从 CSV 转换为 Python DataFrame 中的分类数据

Question

I have Insurance data that have a Colum Called 'Region' in which the regions are specified. For the Data Visualization Purpose, I need to change those alphabetical values to numerical values ie, South Should change to 1. If the region is only 1 or 2 I can change it but as the Region count is larger it is not possible. Is there any method to do this? Follow is code that I do so far(Not sure If it's correct or not)

k = insurance.shape[0]
dict1={}       
for i in range(k):
    if insurance['region'][i] in dict1:
        print('Testing')
    else:
        dict1[i] = insurance['region'][i]
print(dict1)

What should be the code to resolve the above-mentioned problem?

Answer 1

If you can use 3rd party libraries, you can leverage factorize . Following the docs , here as an example with toy data:

import pandas as pd

df = pd.DataFrame({"region": ["b", "c", "d" , "a", "a"]})

df["region_as_num"], _ = pd.factorize(df["region"], sort=True)