dataframe adding column/filling data by mapping conditions

Question

the aim is to construct a dataframe with a dictionary with some modifications:

df = pd.DataFrame({'1-7':[0,0,1],'1-2':[1,0,1],'2-3':[1,0,0],'2-2':[0,1,0],'1-1':[1,0,0],'1-3':[0,1,1],'1-5':[0,1,0]},index=dici.keys())
df

Data:

I got a dictionary like this:

dici={'a':['1-1','1-2','2-3'],'b':['2-2','1-5','1-3'],'c':['1-7','1-2','1-3']}
dici

the union of the list dici.values() will be used as the column name, and the list dici.keys() will be used as the index name.

the data explanation in df: for example, if the value '1-1' exits /equals to the name of the column, the value will be 1, else, the value will be 0.

Answer 1

You can convert your dict into a Series object, and then join them by any random string and use .str.get_dummies:

df = pd.Series(dici).str.join('x').str.get_dummies('x')

Output:

>>> df
   1-1  1-2  1-3  1-5  1-7  2-2  2-3
a    1    1    0    0    0    0    1
b    0    0    1    1    0    1    0
c    0    1    1    0    1    0    0