转换和映射分类数据

Question

I have a dataset which has categoric and numeric columns. I want to convert the categoric data to numeric together with mapping each type of category to a specific numeric value. For example, under column ['Education'], I have Highschool, Undergraduate, Graduate, PHD etc. I'd appreciate if someone could provide me the code to map each code to an arbitrary numeric value.

Answer 1

import pandas as pd
df = pd.DataFrame(["Highschool", "Undergraduate","Highschool" ,"Graduate", "PHD", "Graduate", "Graduate","Undergraduate"],columns = ["Education"]) 
df_transformed = pd.get_dummies(df)

df_transformed.head()

OP:

 Education_Graduate Education_Highschool    Education_PHD   Education_Undergraduate
0         0               1                    0                0
1         0               0                    0                1
2         0               1                    0                0
3         1               0                    0                0
4         0               0                    1                0

#Label Encoding

from sklearn import preprocessing
encoder = preprocessing.LabelEncoder()
encoder.fit(df["Education"].values)

#use_any_input_list_here and it will assign a numerical value. I have given a sample list
encoder.transform(["Undergraduate","Highschool" ,"Graduate"])