python3 和 python2 的语法差异应该是最蛋疼的事情了

dict本来就是没有顺序的吧

把dict转换成list

再去排序就会比较好了

#!/usr/bin/env python3

# -*- coding: utf-8 -*-

import jieba

import csv

def dict2list(dic:dict):

# 将字典转化为列表

keys = dic.keys()

vals = dic.values()

lst = [(key, val) for key, val in zip(keys, vals)]

return lst

csv_reader = csv.reader(open('/Users/dear_jinx/Desktop/zz.csv', 'U'))

dic = []

for row in csv_reader:

# seg_list = jieba.cut_for_search(row[4])

seg_list = jieba.cut(row[4])

for x in seg_list:

dic.append(x)

word = {}

for i in dic:

if i not in word:

word[i] = 1

else:

word[i] += 1

list = sorted(dict2list(word), key=lambda x: x[1], reverse=False)

for x in list:

print(x)

# for item in word.items():

# print(item)

# print("/".join(dic))

上面的方法太繁琐了，并且分词的效果也不好，会出现一些符号的统计。

这里我们只在列表里面加入那些长度大于等于2的词

并且用counter去做统计

#!/usr/bin/env python3

# -*- coding: utf-8 -*-

import jieba

import csv

from collections import Counter

def dict2list(dic:dict):

# 将字典转化为列表

keys = dic.keys()

vals = dic.values()

lst = [(key, val) for key, val in zip(keys, vals)]

return lst

csv_reader = csv.reader(open('/Users/dear_jinx/Desktop/zz.csv', 'U'))

dic = []

for row in csv_reader:

# seg_list = jieba.cut_for_search(row[4])

seg_list = jieba.cut(row[4])

for x in seg_list:

if len(x) >= 2:

dic.append(x)

c = Counter(dic).most_common(20)

print(c)