对句子列中的数据进行分类

Question

我正在尝试通过分析每行包含一个句子的列来添加一列单词类别

我尝试了以下代码，但它一直给我错误！

def loan_cat(row):
    rows = df[df.columns[0]].count()
    for i in rows: 
        data = df['purpose'][i]
        if 'house' in data:
            return 'house'
        elif 'education' | 'university' in data:
            return 'education'
        elif 'wedding' in data:
            return 'wedding'
        elif 'car' in data:
            return 'car'
        elif 'real' in data:
            return 'real estate'
        elif 'property'in data:
            return 'property'
        return 'undefined'
    
df['purpose_1'] = df.apply(loan_cat, axis=1)

是否有更好的方法来分析和分类数据？

Answer 1

使用字典

import pandas

data = pandas.Series(["purchase a house",
                      "purchase car",
                      "supplemental education",
                      "burger",
                      "attend university"])

arr = {"house": "house",
       "education": "education",
       "university": "education",
       "car": "car"}


def foo(s, d):
    for k, v in d.items():
        if k in s:
            return v
    return "NA"


data.apply(lambda x: foo(x, arr))
# 0        house
# 1          car
# 2    education
# 3           NA
# 4    education
# dtype: object

Answer 2

我找到答案了：

def loan_cat(value): 

      if 'hous' in value:
         return 'House'
      elif 'educ' in value:
         return 'Education'
      elif 'university' in value:
         return 'Education'
      elif 'wedding' in value:
         return 'Wedding'
      elif 'car' in value:
         return 'Car'
      elif 'real' in value:
         return 'Real Estate'
      elif 'property'in value:
         return 'Property'
      return 'undefined'

df['purpose_cat'] = df['purpose'].apply(lambda value: loan_cat(value)) 
print(df['purpose_cat'].value_counts())

对句子列中的数据进行分类

Categorize data from sentence column

python-3.x

pandas

dataframe

analysis