I was wondering how I can map a dictionary key with multiple dictionary items. I have tried the below however the output is not the expected one.
d = {'col1': ['type 2','type 3', 'type 4', 'type 5', 'type 6', 'type 6']}
df = pd.DataFrame(data=d)
dict = {
'a' :['type 2', 'type 3'],
'b' : ['type 4', 'type 5'],
'c': ['types 6', 'types 7']
}
for k, v in df.items():
df['col1'].map({k: v})
print(df)
expected output:
You may have to convert your dict such that the keys are values and vice versa.
dd = {
'a' :['type 2', 'type 3'],
'b' : ['type 4', 'type 5'],
'c': ['type 6', 'type 7']
}
ddd = {l:v for v,k in dd.items() for l in k}
print(ddd)
Out:
{'type 2': 'a',
'type 3': 'a',
'type 4': 'b',
'type 5': 'b',
'type 6': 'c',
'type 7': 'c'}
Now you can map it easily.
df.col1.map(ddd)
Out:
0 a
1 a
2 b
3 b
4 c
5 c
Name: col1, dtype: object
We can try explode
s = pd.Series(d).explode()
df['col1'] = df['col1'].map(dict(zip(s,s.index)))
Input
d= {
'a' :['type 2', 'type 3'],
'b' : ['type 4', 'type 5'],
'c': ['type 6', 'type 7']
}
Notice : do not named a variable same as original function from python or pandas
