我想在 Python 中将分类变量转换为数值

Question

I have a dataframe having categorical variables. I want to convert them to the numerical using the following logic:

I have 2 lists one contains the distinct categorical values in the column and the second list contains the values for each category. Now i need to map these values in place of those categorical values.

For Eg:

List_A = ['A','B','C','D','E']

List_B = [3,2,1,1,2]

I need to replace A with 3, B with 2, C and D with 1 and E with 2.

Is there any way to do this in Python.

I can do this by applying multiple for loops but I am looking for some easier way or some direct function if there is any.

Any help is very much appreciated, Thanks in Advance.

Answer 1

Create a mapping dict

List_A = ['A','B','C','D','E',]

List_B = [3,2,1,1,2]
d=dict(zip(List_A, List_B))

new_list=['A','B','C','D','E','A','B']
new_mapped_list=[d[v] for v in new_list if v in d]
new_mapped_list

Or define a function and use map

List_A = ['A','B','C','D','E',]

List_B = [3,2,1,1,2]

d=dict(zip(List_A, List_B))

def mapper(value):
    if value in d:
        return d[value]
    return None

new_list=['A','B','C','D','E','A','B']
map(mapper,new_list)

Answer 2

Suppose df is your data frame and "Category" is the name of the column holding your categories:

df[df.Category == "A"] = 3,2, 1, 1, 2
df[(df.Category == "B") | (df.Category == "E") ] = 2
df[(df.Category == "C") | (df.Category == "D") ] = 1

Answer 3

If you only need to replace values in one list with the values of other and the structure is like the one you say. Two list, same lenght and same position, then you only need this:

list_a = []
list_a = list_b

A more convoluted solution would be like this, with a function that will create a dictionary that you can use on other lists:

# we make a function
def convert_list(ls_a,ls_b):
    dic_new = {}
    for letter,number in zip(ls_a,ls_b):
        dic_new[letter] = number
    return dic_new

This will make a dictionary with the combinations you need. You pass the two list, then you can use that dictionary on other list:

List_A = ['A','B','C','D','E']
List_B = [3,2,1,1,2]

dic_new = convert_list(ls_a, ls_b)

other_list = ['a','b','c','d']

for _ in other_list:
    print(dic_new[_.upper()])

# prints
3
2
1
1

cheers

Answer 4

You could use a solution from machine learning scikit-learn module.

OneHotEncoder

LabelEncoder

http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html

The pandas "hard" way:

https://stackoverflow.com/a/29330853/9799449