如何做pd.get_dummies或其他方式?

问题描述

实际上，我的问题是基于:

Actually,My problem is based on the :

是否存在

因此，数据应为:

import pandas as pd
import io
t="""
AV4MdG6Ihowv-SKBN_nB    DTP,FOOD
AV4Mc2vNhowv-SKBN_Rn    Cash 1,FOOD
AV4MeisikOpWpLdepWy6    DTP,Bar
AV4MeRh6howv-SKBOBOn    Cash 1,FOOD
AV4Mezwchowv-SKBOB_S    DTOT,Bar
AV4MeB7yhowv-SKBOA5b    DTP,Bar
"""
data_vec=pd.read_csv(io.StringIO(t),sep='\s{2,}',names=['id','source'])
data_vec

这是data_vec:

This is the data_vec:

    id  source
0   AV4MdG6Ihowv-SKBN_nB    DTP,FOOD
1   AV4Mc2vNhowv-SKBN_Rn    Cash 1,FOOD
2   AV4MeisikOpWpLdepWy6    DTP,Bar
3   AV4MeRh6howv-SKBOBOn    Cash 1,FOOD
4   AV4Mezwchowv-SKBOB_S    DTOT,Bar
5   AV4MeB7yhowv-SKBOA5b    DTP,Bar

如果我想要如下结果:(这意味着如何向量化多个标签或类别?)

If I want the result like follow:(It means how to vectorize the mutipletags or categories ?)

                  _id  source_Cash 1  source_DTOT  source_DTP  Food  Bar
0  AV4MdG6Ihowv-SKBN_nB              0            0        1      1    0
1  AV4Mc2vNhowv-SKBN_Rn              1            0        0      1    0
2  AV4MeisikOpWpLdepWy6              0            0        1      0    1
3  AV4MeRh6howv-SKBOBOn              1            0        0      1    0
4  AV4Mezwchowv-SKBOB_S              0            1        0      0    1
5  AV4MeB7yhowv-SKBOA5b              0            0        1      0    1

如果重复，请警告我删除！

If it is duplicate, warn me to delete!

推荐答案

一些str.split和pd.get_dummies魔术，由Scott Boston 进行了改进，并从原始版本进行了改进(从原始版本开始).

A bit of str.split and pd.get_dummies magic, inspired by Scott Boston and improved (from original version) thanks to JohnE.

df = df.set_index('id').source.str.get_dummies(',')
df.columns = df.columns.str.split().str[0].str.lower()
df = df.add_prefix('source_').reset_index()

print(df)
                     id  source_bar  source_cash  source_dtot  source_dtp  \
0  AV4MdG6Ihowv-SKBN_nB           0            0            0           1
1  AV4Mc2vNhowv-SKBN_Rn           0            1            0           0
2  AV4MeisikOpWpLdepWy6           1            0            0           1
3  AV4MeRh6howv-SKBOBOn           0            1            0           0
4  AV4Mezwchowv-SKBOB_S           1            0            1           0
5  AV4MeB7yhowv-SKBOA5b           1            0            0           1

   source_food
0            1
1            1
2            0
3            1
4            0
5            0

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