python练习10
豆瓣图书评论数据分析与可视化.py
import refrom collections import Counter
import requests
from lxml import etree
import pandas as pd
import jieba
import matplotlib.pyplot as plt
from wordcloud import WordCloud
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.54 Safari/537.36 Edg/101.0.1210.39"
}
comments = []
words = []
def regex_change(line):
# 前缀的正则2
username_regex = re.compile(r"^\d+::")
# URL，为了防止对中文的过滤，所以使用[a-zA-Z0-9]而不是\w
url_regex = re.compile(r"""
(https?://)?
([a-zA-Z0-9]+)
(\.[a-zA-Z0-9]+)
(\.[a-zA-Z0-9]+)*
(/[a-zA-Z0-9]+)*
""", re.VERBOSE | re.IGNORECASE)
# 剔除日期
data_regex = re.compile(u""" #utf-8编码
年 |
月 |
日 |
(周一) |
(周二) |
(周三) |
(周四) |
(周五) |
(周六)
""", re.VERBOSE)
# 剔除所有数字
decimal_regex = re.compile(r"[^a-zA-Z]\d+")
# 剔除空格
space_regex = re.compile(r"\s+")
regEx = "[\n”“|,，；;''! 。的了是]" # 去除字符串中的换行符、中文冒号、|，需要去除什么字符就在里面写什么字符
line = re.sub(regEx, "", line)
line = username_regex.sub(r"", line)
line = url_regex.sub(r"", line)
line = data_regex.sub(r"", line)
line = decimal_regex.sub(r"", line)
line = space_regex.sub(r"", line)
return line
def getComments(url):
score = 0
resp = requests.get(url, headers=headers).text
html = etree.HTML(resp)
comment_list = html.xpath(".//div[@class='comment']")
for comment in comment_list:
status = ""
name = comment.xpath(".//span[@class='comment-info']/a/text()")[0] # 用户名
content = comment.xpath(".//p[@class='comment-content']/span[@class='short']/text()")[0] # 短评内容
content = str(content).strip()
word = jieba.cut(content, cut_all=False, HMM=False)
time = comment.xpath(".//span[@class='comment-info']/a/text()")[1] # 评论时间
mark = comment.xpath(".//span[@class='comment-info']/span/@title") # 评分
if len(mark) == 0:
score = 0
else:
for i in mark:
status = str(i)
if status == "力荐":
score = 5
elif status == "推荐":
score = 4
elif status == "还行":
score = 3
elif status == "较差":
score = 2
elif status == "很差":
score = 1
good = comment.xpath(".//span[@class='comment-vote']/span[@class='vote-count']/text()")[0] # 点赞数（有用数）
comments.append([str(name), content, str(time), score, int(good)])
for i in word:
if len(regex_change(i)) >= 2:
words.append(regex_change(i))
def getWordCloud(words):
# 生成词云
all_words = []
all_words += [word for word in words]
dict_words = dict(Counter(all_words))
bow_words = sorted(dict_words.items(), key=lambda d: d[1], reverse=True)
print("热词前10位：")
for i in range(10):
print(bow_words[i])
text = ' '.join(words)
w = WordCloud(background_color='white',
width=1000,
height=700,
font_path='simhei.ttf',
margin=10).generate(text)
plt.show()
plt.imshow(w)
w.to_file('wordcloud.png')
print("请选择以下选项:")
print(" 1.热门评论")
print(" 2.最新评论")
info = int(input())
print("前10位短评信息：")
title = ['用户名', '短评内容', '评论时间', '评分', '点赞数']
if info == 1:
comments = []
words = []
for i in range(0, 60, 20):
url = "https://book.douban.com/subject/10517238/comments/?start={}&limit=20&status=P&sort=new_score".format(
i) # 前3页短评信息（热门）
getComments(url)
df = pd.DataFrame(comments, columns=title)
print(df.head(10))
print("点赞数前10位的短评信息：")
df = df.sort_values(by='点赞数', ascending=False)
print(df.head(10))
getWordCloud(words)
elif info == 2:
comments = []
words=[]
for i in range(0, 60, 20):
url = "https://book.douban.com/subject/10517238/comments/?start={}&limit=20&status=P&sort=time".format(
i) # 前3页短评信息（最新）
getComments(url)
df = pd.DataFrame(comments, columns=title)
print(df.head(10))
print("点赞数前10位的短评信息：")
df = df.sort_values(by='点赞数', ascending=False)
print(df.head(10))
getWordCloud(words)
标签：comment,10,python,练习,regex,words,print,line From： https://www.cnblogs.com/yunbianshangdadun/p/17404410.html