1 
1  0  0  1  1  0 1  0 
2  0  0  1  0  0 1  1 
3  0  0  1  0  1 1  1 
4  0  0  1  0  1 1  1 
5  0  0  1  0  1 1  1 
6  0  1  1  0  1 1  0 
7  1  1  0  1  1 0  0 
8  1  1  1  1  0 0  1