I am very new to python and trying to get value from dictionary where keys are defined in a dataframe column (pandas). I searched quite a bit and the closest thing is a question in the link below, but it doesnt come with an answer.

So, here I am trying to find answer for the same type of question.

Select from dictionary using pandas series

I have a dictionary

type_dict = {3: 'foo', 4:'bar',5:'foobar', 6:'foobarbar'}

and a data frame with the following column:

>>> df.type
0     3
1     4
2     5
3     6
4     3
5     4
6     5
7     6
8     3

I want to create a new column containing the corresponding type_dict value, but the following was the only thing I could come up and was not working:

type_dict[df.type]

TypeError: 'Series' objects are mutable, thus they cannot be hashed

type_dict[df.type.values]

TypeError: unhashable type: 'numpy.ndarray'

Updated question:

for pandas DataFrame, say 'df', how can i plot speed over meters with type as the key of marker dictionary.

mkr_dict = {'gps': 'x', 'phone': '+', 'car': 'o'}x = {'speed': [10, 15, 20, 18, 19], 'meters' : [122, 150, 190, 230, 300], 'type': ['phone', 'phone', 'gps', 'gps', 'car']}df = pd.DataFrame(x)meters  speed   type
0     122     10  phone
1     150     15  phone
2     190     20    gps
3     230     18    gps
4     300     19    carplt.scatter(df.meters, df.Speed, marker = df.type.map(mkr_dict)) 

the scatter plot doesn't work for me...

Pass the dict as an arg to map:

In [79]:df['type'].map(type_dict)
Out[79]:
0          foo
1          bar
2       foobar
3    foobarbar
4          foo
5          bar
6       foobar
7    foobarbar
8          foo
Name: type, dtype: object

This will lookup the key value in the dict and return the associated value from the dict.