如何解决如何迭代 Python 中多语言文本的结果?
我想计算我的数据实体的结果。
这是我的 df:
my_dict = {"customer_1": "Adidas é melhor do que Nike","customer_2": "Até que Nike é bom","customer_3": "Eu gosto do Google e da Microsoft"}
my_df = pd.DataFrame(list(my_dict.items()),columns = ['customer_id','review'])
print(my_df)
customer_id review
0 customer_1 Adidas é melhor do que Nike e Microsoft
1 customer_2 Até que Nike é bom
2 customer_3 Eu gosto do Google e da Microsoft
我正在使用 polyglot 的文本来识别这样的实体:
# Create a new text object using polyglot's Text class: txt
import polyglot
from polyglot.text import Text,Word
txt = Text(my_df['review'][2])
# Print each of the entities found
for ent in txt.entities:
print(ent)
['Google']
['Microsoft']
不是在括号内输入行数(如上),我想得到这样的结果:
Entity Count
Nike 2
Adidas 1
Google 1
Microsoft 2
到目前为止我已经尝试过了,但是没有用:
for i in x_col['Texto_Abertura']:
txt = Text(x_col['Texto_Abertura'][i])
# Print each of the entities found
for ent in txt.entities:
counter += ent
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