Question

这是我的熊猫提供的数据样本

word = pd.Series[['a', 'b', 'c', 'd'],['b', 'c'],['c', 'd'],['a', 'b', 'c']] 我想获取频率（1）和语料数据（2）

（1）频率（排序）

b : 3 
c : 3
d : 2
a : 2

（2）语料库数据（未排序）

corpus = ['a b c d', 'b c', 'c d', 'a b c']

如何获得这些？我需要帮助

我将python用于朝鲜语NLP：这是我的代码

import numpy as np
import pandas as pd

import itertools as it
from khaiii import KhaiiiApi # Korean NLP

df = pd.read_csv('https://drive.google.com/u/0/uc?id=1IZ1NYJmbabv6Xo7WJeqRcDFl1Z5pumni&export=download', encoding = 'utf-8')
df = pd.DataFrame(df)

api = KhaiiiApi()

def parse(sentence):
        pos = ((morph.lex, morph.tag) for word in api.analyze(sentence) for morph in word.morphs if morph.tag in ['NNG', 'VV', 'VA', 'NNP'])    # only nng, vv, va
        words = [item[0] if item[1] == 'NNG' or item[1] == 'NNP' else f'{item[0]}다' for item in pos]  # append suffix
        return words

df['내용'] = df["내용"].str.replace(",", "") 

split = df.내용.str.split(".")
split = split.apply(lambda x: pd.Series(x))
split = split.stack().reset_index(level=1,drop=True).to_frame('sentences')
df = df.merge(split, left_index=True, right_index=True, how='left')
df = df.drop(['내용'], axis = 1)
df['sentences'].replace('', np.nan, inplace= True)  
df['sentences'].replace(' ', np.nan, inplace= True)
df.dropna(subset=['sentences'], inplace=True)

df['reconstruct'] = df['sentences'].apply(parse)

Answer 1

您可以在value_counts之后使用explode（熊猫0.25 +

）获得频率

word.explode().value_counts()
c    4
b    3
d    2
a    2
dtype: int64

您可以通过以下方式获取值

corpus = [' '.join(v) for k, v in word.to_dict().items()]
print(corpus)
['a b c d', 'b c', 'c d', 'a b c']

计算熊猫的str频率

1 个答案: