爬取和分析电影《流浪地球》的猫眼评论

爬取和分析电影《流浪地球》的猫眼评论

一,选题背景

《流浪地球》在猫眼评论区的评价趋于两极分化,很多人将其与“爱国主义情怀”联系在一起,这并没有必要,因为电影毕竟只是电影,更何况这是一部商业片,其根本目的是赚取更多票房。将一种商业模式的产物与“爱国主义”联系在一起,是对“爱国”的误解——热爱祖国,不需要通过夸奖一部电影来表达。同理,对国产电影合理且有依有据的批判,也并不代表着对国产电影的失望。

 

二,设计方案

1,爬虫名称:爬取和分析电影《流浪地球》的猫眼评论

2,爬虫爬取的内容与数据特征分析

内容:爬取电影《流浪地球》的猫眼评论,把评论保存到mongodb

数据特征分析:

  • 共有102580条数据;
  • 包含字段:评论内容、性别、评论ID、评论者昵称、回复数量、评分、时间、点赞数量、评论者ID、评论者等级

 

三,结构特征分析

 

1,页面的结构与特征分析

 

 

 

 

四,程序设计

 

1.#实例化MongoClient,# 连接到maoyan数据库

 

 

 1 import pandas as pd
 2 import numpy as np
 3 import matplotlib.pyplot as plt
 4 from pymongo import MongoClient
 5 from pandas.io.json import json_normalize
 6 %matplotlib inline
 7 
 8 conn = MongoClient(host='127.0.0.1', port=27017)  # 实例化MongoClient
 9 db = conn.get_database('maoyan')  # 连接到maoyan数据库
10 maoyan = db.get_collection('maoyan') # 连接到集合maoyan
11 mon_data = maoyan.find()  # 查询这个集合下的所有记录
12 
13 data = json_normalize([comment for comment in mon_data])
14 
15 data.info()

 

 

 

data.head()

 

 2,#数据清洗

1 # 数据清洗
2 data = data.drop(columns='_id')
3 data = data.drop_duplicates(subset='userId')
4 data['time'] = pd.to_datetime(data['time']/1000, unit='s')
5 data = data[data['time']>=pd.to_datetime('2019-02-05 00:00:00')]
6 data.set_index(data["time"], inplace=True)
7 data.head()

 

1 data.info()

 

 3,#数据分析

  • 共有102580条数据;
  • 包含字段:评论内容、性别、评论ID、评论者昵称、回复数量、评分、时间、点赞数量、评论者ID、评论者等级
#3.1. 总体评价
data['score'].mean()

 

 1 from pyecharts import Bar
 2 from pyecharts import Line
 3 from pyecharts import Overlap
 4 
 5 score_total = data['score'].value_counts().sort_index()
 6 bar = Bar("《流浪地球》各评分数量", width=700)
 7 line = Line("", width=700)
 8 bar.add("", score_total.index, score_total.values, is_stack=True, is_label_show=True,
 9        bar_category_gap='40%', label_color = ['#130f40'],
10        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
11 line.add("", score_total.index, score_total.values+1000, is_smooth=True)
12 
13 overlap = Overlap(width=700)
14 overlap.add(bar)
15 overlap.add(line)
16 
17 overlap
1 # 低分百分比
2 score_total[:5].sum()/score_total.sum()*100

 

 

# 高分百分比
score_total[7:].sum()/score_total.sum()*100

 

 

# 满分百分比
score_total[10:].sum()/score_total.sum()*100

 

 

 #3.2总体评价的时间走向

1 score_by_time = data['score'].resample('H').mean()
2 line = Line("《流浪地球》平均评分时间走向", width=700)
3 line.add("", score_by_time.index.date, score_by_time.values, is_smooth=True,
4          legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18,
5          xaxis_rotate=20, yaxis_min=8)
6 line
score_by_time.nsmallest(6)

 

 

#3.3. 高分的评价理由
 1 import jieba
 2 from collections import Counter
 3 from pyecharts import WordCloud
 4 
 5 jieba.add_word('屈楚萧')
 6 jieba.add_word('刘启')
 7 jieba.add_word('吴京')
 8 jieba.add_word('刘培强')
 9 jieba.add_word('李光洁')
10 jieba.add_word('王磊')
11 jieba.add_word('吴孟达')
12 jieba.add_word('达叔')
13 jieba.add_word('韩子昂')
14 jieba.add_word('赵今麦')
15 jieba.add_word('韩朵朵')
16 
17 swords = [x.strip() for x in open ('stopwords.txt')]
 1 def plot_word_cloud(data, swords):
 2     text = ''.join(data['content'])
 3     words = list(jieba.cut(text))
 4     ex_sw_words = []
 5     for word in words:
 6         if len(word)>1 and (word not in swords):
 7             ex_sw_words.append(word)
 8     c = Counter()
 9     c = Counter(ex_sw_words)
10     wc_data = pd.DataFrame({'word':list(c.keys()), 'counts':list(c.values())}).sort_values(by='counts', ascending=False).head(100)
11     wordcloud = WordCloud(width=1300, height=620)
12     wordcloud.add("", wc_data['word'], wc_data['counts'], word_size_range=[20, 100])
13     return wordcloud
14 # 高分的评价
15 plot_word_cloud(data=data[data['score']>6], swords=swords)
1 data[data['score']>6].nlargest(10, 'upCount')

 

 

1 for i in data[data['score']>6].nlargest(10, 'upCount')['content']:
2     print(i+'\n')

 

 #3.4 低分的评价理由

 

1 # 低分的评价
2 plot_word_cloud(data=data[data['score']<5], swords=swords)
1 data[data['score']<5].nlargest(10, 'upCount')

 

 

 

 

1 for i in data[data['score']<5].nlargest(10, 'upCount')['content']:
2     print(i+'\n')

 

 #3.5低分的人群有哪些特征

1 # 总体的性别比例
2 gender_total = data['gender'].value_counts()
3 bar = Bar("《流浪地球》观众性别", width=700)
4 bar.add("", ['未知', '', ''], gender_total.values, is_stack=True, is_label_show=True,
5        bar_category_gap='60%', label_color = ['#130f40'],
6        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
7 bar
8 gender_total/gender_total.sum()*100

 

 

 1 # 低分的性别比例
 2 
 3 gender_low = data.loc[data['score']<5, 'gender'].value_counts()
 4 
 5 bar = Bar("《流浪地球》低分评论观众性别", width=700)
 6 
 7 bar.add("", ['未知'zh, '', ''], gender_low.values, is_stack=True, is_label_show=True, bar_category_gap='60%', label_color = ['#130f40'],
 8 
 9 legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
10 
11 bar
12 
13 gender_low/gender_low.sum()*100

 

 

 

 

 1 mapping = {'liucixin':'刘慈欣|大刘', 'guofan':'郭帆', 'quchuxiao':'屈楚萧|刘启|户口', 'wujing':'吴京|刘培强',
 2 
 3 'liguangjie':'李光洁|王磊', 'wumengda':'吴孟达|达叔|韩子昂', 'zhaojinmai':'赵今麦|韩朵朵'}
 4 
 5 for key, value in mapping.items():
 6 
 7 data[key] = data['content'].str.contains(value)
 8 
 9 
10 # 总体提及次数 staff_count = pd.Series({key: data.loc[data[key], 'score'].count() for key in
11 
12 mapping.keys()}).sort_values()
13 
14 staff_count

 


 

 

1 bar = Bar("《流浪地球》演职员总体提及次数", width=700)
2 bar.add("", ['李光洁','郭帆','赵今麦','吴孟达','屈楚萧','刘慈欣','吴京'], staff_count.values, is_stack=True, is_label_show=True,
3        bar_category_gap='60%', label_color = ['#130f40'],
4        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
5 bar
6 average_score = pd.Series({key: data.loc[data[key], 'score'].mean() for key in mapping.keys()}).sort_values()
7 average_score

 

 

 

1 bar = Bar("《流浪地球》演职员平均分", width=700)
2 bar.add("", ['赵今麦','吴孟达','吴京','屈楚萧','李光洁','刘慈欣','郭帆'], np.round(average_score.values,2), is_stack=True, is_label_show=True,
3        bar_category_gap='60%', label_color = ['#130f40'],
4        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
5 bar
6 
7 staff_count_low = pd.Series({key: data.loc[data[key]&(data['score']<5), 'score'].count() for key in mapping.keys()}).sort_values()
8 staff_count_low

 

 

 

 

1 staff_count_pct = np.round(staff_count_low/staff_count*100, 2).sort_values()
2 staff_count_pct

 

 

 

1 bar = Bar("《流浪地球》演职员低分评论提及百分比", width=700)
2 bar.add("", ['郭帆','刘慈欣','李光洁','屈楚萧','赵今麦','吴京','吴孟达'], staff_count_pct.values, is_stack=True, is_label_show=True,
3        bar_category_gap='60%', label_color = ['#130f40'],
4        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
5 bar
6 
7 data[data['wumengda']&(data['score']<5)].nlargest(5, 'upCount')

 

 


 

 

1 for i in data[data['wujing']&(data['score']<5)].nlargest(5, 'upCount')['content']:
2     print(i+'\n')

 


 

五、总结

总体来说,猫眼的观众对于这部电影的认可度还是很高的,认为导演良心、剧情紧凑、表演过关、特效震撼,中国首部硬核科幻电影当之无愧!同时也还是有一些剧情上和年轻演员上的小问题,导致有些本片有些尴尬和无聊。不过,我觉得瑕不掩瑜、应该支持,相较于真正低分的毕导的《逐梦演艺圈》,不知道高到哪里去了。希望国产科幻片可以越来越好!

 

完整代码:

 

  1 import os
  2 import time
  3 from datetime import datetime
  4 import requests
  5 from pymongo import MongoClient
  6 
  7 
  8 class MaoYan(object):
  9 """
 10 猫眼评论爬虫,爬取电影《流浪地球》的评论和评分
 11 """
 12 
 13 def __init__(self):
 14 """
 15 初始化函数
 16 :param
 17 headers: 请求头
 18 time: 当前时间戳
 19 premiere_time: 首映时间的时间戳
 20 """
 21 self.headers = {'User-Agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 11_0 like Mac OS X) AppleWebKit/604.1.'
 22 '38 (KHTML, like Gecko) Version/11.0 Mobile/15A372 Safari/604.1',
 23 'Connection': 'keep-alive',
 24 'Cookie': '_lxsdk_cuid=168d5d128e7c8-033114908a580c-10376654-fa000-168d5d128e7c8;'
 25 ' _lx_utm=utm_source%3Dbing%26utm_medium%3Dorganic; uuid_n_v=v1;'
 26 ' iuuid=5D49FF702DB211E9AF1B8D0648275EC02D381B7848144BC1A299A63C05094BF5;'
 27 ' webp=true; selectci=true; ci=281%2C%E6%83%A0%E5%B7%9E;'
 28 ' __mta=247299643.1549775481575.1549783540088.1549862773375.3;'
 29 ' _lxsdk=5D49FF702DB211E9AF1B8D0648275EC02D381B7848144BC1A299A63C05094BF5;'
 30 ' _lxsdk_s=168db05185a-332-e0d-bc5%7C%7C157'}
 31 self.time = int(time.time()*1000)
 32 self.premiere_time = int(time.mktime(time.strptime('2019-02-05 00:00:00', '%Y-%m-%d %H:%M:%S'))*1000)
 33 
 34 # 配置mongodb数据库
 35 host = os.environ.get('MONGODB_HOST', '127.0.0.1') # 本地数据库
 36 port = os.environ.get('MONGODB_PORT', '27017') # 数据库端口
 37 mongo_url = 'mongodb://{}:{}'.format(host, port)
 38 mongo_db = os.environ.get('MONGODB_DATABASE', 'maoyan')
 39 client = MongoClient(mongo_url)
 40 self.db = client[mongo_db]
 41 self.db['maoyan'].create_index('id', unique=True) # 以评论的id为主键进行去重
 42 
 43 def get_comment(self):
 44 """
 45 爬取首映到当前时间的电影评论
 46 :param
 47 url: 评论真实请求的url,参数ts为时间戳
 48 :return: None
 49 """
 50 url = 'http://m.maoyan.com/review/v2/comments.json?movieId=248906&userId=-1&' \
 51 'offset=0&limit=15&ts={}&type=3'
 52 while self.time > self.premiere_time:
 53 req_url = url.format(self.time)
 54 res = requests.get(req_url, headers=self.headers)
 55 count = 0
 56 for com in res.json()['data']['comments']:
 57 self.parse_comment(com=com)
 58 count += 1
 59 if count == 15:
 60 self.time = com['time']
 61 
 62 print('成功爬取截止到{}的数据!'.format(datetime.fromtimestamp(int(self.time/1000))))
 63 
 64 def parse_comment(self, com):
 65 """
 66 解析函数,用来解析爬回来的json评论数据,并把数据保存进mongodb数据库
 67 :param com: 每一条评论的json数据
 68 :return:
 69 """
 70 comment = {'content': com['content'], 'gender': com['gender'], 'id': com['id'],
 71 'nick': com['nick'], 'replyCount': com['replyCount'], 'score': com['score'],
 72 'time': com['time'], 'upCount': com['upCount'],
 73 'userId': com['userId'], 'userLevel': com['userLevel']} # 构造评论字典
 74 # 通过评论id去重,如果已经有了就更新,没有就插入
 75 self.db['maoyan'].update_one({'id': comment['id']}, {'$set': comment}, upsert=True)
 76 
 77 
 78 if __name__ == '__main__':
 79 my = MaoYan()
 80 my.get_comment()
 81 
 82 import pandas as pd
 83 import numpy as np
 84 import matplotlib.pyplot as plt
 85 from pymongo import MongoClient
 86 from pandas.io.json import json_normalize
 87 %matplotlib inline
 88 
 89 conn = MongoClient(host='127.0.0.1', port=27017)  # 实例化MongoClient
 90 db = conn.get_database('maoyan')  # 连接到maoyan数据库
 91 
 92 maoyan = db.get_collection('maoyan') # 连接到集合maoyan
 93 mon_data = maoyan.find()  # 查询这个集合下的所有记录
 94 
 95 
 96 data = json_normalize([comment for comment in mon_data])
 97 
 98 
 99 data.info()
100 
101 data.head()
102 
103 # 数据清洗
104 data = data.drop(columns='_id')
105 data = data.drop_duplicates(subset='userId')
106 data['time'] = pd.to_datetime(data['time']/1000, unit='s')
107 data = data[data['time']>=pd.to_datetime('2019-02-05 00:00:00')]
108 data.set_index(data["time"], inplace=True)
109 data.head()
110 
111 data.info()
112 
113 
114 data['score'].mean()
115 
116 from pyecharts import Bar
117 from pyecharts import Line
118 from pyecharts import Overlap
119 
120 score_total = data['score'].value_counts().sort_index()
121 bar = Bar("《流浪地球》各评分数量", width=700)
122 line = Line("", width=700)
123 bar.add("", score_total.index, score_total.values, is_stack=True, is_label_show=True,
124        bar_category_gap='40%', label_color = ['#130f40'],
125        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
126 line.add("", score_total.index, score_total.values+1000, is_smooth=True)
127 
128 overlap = Overlap(width=700)
129 overlap.add(bar)
130 overlap.add(line)
131 
132 overlap
133 
134 # 低分百分比
135 score_total[:5].sum()/score_total.sum()*100
136 
137 # 高分百分比
138 score_total[7:].sum()/score_total.sum()*100
139 
140 # 满分百分比
141 score_total[10:].sum()/score_total.sum()*100
142 
143 
144 score_by_time = data['score'].resample('H').mean()
145 line = Line("《流浪地球》平均评分时间走向", width=700)
146 line.add("", score_by_time.index.date, score_by_time.values, is_smooth=True,
147          legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18,
148          xaxis_rotate=20, yaxis_min=8)
149 line
150 
151 
152 score_by_time.nsmallest(6)
153 
154 import jieba
155 from collections import Counter
156 from pyecharts import WordCloud
157 
158 jieba.add_word('屈楚萧')
159 jieba.add_word('刘启')
160 jieba.add_word('吴京')
161 jieba.add_word('刘培强')
162 jieba.add_word('李光洁')
163 jieba.add_word('王磊')
164 jieba.add_word('吴孟达')
165 jieba.add_word('达叔')
166 jieba.add_word('韩子昂')
167 jieba.add_word('赵今麦')
168 jieba.add_word('韩朵朵')
169 
170 swords = [x.strip() for x in open ('stopwords.txt')]
171 
172 
173 def plot_word_cloud(data, swords):
174     text = ''.join(data['content'])
175     words = list(jieba.cut(text))
176     ex_sw_words = []
177     for word in words:
178         if len(word)>1 and (word not in swords):
179             ex_sw_words.append(word)
180     c = Counter()
181     c = Counter(ex_sw_words)
182     wc_data = pd.DataFrame({'word':list(c.keys()), 'counts':list(c.values())}).sort_values(by='counts', ascending=False).head(100)
183     wordcloud = WordCloud(width=1300, height=620)
184     wordcloud.add("", wc_data['word'], wc_data['counts'], word_size_range=[20, 100])
185     return wordcloud
186 
187 
188 # 高分的评价
189 plot_word_cloud(data=data[data['score']>6], swords=swords)
190 
191 
192 data[data['score']>6].nlargest(10, 'upCount')
193 
194 
195 for i in data[data['score']>6].nlargest(10, 'upCount')['content']:
196     print(i+'\n')
197 
198 
199 # 低分的评价
200 plot_word_cloud(data=data[data['score']<5], swords=swords)
201 
202 data[data['score']<5].nlargest(10, 'upCount')
203 
204 for i in data[data['score']<5].nlargest(10, 'upCount')['content']:
205     print(i+'\n')
206 
207 # 总体的性别比例
208 gender_total = data['gender'].value_counts()
209 bar = Bar("《流浪地球》观众性别", width=700)
210 bar.add("", ['未知', '', ''], gender_total.values, is_stack=True, is_label_show=True,
211        bar_category_gap='60%', label_color = ['#130f40'],
212        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
213 bar
214 
215 gender_total/gender_total.sum()*100
216 
217 # 低分的性别比例
218 gender_low = data.loc[data['score']<5, 'gender'].value_counts()
219 bar = Bar("《流浪地球》低分评论观众性别", width=700)
220 bar.add("", ['未知'zh, '', ''], gender_low.values, is_stack=True, is_label_show=True,
221        bar_category_gap='60%', label_color = ['#130f40'],
222        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
223 bar
224 
225 gender_low/gender_low.sum()*100
226 
227 
228 # 总体的等级比例
229 level_total = data['userLevel'].value_counts().sort_index()
230 bar = Bar("《流浪地球》观众等级", width=700)
231 bar.add("", level_total.index, level_total.values, is_stack=True, is_label_show=True,
232        bar_category_gap='40%', label_color = ['#130f40'],
233        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
234 bar
235 
236 # 低分评论的观众等级比例
237 level_low = data.loc[data['score']<5, 'userLevel'].value_counts().sort_index()
238 bar = Bar("《流浪地球》低分评论的观众等级", width=700)
239 bar.add("", level_low.index, level_low.values, is_stack=True, is_label_show=True,
240        bar_category_gap='40%', label_color = ['#130f40'],
241        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
242 bar
243 
244 
245 mapping = {'liucixin':'刘慈欣|大刘', 'guofan':'郭帆', 'quchuxiao':'屈楚萧|刘启|户口', 'wujing':'吴京|刘培强', 
246            'liguangjie':'李光洁|王磊', 'wumengda':'吴孟达|达叔|韩子昂', 'zhaojinmai':'赵今麦|韩朵朵'}
247 for key, value in mapping.items():
248     data[key] = data['content'].str.contains(value)
249 
250 
251 # 总体提及次数
252 staff_count = pd.Series({key: data.loc[data[key], 'score'].count() for key in mapping.keys()}).sort_values()
253 staff_count
254 
255 bar = Bar("《流浪地球》演职员总体提及次数", width=700)
256 bar.add("", ['李光洁','郭帆','赵今麦','吴孟达','屈楚萧','刘慈欣','吴京'], staff_count.values, is_stack=True, is_label_show=True,
257        bar_category_gap='60%', label_color = ['#130f40'],
258        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
259 bar
260 
261 
262 average_score = pd.Series({key: data.loc[data[key], 'score'].mean() for key in mapping.keys()}).sort_values()
263 average_score
264 
265 bar = Bar("《流浪地球》演职员平均分", width=700)
266 bar.add("", ['赵今麦','吴孟达','吴京','屈楚萧','李光洁','刘慈欣','郭帆'], np.round(average_score.values,2), is_stack=True, is_label_show=True,
267        bar_category_gap='60%', label_color = ['#130f40'],
268        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
269 bar
270 
271 staff_count_low = pd.Series({key: data.loc[data[key]&(data['score']<5), 'score'].count() for key in mapping.keys()}).sort_values()
272 staff_count_low
273 
274 staff_count_pct = np.round(staff_count_low/staff_count*100, 2).sort_values()
275 staff_count_pct
276 
277 
278 bar = Bar("《流浪地球》演职员低分评论提及百分比", width=700)
279 bar.add("", ['郭帆','刘慈欣','李光洁','屈楚萧','赵今麦','吴京','吴孟达'], staff_count_pct.values, is_stack=True, is_label_show=True,
280        bar_category_gap='60%', label_color = ['#130f40'],
281        legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)
282 bar
283 
284 
285 data[data['wumengda']&(data['score']<5)].nlargest(5, 'upCount')
286 
287 
288 for i in data[data['wumengda']&(data['score']<5)].nlargest(5, 'upCount')['content']:
289     print(i+'\n')
290 
291 
292 data[data['wujing']&(data['score']<5)].nlargest(5, 'upCount')
293 
294 for i in data[data['wujing']&(data['score']<5)].nlargest(5, 'upCount')['content']:
295     print(i+'\n')
296 
297 data[data['zhaojinmai']&(data['score']<5)].nlargest(5, 'upCount')
298 
299 for i in data[data['zhaojinmai']&(data['score']<5)].nlargest(5, 'upCount')['content']:
300     print(i+'\n')

 

 

 

 

 

[{"metadata":{"trusted":false},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom pymongo import MongoClient\nfrom pandas.io.json import json_normalize\nmatplotlib inline","execution_count":null,"outputs":[]},{"metadata":{"trusted":false},"cell_type":"code","source":"conn = MongoClient(host='127.0.0.1', port=27017)  # 实例化MongoClient\ndb = conn.get_database('maoyan')  # 连接到maoyan数据库\n\nmaoyan = db.get_collection('maoyan') # 连接到集合maoyan\nmon_data = maoyan.find()  # 查询这个集合下的所有记录","execution_count":null,"outputs":[]},{"metadata":{"trusted":false},"cell_type":"code","source":"data = json_normalize([comment for comment in mon_data])","execution_count":null,"outputs":[]},{"metadata":{"trusted":false},"cell_type":"code","source":"data.info()","execution_count":null,"outputs":[]},{"metadata":{"trusted":false},"cell_type":"code","source":"data.head()","execution_count":2,"outputs":[{"ename":"NameError","evalue":"name 'data' is not defined","output_type":"error","traceback":["\u001b[1;31m---------------------------------------------------------------------------\u001b[0m","\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)","\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[1;31mNameError\u001b[0m: name 'data' is not defined"]}]},{"metadata":{"scrolled":true,"trusted":false},"cell_type":"code","source":"# 数据清洗\ndata = data.drop(columns='_id')\ndata = data.drop_duplicates(subset='userId')\ndata['time'] = pd.to_datetime(data['time']/1000, unit='s')\ndata = data[data['time']>=pd.to_datetime('2019-02-05 00:00:00')]\ndata.set_index(data[\"time\"], inplace=True)\ndata.head()","execution_count":6,"outputs":[{"data":{"text/html":"
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 contentgenderidnickreplyCountscoretimeupCountuserIduserLevel
time          
2019-02-11 10:10:00 很好震撼的很啊 1 1056560079 江生 0 9 2019-02-11 10:10:00 0 201695017 3
2019-02-11 10:10:00 国产的科幻巅峰,丝毫不逊色好莱坞科幻大片,影响力就像星球大战一样,是国产科幻的开山之做,希望... 0 1056560077 Decadence 0 10 2019-02-11 10:10:00 0 1020875871 4
2019-02-11 10:10:00 超级好看啊 户口帅的一批 我自己一个人看的 看得热血沸腾啊 爷爷死的时候真的哭死了 2 1056557517 暴走萝莉912 0 10 2019-02-11 10:10:00 0 304299563 3
2019-02-11 10:10:00 保护生态环境,从我做 1 1056557516 *^_^*红尘逍遥 0 10 2019-02-11 10:10:00 0 1548122992 2
2019-02-11 10:10:00 超级好看,感动,特效好哒 2 1056560066 罗大大 0 9 2019-02-11 10:10:00 0 897364142 2
\n
","text/plain":"                                                               content  \\\ntime                                                                     \n2019-02-11 10:10:00                                            很好震撼的很啊   \n2019-02-11 10:10:00  国产的科幻巅峰,丝毫不逊色好莱坞科幻大片,影响力就像星球大战一样,是国产科幻的开山之做,希望...   \n2019-02-11 10:10:00          超级好看啊 户口帅的一批 我自己一个人看的 看得热血沸腾啊 爷爷死的时候真的哭死了   \n2019-02-11 10:10:00                                         保护生态环境,从我做   \n2019-02-11 10:10:00                                       超级好看,感动,特效好哒   \n\n                     gender          id       nick  replyCount  score  \\\ntime                                                                    \n2019-02-11 10:10:00       1  1056560079         江生           0      9   \n2019-02-11 10:10:00       0  1056560077  Decadence           0     10   \n2019-02-11 10:10:00       2  1056557517    暴走萝莉912           0     10   \n2019-02-11 10:10:00       1  1056557516  *^_^*红尘逍遥           0     10   \n2019-02-11 10:10:00       2  1056560066        罗大大           0      9   \n\n                                   time  upCount      userId  userLevel  \ntime                                                                     \n2019-02-11 10:10:00 2019-02-11 10:10:00        0   201695017          3  \n2019-02-11 10:10:00 2019-02-11 10:10:00        0  1020875871          4  \n2019-02-11 10:10:00 2019-02-11 10:10:00        0   304299563          3  \n2019-02-11 10:10:00 2019-02-11 10:10:00        0  1548122992          2  \n2019-02-11 10:10:00 2019-02-11 10:10:00        0   897364142          2  "},"execution_count":6,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"data.info()","execution_count":7,"outputs":[{"name":"stdout","output_type":"stream","text":"<class 'pandas.core.frame.dataframe'="">\nDatetimeIndex: 102580 entries, 2019-02-11 10:10:00 to 2019-02-11 01:40:00\nData columns (total 10 columns):\ncontent       102580 non-null object\ngender        102580 non-null int64\nid            102580 non-null int64\nnick          102580 non-null object\nreplyCount    102580 non-null int64\nscore         102580 non-null int64\ntime          102580 non-null datetime64[ns]\nupCount       102580 non-null int64\nuserId        102580 non-null int64\nuserLevel     102580 non-null int64\ndtypes: datetime64[ns](1), int64(7), object(2)\nmemory usage: 8.6+ MB\n"}]},{"metadata":{},"cell_type":"markdown","source":"#### 一、数据详情\n- 共有102580条数据;\n- 包含字段:评论内容、性别、评论ID、评论者昵称、回复数量、评分、时间、点赞数量、评论者ID、评论者等级\n\n#### 二、问题\n1. 总体评价如何?\n2. 总体评价的时间走向如何?\n3. 高分的评价理由是什么?\n4. 低分的评价理由是什么?\n5. 低分的人群有哪些特征?(性别、等级)\n6. 低分跟哪位演员有关?"},{"metadata":{},"cell_type":"markdown","source":"##### 1. 总体评价如何?"},{"metadata":{"trusted":false},"cell_type":"code","source":"data['score'].mean()","execution_count":8,"outputs":[{"data":{"text/plain":"9.241450575160851"},"execution_count":8,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"from pyecharts import Bar\nfrom pyecharts import Line\nfrom pyecharts import Overlap\n\nscore_total = data['score'].value_counts().sort_index()\nbar = Bar(\"《流浪地球》各评分数量\", width=700)\nline = Line(\"\", width=700)\nbar.add(\"\", score_total.index, score_total.values, is_stack=True, is_label_show=True,\n       bar_category_gap='40%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nline.add(\"\", score_total.index, score_total.values+1000, is_smooth=True)\n\noverlap = Overlap(width=700)\noverlap.add(bar)\noverlap.add(line)\n\noverlap","execution_count":9,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":9,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 低分百分比\nscore_total[:5].sum()/score_total.sum()*100","execution_count":10,"outputs":[{"data":{"text/plain":"3.6342366933125363"},"execution_count":10,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 高分百分比\nscore_total[7:].sum()/score_total.sum()*100","execution_count":11,"outputs":[{"data":{"text/plain":"93.54650029245467"},"execution_count":11,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 满分百分比\nscore_total[10:].sum()/score_total.sum()*100","execution_count":12,"outputs":[{"data":{"text/plain":"71.40280756482746"},"execution_count":12,"metadata":{},"output_type":"execute_result"}]},{"metadata":{},"cell_type":"markdown","source":"##### 2. 总体评价的时间走向如何?"},{"metadata":{"trusted":false},"cell_type":"code","source":"score_by_time = data['score'].resample('H').mean()\nline = Line(\"《流浪地球》平均评分时间走向\", width=700)\nline.add(\"\", score_by_time.index.date, score_by_time.values, is_smooth=True,\n         legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18,\n         xaxis_rotate=20, yaxis_min=8)\nline","execution_count":40,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":40,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"score_by_time.nsmallest(6)","execution_count":48,"outputs":[{"data":{"text/plain":"time\n2019-02-07 21:00:00    8.357143\n2019-02-10 22:00:00    8.375000\n2019-02-08 21:00:00    8.461538\n2019-02-05 01:00:00    8.594203\n2019-02-10 21:00:00    8.636364\n2019-02-09 22:00:00    8.739130\nName: score, dtype: float64"},"execution_count":48,"metadata":{},"output_type":"execute_result"}]},{"metadata":{},"cell_type":"markdown","source":"##### 3. 高分的评价理由是什么?"},{"metadata":{"trusted":false},"cell_type":"code","source":"import jieba\nfrom collections import Counter\nfrom pyecharts import WordCloud\n\njieba.add_word('屈楚萧')\njieba.add_word('刘启')\njieba.add_word('吴京')\njieba.add_word('刘培强')\njieba.add_word('李光洁')\njieba.add_word('王磊')\njieba.add_word('吴孟达')\njieba.add_word('达叔')\njieba.add_word('韩子昂')\njieba.add_word('赵今麦')\njieba.add_word('韩朵朵')\n\nswords = [x.strip() for x in open ('stopwords.txt')]","execution_count":103,"outputs":[]},{"metadata":{"trusted":false},"cell_type":"code","source":"def plot_word_cloud(data, swords):\n    text = ''.join(data['content'])\n    words = list(jieba.cut(text))\n    ex_sw_words = []\n    for word in words:\n        if len(word)>1 and (word not in swords):\n            ex_sw_words.append(word)\n    c = Counter()\n    c = Counter(ex_sw_words)\n    wc_data = pd.DataFrame({'word':list(c.keys()), 'counts':list(c.values())}).sort_values(by='counts', ascending=False).head(100)\n    wordcloud = WordCloud(width=1300, height=620)\n    wordcloud.add(\"\", wc_data['word'], wc_data['counts'], word_size_range=[20, 100])\n    return wordcloud","execution_count":132,"outputs":[]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 高分的评价\nplot_word_cloud(data=data[data['score']>6], swords=swords)","execution_count":145,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":145,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"data[data['score']>6].nlargest(10, 'upCount')","execution_count":146,"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
 contentgenderidnickreplyCountscoretimeupCountuserIduserLevel
time          
2019-02-05 00:02:00 为什么没有7星,8星?完美已经不足以诠释这部电影的出色!感动,全程捏着拳头看完。叙事不拖沓,... 1 1053375466 奇异果Grissom 271 10 2019-02-05 00:02:00 5627 681463650 3
2019-02-05 11:28:00 在学校看了《流浪地球》的点映!除了电影情节、在现场看到了大刘老师!我更难忘的是郭帆导演在现场... 2 1052407417 Hope And Legacy 108 10 2019-02-05 11:28:00 3838 1812991790 4
2019-02-07 09:16:00 10分!太棒了!三次掉泪,父爱如山啊。40年前《星球大战》横空出世,好莱坞工业绿魔就此诞生;... 1 1054132930 CHAOSAY 29 10 2019-02-07 09:16:00 280 9693997 4
2019-02-05 14:56:00 超过预期。《流浪地球》的确开启了中国科幻片和灾难片的新纪元,无论是在哪一坐标中进行比对。虽然... 1 1053946211 徐若风 4 9 2019-02-05 14:56:00 224 116677026 4
2019-02-06 17:48:00 这场浩浩汤汤的太阳系“春运”燃情又暖心。父子情,战友情,人类与人工智能的情感与理智的抉择,电... 1 1054564832 电影大指南 12 10 2019-02-06 17:48:00 207 272340441 4
2019-02-05 11:01:00 中国终于有自己拿的出手的科幻片了!\\n特效OK,剧情OK,没有大牌明星但全部演技都算得上OK... 0 1053741717 shadownihil 20 10 2019-02-05 11:01:00 201 8208177 4
2019-02-09 02:04:00 从故事层面,本片以刘慈欣科幻小说作为基底,剧本改编非常的扎实,不仅极具想象力,而且也涉及到很... 1 1055541594 娱评天下 9 10 2019-02-09 02:04:00 184 172967358 4
2019-02-05 13:03:00 剧作短板,特效完美,演员优秀,逻辑还是完全经不起推销。地球离太阳最后的距离还不得冻成一个冰球... 2 1053840774 刘小黛 194 7 2019-02-05 13:03:00 174 12695322 3
2019-02-05 14:44:00 前部分虽有不足,但特效是超出预期,后劲较足,到了中后部分有两个地方感动到我,刘培强实现预言,... 2 1053940077 JuliaFanl 6 8 2019-02-05 14:44:00 172 227360759 5
2019-02-07 05:40:00 在电影院看到的预告片,希望早日上映 1 134074136 纸牌巫 4 9 2019-02-07 05:40:00 110 418468642 3
\n
","text/plain":"                                                               content  \\\ntime                                                                     \n2019-02-05 00:02:00  为什么没有7星,8星?完美已经不足以诠释这部电影的出色!感动,全程捏着拳头看完。叙事不拖沓,...   \n2019-02-05 11:28:00  在学校看了《流浪地球》的点映!除了电影情节、在现场看到了大刘老师!我更难忘的是郭帆导演在现场...   \n2019-02-07 09:16:00  10分!太棒了!三次掉泪,父爱如山啊。40年前《星球大战》横空出世,好莱坞工业绿魔就此诞生;...   \n2019-02-05 14:56:00  超过预期。《流浪地球》的确开启了中国科幻片和灾难片的新纪元,无论是在哪一坐标中进行比对。虽然...   \n2019-02-06 17:48:00  这场浩浩汤汤的太阳系“春运”燃情又暖心。父子情,战友情,人类与人工智能的情感与理智的抉择,电...   \n2019-02-05 11:01:00  中国终于有自己拿的出手的科幻片了!\\n特效OK,剧情OK,没有大牌明星但全部演技都算得上OK...   \n2019-02-09 02:04:00  从故事层面,本片以刘慈欣科幻小说作为基底,剧本改编非常的扎实,不仅极具想象力,而且也涉及到很...   \n2019-02-05 13:03:00  剧作短板,特效完美,演员优秀,逻辑还是完全经不起推销。地球离太阳最后的距离还不得冻成一个冰球...   \n2019-02-05 14:44:00  前部分虽有不足,但特效是超出预期,后劲较足,到了中后部分有两个地方感动到我,刘培强实现预言,...   \n2019-02-07 05:40:00                                  在电影院看到的预告片,希望早日上映   \n\n                     gender          id             nick  replyCount  score  \\\ntime                                                                          \n2019-02-05 00:02:00       1  1053375466       奇异果Grissom         271     10   \n2019-02-05 11:28:00       2  1052407417  Hope And Legacy         108     10   \n2019-02-07 09:16:00       1  1054132930          CHAOSAY          29     10   \n2019-02-05 14:56:00       1  1053946211              徐若风           4      9   \n2019-02-06 17:48:00       1  1054564832            电影大指南          12     10   \n2019-02-05 11:01:00       0  1053741717      shadownihil          20     10   \n2019-02-09 02:04:00       1  1055541594             娱评天下           9     10   \n2019-02-05 13:03:00       2  1053840774              刘小黛         194      7   \n2019-02-05 14:44:00       2  1053940077        JuliaFanl           6      8   \n2019-02-07 05:40:00       1   134074136              纸牌巫           4      9   \n\n                                   time  upCount      userId  userLevel  \ntime                                                                     \n2019-02-05 00:02:00 2019-02-05 00:02:00     5627   681463650          3  \n2019-02-05 11:28:00 2019-02-05 11:28:00     3838  1812991790          4  \n2019-02-07 09:16:00 2019-02-07 09:16:00      280     9693997          4  \n2019-02-05 14:56:00 2019-02-05 14:56:00      224   116677026          4  \n2019-02-06 17:48:00 2019-02-06 17:48:00      207   272340441          4  \n2019-02-05 11:01:00 2019-02-05 11:01:00      201     8208177          4  \n2019-02-09 02:04:00 2019-02-09 02:04:00      184   172967358          4  \n2019-02-05 13:03:00 2019-02-05 13:03:00      174    12695322          3  \n2019-02-05 14:44:00 2019-02-05 14:44:00      172   227360759          5  \n2019-02-07 05:40:00 2019-02-07 05:40:00      110   418468642          3  "},"execution_count":146,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"for i in data[data['score']>6].nlargest(10, 'upCount')['content']:\n    print(i+'\\n')","execution_count":147,"outputs":[{"name":"stdout","output_type":"stream","text":"为什么没有7星,8星?完美已经不足以诠释这部电影的出色!感动,全程捏着拳头看完。叙事不拖沓,没有美式灾难片的个人英雄主义;宏大,还是宏大,全片充满各种想象;特效,丝毫不输好莱坞进口大片,甚至有些地方有过之而无不及。强烈建议,制作团队赶紧买了三体的版权吧,三年、五年甚至十年,我都等……\n\n在学校看了《流浪地球》的点映!除了电影情节、在现场看到了大刘老师!我更难忘的是郭帆导演在现场讲述的拍摄历程。真的真的太难了、也许有的人会一听国产科幻失去兴趣(真的,我身边哪怕看了很多书的同学、也有的会这样)这也不能怪任何人,毕竟大家看电影也都是想看到好看的、但是对于对科幻有兴趣的朋友,真的来看一看吧。我相信同为科幻迷并为科幻奋斗了这么多年的郭帆老师、绝对值得一张电影票\n    在看后\n太让人惊喜了,紧凑的节奏、多次的剧情反转、\n以及我们自己的价值观(如果是美国电影、大概最后会采用让一部分精英去往新家园,而我们中国的农耕文明注定了我们对土地对地球的情感无法割舍,在流浪地球背后正是这层含义吧\n\n10分!太棒了!三次掉泪,父爱如山啊。40年前《星球大战》横空出世,好莱坞工业绿魔就此诞生;而在40年后,《流浪地球》的上映,标志着中国科幻片就此诞生了。稳稳的拿下中国科幻片里程碑的称号了。再渺小的生命, 只要心有定力, 终会达到目的。要有牺牲小我,完成大我的勇气,小人物也是能拯救世界的。\n\n超过预期。《流浪地球》的确开启了中国科幻片和灾难片的新纪元,无论是在哪一坐标中进行比对。虽然我们并非是一直都没有所谓的科幻电影,但其中的大多都不是工业化、硬科幻的路子。\n《流浪地球》则在概念和执行上都达到了这一标准,特效技术、工整剧作、演员所合力营造出的氛围都很对。它代表的,是华语科幻电影的一个“关键转折点”。\n从原著角度而言,这是一个带着孤独感的故事。电影采用了小说中的整体设定,但故事与人物有了新的创造,且塑造了很好的主题,即对乡土情结的回归和牺牲精神。\n\n这场浩浩汤汤的太阳系“春运”燃情又暖心。父子情,战友情,人类与人工智能的情感与理智的抉择,电影赋予了刘慈欣原著更多没有的元素。张弛有度的节奏,两个小时的时间,心情随着剧情起伏。更别说激动人心,艳惊四座的特效画面了。看过《流浪地球》,我们终于可以理直气壮的说:国产电影终于有了真正的硬核科幻片!\n\n中国终于有自己拿的出手的科幻片了!\n特效OK,剧情OK,没有大牌明星但全部演技都算得上OK!\n有靠谱的团队我们还是可以拿的出手科幻片的!\n\n从故事层面,本片以刘慈欣科幻小说作为基底,剧本改编非常的扎实,不仅极具想象力,而且也涉及到很多专业知识,科技含量极高,算是对太空知识的普及,尤其是那几句“再见,太阳系”,透露出一种科幻电影难得的悲壮感、史诗气质。\n从视听效果上,本片也是足以比肩好莱坞科幻大片的饕餮盛宴。\n地球表面的天寒地冻,高耸入云的地球推进器,在冰天雪地行进的巨型卡车,太空中宏伟壮观的空间站,被冰雪覆盖的东方明珠塔,高楼电梯的惊险救援,地球大气被木星捕获的炫美一幕,还有最后点燃木星的震撼一刻……这些精彩炫目的场面,此前只能在国外大制作才能得见,如今我们中国电影也能完美呈现,这一跨越式的进步当然让观众心生自豪。\n\n剧作短板,特效完美,演员优秀,逻辑还是完全经不起推销。地球离太阳最后的距离还不得冻成一个冰球?一个女孩的中学获奖感言感动全人类,几个毛孩拯救地球,中国宇航员牺牲自我其他国家的都是休眠待毙,其实主题和战狼一模一样。原小说就是个体量不充沛的概念框架,改编影像困难。当然对整体工业水准有推进,什么时候能消除国别差异,关注个体,展露基本人性原生态,再搭配科幻质感,并且还能上映。\n\n前部分虽有不足,但特效是超出预期,后劲较足,到了中后部分有两个地方感动到我,刘培强实现预言,其次是王磊队长说出命令的瞬间。希望是什么?在绝境中不放弃任何一种可能,与其等待死亡,不如拼死一搏!长大又是什么?与家人共同经历之后理解彼此,打开心结。这次拯救地球集结了大家的力量,也见证了刘启的成长。流浪地球计划,让地球不再流浪。\n\n在电影院看到的预告片,希望早日上映\n\n"}]},{"metadata":{},"cell_type":"markdown","source":"##### 4. 低分的评价理由是什么?"},{"metadata":{"trusted":false},"cell_type":"code","source":"# 低分的评价\nplot_word_cloud(data=data[data['score']<5], swords=swords)","execution_count":148,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":148,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"data[data['score']<5].nlargest(10, 'upCount')","execution_count":149,"outputs":[{"data":{"text/html":"
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 contentgenderidnickreplyCountscoretimeupCountuserIduserLevel
time          
2019-02-06 23:47:00 也许进入地下没有了阳光,人们的内心就趋向黑暗!小太妹一样的妹妹人设,不知所谓的混血?没有缘由... 1 1054591874 逗逼老爸 67 2 2019-02-06 23:47:00 99 163219720 4
2019-02-07 23:00:00 太多人给这部片高分了,我必须给低分把这部电影的评分拉低,因为他不值得9点多分,顶多值6.5分... 1 1055063063 杨某X 42 2 2019-02-07 23:00:00 95 85500030 1
2019-02-08 04:14:00 电影就是电影不要嘈杂着其他因素,就电影本质来说,这电影特效,大场面,做的让我赞叹不已,非常的... 1 1055119853 一抹晨曦784 21 3 2019-02-08 04:14:00 75 156486326 2
2019-02-08 01:42:00 情感细节0分,演员演技0分,特别是17岁的那两个孩子,真是醉了!从前烂到尾,bug多如牛毛。... 1 1055075620 秭归小武 25 1 2019-02-08 01:42:00 75 70329844 1
2019-02-08 19:51:00 没逻辑没智商没演技超尴尬!最后不作不死的小女生用一篇激情澎湃的即兴小学生作文感动了全球救援队... 1 1055518330 威仔 22 1 2019-02-08 19:51:00 74 419136037 3
2019-02-08 02:18:00 我想问问你们摸着良心说是真的觉得好看吗?反正有不少人跟我一起提前离场就是了。 0 1055083535 弧鸽 38 1 2019-02-08 02:18:00 74 1008203632 2
2019-02-06 06:16:00 理性分析,我是科幻迷,我对这部电影的科幻背景没有一点意见,特效当然是进步了,但用力过度,剧情... 1 1054184286 Refine? 97 4 2019-02-06 06:16:00 72 1053444729 2
2019-02-07 12:18:00 看过好后悔,好奇怪怎么会有这么多好评?真的不太好看,主演真心是败笔!几个年轻孩子根本撑不起这... 2 1054680274 淡然1547 48 3 2019-02-07 12:18:00 70 45444833 2
2019-02-10 10:40:00 这么烂的电影居然这么高评分,可见水军力量可以,还有就是随波逐流的那些不懂电影的人给个特效的赞... 1 1055061178 栄栄栄轩 25 1 2019-02-10 10:40:00 69 48197366 2
2019-02-08 02:29:00 垃圾,评分是假的 0 1055090859 三高人生 26 1 2019-02-08 02:29:00 68 1021605168 3
\n
","text/plain":"                                                               content  \\\ntime                                                                     \n2019-02-06 23:47:00  也许进入地下没有了阳光,人们的内心就趋向黑暗!小太妹一样的妹妹人设,不知所谓的混血?没有缘由...   \n2019-02-07 23:00:00  太多人给这部片高分了,我必须给低分把这部电影的评分拉低,因为他不值得9点多分,顶多值6.5分...   \n2019-02-08 04:14:00  电影就是电影不要嘈杂着其他因素,就电影本质来说,这电影特效,大场面,做的让我赞叹不已,非常的...   \n2019-02-08 01:42:00  情感细节0分,演员演技0分,特别是17岁的那两个孩子,真是醉了!从前烂到尾,bug多如牛毛。...   \n2019-02-08 19:51:00  没逻辑没智商没演技超尴尬!最后不作不死的小女生用一篇激情澎湃的即兴小学生作文感动了全球救援队...   \n2019-02-08 02:18:00             我想问问你们摸着良心说是真的觉得好看吗?反正有不少人跟我一起提前离场就是了。   \n2019-02-06 06:16:00  理性分析,我是科幻迷,我对这部电影的科幻背景没有一点意见,特效当然是进步了,但用力过度,剧情...   \n2019-02-07 12:18:00  看过好后悔,好奇怪怎么会有这么多好评?真的不太好看,主演真心是败笔!几个年轻孩子根本撑不起这...   \n2019-02-10 10:40:00  这么烂的电影居然这么高评分,可见水军力量可以,还有就是随波逐流的那些不懂电影的人给个特效的赞...   \n2019-02-08 02:29:00                                           垃圾,评分是假的   \n\n                     gender          id     nick  replyCount  score  \\\ntime                                                                  \n2019-02-06 23:47:00       1  1054591874     逗逼老爸          67      2   \n2019-02-07 23:00:00       1  1055063063      杨某X          42      2   \n2019-02-08 04:14:00       1  1055119853  一抹晨曦784          21      3   \n2019-02-08 01:42:00       1  1055075620     秭归小武          25      1   \n2019-02-08 19:51:00       1  1055518330       威仔          22      1   \n2019-02-08 02:18:00       0  1055083535       弧鸽          38      1   \n2019-02-06 06:16:00       1  1054184286  Refine?          97      4   \n2019-02-07 12:18:00       2  1054680274   淡然1547          48      3   \n2019-02-10 10:40:00       1  1055061178     栄栄栄轩          25      1   \n2019-02-08 02:29:00       0  1055090859     三高人生          26      1   \n\n                                   time  upCount      userId  userLevel  \ntime                                                                     \n2019-02-06 23:47:00 2019-02-06 23:47:00       99   163219720          4  \n2019-02-07 23:00:00 2019-02-07 23:00:00       95    85500030          1  \n2019-02-08 04:14:00 2019-02-08 04:14:00       75   156486326          2  \n2019-02-08 01:42:00 2019-02-08 01:42:00       75    70329844          1  \n2019-02-08 19:51:00 2019-02-08 19:51:00       74   419136037          3  \n2019-02-08 02:18:00 2019-02-08 02:18:00       74  1008203632          2  \n2019-02-06 06:16:00 2019-02-06 06:16:00       72  1053444729          2  \n2019-02-07 12:18:00 2019-02-07 12:18:00       70    45444833          2  \n2019-02-10 10:40:00 2019-02-10 10:40:00       69    48197366          2  \n2019-02-08 02:29:00 2019-02-08 02:29:00       68  1021605168          3  "},"execution_count":149,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"for i in data[data['score']<5].nlargest(10, 'upCount')['content']:\n    print(i+'\\n')","execution_count":150,"outputs":[{"name":"stdout","output_type":"stream","text":"也许进入地下没有了阳光,人们的内心就趋向黑暗!小太妹一样的妹妹人设,不知所谓的混血?没有缘由的痞帅(真心不帅),地震只顾自己逃亡不让救人的姥爷,吐满自己的头盔又抢别人头盔的救援队?为了亲情强行不进入休眠的爸爸,为了不再死人打坏火石的女队员……不学无术的少年比世界所有科学家都厉害,看来地球就剩下牛顿的弟弟牛逼啦!整部片子充满了一种戾气!为啥中国拯救世界就非得用这样的人物支撑人设?为了后面的反转?虽然特效还行,真心不好看!希望不要影响大家的观影心情!\n\n太多人给这部片高分了,我必须给低分把这部电影的评分拉低,因为他不值得9点多分,顶多值6.5分样子,在国产片里面算不错的,剧情烂,东拉西扯的,地球你造发动机推动脱离太阳引力我也忍了,点燃木星就太扯了,点燃木星瞬间推动地球逃脱木星引力,那么大的冲击力地球生物不死绝鬼都不信!还有作为灾难科幻片,震撼人心的灾难场景基本没有,地球停海啸爆发,我一直在期待灾难爆发时刻人类逃亡的场景,但是从头到尾都没有!走到哪里都挂着国旗,又是打爱国情怀,很符合吴京蹭爱国热度的习惯,反正不会错,但是我就觉得很作!恶心!\n\n电影就是电影不要嘈杂着其他因素,就电影本质来说,这电影特效,大场面,做的让我赞叹不已,非常的有气势,但是演员演技实在捉急,特别是两个主角,男主人设叛逆性格太过了,女主那段演讲是本片的最大败笔,看完那段演讲让我尴尬的有种跑出电影院的冲动,每个人物死掉都会莫名其妙的来段演讲煽情戏,编剧真的是尬王!总的来说,网上给予这片子得评分没有很客观,相比较国外科幻大片,流浪地球有进步,但是还差得远!电影就是电影跟爱不爱国无关,请不要道德绑架!\n\n情感细节0分,演员演技0分,特别是17岁的那两个孩子,真是醉了!从前烂到尾,bug多如牛毛。无数个人在玩手机。中国科幻电影需要学习的地方还有太多太多。\n\n以后看电影不能再去豆瓣上看评分啦,前期的水军真多!\n\n没逻辑没智商没演技超尴尬!最后不作不死的小女生用一篇激情澎湃的即兴小学生作文感动了全球救援队!成功拯救了地球!这导演跟编剧是小学没毕业吧!\n\n我想问问你们摸着良心说是真的觉得好看吗?反正有不少人跟我一起提前离场就是了。\n\n理性分析,我是科幻迷,我对这部电影的科幻背景没有一点意见,特效当然是进步了,但用力过度,剧情从引爆木星那段就开始崩了,在此之前一切都称得上非常不错,在引爆木星剧情开始前,我甚至以为电影结束了,结果又塞进来一大段,我就耐着性子继续看,结果越来越崩,各种雷点和莫名其妙的煽情点,还可以忍忍,到了主角坠崖我以为结束了,这时候电影在我心里值7.5分,结果!又塞进去不长不短的一段莫名其妙的典型喜剧式结尾,主角头盔破了,暴露在缺氧和超低温环境下不知道多久,居然活蹦乱跳?这是欺负谁的智商呢?电影在这里彻底崩掉,如果说引爆木星之前,这部电影完全比肩世界其他任何科幻片,引爆木星以后,就完全沦落为国产轻喜剧。\n\n看过好后悔,好奇怪怎么会有这么多好评?真的不太好看,主演真心是败笔!几个年轻孩子根本撑不起这样的巨作!最终竟然是啥都不会的年轻小孩拯救地球?假的要死!那么多高科技产品,没经过任何训练怎么可能会操作?专业救援队倒是什么都不懂,只会干点出力的事!导演脑袋有坑吧!\n还有主演朵朵,都不知道她在剧里有什么用?只为煽情吗?这么好的大片整个无用的人煽情太毁剧了!\n除了特效没有看点!不是黑粉,个人感受,不喜勿喷!\n\n这么烂的电影居然这么高评分,可见水军力量可以,还有就是随波逐流的那些不懂电影的人给个特效的赞吧,一个围绕家庭亲情为主线拯救地球的故事,居然靠一个自恃清高演技一般的小孩为主,全球科学家全球人都没有一个小孩厉害,国内科幻片还是有很大进步空间,不是我不支持国产电影而是这个电影本人感觉没有逻辑没有足够的理论知识卖个特效骗个票房,希望还是多用心做电影吧…\n\n垃圾,评分是假的\n\n"}]},{"metadata":{},"cell_type":"markdown","source":"##### 5. 低分的人群有哪些特征?(性别、等级)"},{"metadata":{"trusted":false},"cell_type":"code","source":"# 总体的性别比例\ngender_total = data['gender'].value_counts()\nbar = Bar(\"《流浪地球》观众性别\", width=700)\nbar.add(\"\", ['未知', '男', '女'], gender_total.values, is_stack=True, is_label_show=True,\n       bar_category_gap='60%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nbar","execution_count":172,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":172,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"gender_total/gender_total.sum()*100","execution_count":175,"outputs":[{"data":{"text/plain":"0    43.298889\n1    36.886333\n2    19.814779\nName: gender, dtype: float64"},"execution_count":175,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 低分的性别比例\ngender_low = data.loc[data['score']<5, 'gender'].value_counts()\nbar = Bar(\"《流浪地球》低分评论观众性别\", width=700)\nbar.add(\"\", ['未知'zh, '男', '女'], gender_low.values, is_stack=True, is_label_show=True,\n       bar_category_gap='60%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nbar","execution_count":185,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":185,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"gender_low/gender_low.sum()*100","execution_count":179,"outputs":[{"data":{"text/plain":"0    42.650215\n1    37.821888\n2    19.527897\nName: gender, dtype: float64"},"execution_count":179,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 总体的等级比例\nlevel_total = data['userLevel'].value_counts().sort_index()\nbar = Bar(\"《流浪地球》观众等级\", width=700)\nbar.add(\"\", level_total.index, level_total.values, is_stack=True, is_label_show=True,\n       bar_category_gap='40%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nbar","execution_count":187,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":187,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 低分评论的观众等级比例\nlevel_low = data.loc[data['score']<5, 'userLevel'].value_counts().sort_index()\nbar = Bar(\"《流浪地球》低分评论的观众等级\", width=700)\nbar.add(\"\", level_low.index, level_low.values, is_stack=True, is_label_show=True,\n       bar_category_gap='40%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nbar","execution_count":188,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":188,"metadata":{},"output_type":"execute_result"}]},{"metadata":{},"cell_type":"markdown","source":"##### 6. 高低分跟哪位演员有关?"},{"metadata":{"trusted":false},"cell_type":"code","source":"mapping = {'liucixin':'刘慈欣|大刘', 'guofan':'郭帆', 'quchuxiao':'屈楚萧|刘启|户口', 'wujing':'吴京|刘培强', \n           'liguangjie':'李光洁|王磊', 'wumengda':'吴孟达|达叔|韩子昂', 'zhaojinmai':'赵今麦|韩朵朵'}\nfor key, value in mapping.items():\n    data[key] = data['content'].str.contains(value)","execution_count":198,"outputs":[]},{"metadata":{"trusted":false},"cell_type":"code","source":"# 总体提及次数\nstaff_count = pd.Series({key: data.loc[data[key], 'score'].count() for key in mapping.keys()}).sort_values()\nstaff_count","execution_count":204,"outputs":[{"data":{"text/plain":"liguangjie     171\nguofan         272\nzhaojinmai     377\nwumengda       477\nquchuxiao      833\nliucixin      3122\nwujing        5351\ndtype: int64"},"execution_count":204,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"bar = Bar(\"《流浪地球》演职员总体提及次数\", width=700)\nbar.add(\"\", ['李光洁','郭帆','赵今麦','吴孟达','屈楚萧','刘慈欣','吴京'], staff_count.values, is_stack=True, is_label_show=True,\n       bar_category_gap='60%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nbar","execution_count":205,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":205,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"average_score = pd.Series({key: data.loc[data[key], 'score'].mean() for key in mapping.keys()}).sort_values()\naverage_score","execution_count":215,"outputs":[{"data":{"text/plain":"zhaojinmai    8.636605\nwumengda      8.779874\nwujing        9.003738\nquchuxiao     9.018007\nliguangjie    9.134503\nliucixin      9.480782\nguofan        9.658088\ndtype: float64"},"execution_count":215,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"bar = Bar(\"《流浪地球》演职员平均分\", width=700)\nbar.add(\"\", ['赵今麦','吴孟达','吴京','屈楚萧','李光洁','刘慈欣','郭帆'], np.round(average_score.values,2), is_stack=True, is_label_show=True,\n       bar_category_gap='60%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nbar","execution_count":219,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":219,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"staff_count_low = pd.Series({key: data.loc[data[key]&(data['score']<5), 'score'].count() for key in mapping.keys()}).sort_values()\nstaff_count_low","execution_count":220,"outputs":[{"data":{"text/plain":"guofan          3\nliguangjie      4\nzhaojinmai     14\nwumengda       29\nquchuxiao      30\nliucixin       36\nwujing        305\ndtype: int64"},"execution_count":220,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"staff_count_pct = np.round(staff_count_low/staff_count*100, 2).sort_values()\nstaff_count_pct","execution_count":231,"outputs":[{"data":{"text/plain":"guofan        1.10\nliucixin      1.15\nliguangjie    2.34\nquchuxiao     3.60\nzhaojinmai    3.71\nwujing        5.70\nwumengda      6.08\ndtype: float64"},"execution_count":231,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"bar = Bar(\"《流浪地球》演职员低分评论提及百分比\", width=700)\nbar.add(\"\", ['郭帆','刘慈欣','李光洁','屈楚萧','赵今麦','吴京','吴孟达'], staff_count_pct.values, is_stack=True, is_label_show=True,\n       bar_category_gap='60%', label_color = ['#130f40'],\n       legend_text_size=18,xaxis_label_textsize=18,yaxis_label_textsize=18)\nbar","execution_count":233,"outputs":[{"data":{"text/html":"\n
 
\n\n\n\n","text/plain":""},"execution_count":233,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"data[data['wumengda']&(data['score']<5)].nlargest(5, 'upCount')","execution_count":229,"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
 contentgenderidnickreplyCountscoretimeupCountuserIduserLevelliucixinguofanquchuxiaowujingliguangjiewumengdazhaojinmai
time                 
2019-02-05 14:11:00 可惜了60+大洋,达叔的演技是唯一的亮点,小鲜肉们稚嫩且乏味的演技(约等于0.1)好无聊,和... 1 1053902705 熊晓军[德恒律师] 13 1 2019-02-05 14:11:00 42 1154499307 5 False False False False False True False
2019-02-11 02:14:00 真的,这一分我都是给的吴孟达和雷佳音的,剩下的真的不能多给了,电影,最基本的是故事情节,一味... 2 1056402038 林艾G 52 1 2019-02-11 02:14:00 40 63455639 3 False False False False False True False
2019-02-08 04:46:00 主人公太扯了,三观不正,净瞎拍,拿着吴京吴孟达做幌子,真浪费我一百大洋。这片子也就骗骗小孩能... 1 1055139154 博爱永恒 11 3 2019-02-08 04:46:00 39 53086905 2 False False False True False True False
2019-02-09 04:33:00 也别给半星了,剧情太烂,情节不好,故事不合理,尤其最后爆炸,还能爆炸5000公里,飞船都让你... 1 1055580599 闹闹先生丶丶 18 2 2019-02-09 04:33:00 31 173755020 3 False False False False False True False
2019-02-07 10:19:00 台词设定太尴尬,强行煽情,那个外国人设定最恶心,强行设定的人物,吴京,吴孟达只是客串,还有那... 0 1054828448 A_啊杰 7 1 2019-02-07 10:19:00 28 1033874459 4 False False False True False True False
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","text/plain":"                                                               content  \\\ntime                                                                     \n2019-02-05 14:11:00  可惜了60+大洋,达叔的演技是唯一的亮点,小鲜肉们稚嫩且乏味的演技(约等于0.1)好无聊,和...   \n2019-02-11 02:14:00  真的,这一分我都是给的吴孟达和雷佳音的,剩下的真的不能多给了,电影,最基本的是故事情节,一味...   \n2019-02-08 04:46:00  主人公太扯了,三观不正,净瞎拍,拿着吴京吴孟达做幌子,真浪费我一百大洋。这片子也就骗骗小孩能...   \n2019-02-09 04:33:00  也别给半星了,剧情太烂,情节不好,故事不合理,尤其最后爆炸,还能爆炸5000公里,飞船都让你...   \n2019-02-07 10:19:00  台词设定太尴尬,强行煽情,那个外国人设定最恶心,强行设定的人物,吴京,吴孟达只是客串,还有那...   \n\n                     gender          id       nick  replyCount  score  \\\ntime                                                                    \n2019-02-05 14:11:00       1  1053902705  熊晓军[德恒律师]          13      1   \n2019-02-11 02:14:00       2  1056402038        林艾G          52      1   \n2019-02-08 04:46:00       1  1055139154       博爱永恒          11      3   \n2019-02-09 04:33:00       1  1055580599     闹闹先生丶丶          18      2   \n2019-02-07 10:19:00       0  1054828448       A_啊杰           7      1   \n\n                                   time  upCount      userId  userLevel  \\\ntime                                                                      \n2019-02-05 14:11:00 2019-02-05 14:11:00       42  1154499307          5   \n2019-02-11 02:14:00 2019-02-11 02:14:00       40    63455639          3   \n2019-02-08 04:46:00 2019-02-08 04:46:00       39    53086905          2   \n2019-02-09 04:33:00 2019-02-09 04:33:00       31   173755020          3   \n2019-02-07 10:19:00 2019-02-07 10:19:00       28  1033874459          4   \n\n                     liucixin  guofan  quchuxiao  wujing  liguangjie  \\\ntime                                                                   \n2019-02-05 14:11:00     False   False      False   False       False   \n2019-02-11 02:14:00     False   False      False   False       False   \n2019-02-08 04:46:00     False   False      False    True       False   \n2019-02-09 04:33:00     False   False      False   False       False   \n2019-02-07 10:19:00     False   False      False    True       False   \n\n                     wumengda  zhaojinmai  \ntime                                       \n2019-02-05 14:11:00      True       False  \n2019-02-11 02:14:00      True       False  \n2019-02-08 04:46:00      True       False  \n2019-02-09 04:33:00      True       False  \n2019-02-07 10:19:00      True       False  "},"execution_count":229,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"for i in data[data['wumengda']&(data['score']<5)].nlargest(5, 'upCount')['content']:\n    print(i+'\\n')","execution_count":236,"outputs":[{"name":"stdout","output_type":"stream","text":"可惜了60+大洋,达叔的演技是唯一的亮点,小鲜肉们稚嫩且乏味的演技(约等于0.1)好无聊,和看昨晚的春晚感觉差不多,好像喊得很大声,哭得很撕心,但就是没内容,演得太空洞。催泪不够真诚,搞笑不够认真,细节太过毛糙,整个就是一部被制作,为制作而制作的视听片,片尾曲让人无力吐槽。一个人的初一良辰就这么被拱了。\n\n真的,这一分我都是给的吴孟达和雷佳音的,剩下的真的不能多给了,电影,最基本的是故事情节,一味强调特技多么好多么好,去看科技展不就好了?真的是浪费了80块的电影票,毫无情节可言,一味地个人英雄主义,强行煽情,把观众得智商按在地上摩擦,这样的烂片是买了水军吧……垃圾!\n\n主人公太扯了,三观不正,净瞎拍,拿着吴京吴孟达做幌子,真浪费我一百大洋。这片子也就骗骗小孩能行,真的不敢恭维。\n\n也别给半星了,剧情太烂,情节不好,故事不合理,尤其最后爆炸,还能爆炸5000公里,飞船都让你开这么快了,还用的着点燃么?直接开进木星不就好了,飞船后面喷的不是火啊?送达叔一张票,卖战狼一份情,这电影真不行\n\n台词设定太尴尬,强行煽情,那个外国人设定最恶心,强行设定的人物,吴京,吴孟达只是客串,还有那人物设定,太牵强,不知道9.3分怎么来的\n\n"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"data[data['wujing']&(data['score']<5)].nlargest(5, 'upCount')","execution_count":234,"outputs":[{"data":{"text/html":"
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 contentgenderidnickreplyCountscoretimeupCountuserIduserLevelliucixinguofanquchuxiaowujingliguangjiewumengdazhaojinmai
time                 
2019-02-07 23:00:00 太多人给这部片高分了,我必须给低分把这部电影的评分拉低,因为他不值得9点多分,顶多值6.5分... 1 1055063063 杨某X 42 2 2019-02-07 23:00:00 95 85500030 1 False False False True False False False
2019-02-06 17:21:00 逻辑非常不严密,既然定位是科幻片,起码的逻辑得有吧?\\n1.一个0.7级宇宙文明等级的星球,... 1 1054564334 团拼丶小王子 108 1 2019-02-06 17:21:00 58 8675410 3 False False False True False False False
2019-02-07 03:59:00 就这样吧,特效还行,科幻部分不做评价,就人物刻画来讲已经槽点满满了!刘启就是个狂躁症患者,什... 2 1054646769 CpJ26143934 35 4 2019-02-07 03:59:00 53 91570358 2 False False True True False False True
2019-02-07 03:22:00 开头以为是国产科幻大片,气象不凡,道具方面下了不少功夫,某些场景直追好莱坞。整体上离好莱坞还... 1 1054637652 meituanchzhh 33 1 2019-02-07 03:22:00 49 34052306 3 False False False True False False False
2019-02-05 09:17:00 什么玩意儿,发动机和石头砸下来的声音从头震到尾,演技拙劣的儿女情长的片段令人作呕,吴京一副大... 0 1053645922 westbrookFMVP 36 1 2019-02-05 09:17:00 48 779520607 2 False False False True False False False
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","text/plain":"                                                               content  \\\ntime                                                                     \n2019-02-07 23:00:00  太多人给这部片高分了,我必须给低分把这部电影的评分拉低,因为他不值得9点多分,顶多值6.5分...   \n2019-02-06 17:21:00  逻辑非常不严密,既然定位是科幻片,起码的逻辑得有吧?\\n1.一个0.7级宇宙文明等级的星球,...   \n2019-02-07 03:59:00  就这样吧,特效还行,科幻部分不做评价,就人物刻画来讲已经槽点满满了!刘启就是个狂躁症患者,什...   \n2019-02-07 03:22:00  开头以为是国产科幻大片,气象不凡,道具方面下了不少功夫,某些场景直追好莱坞。整体上离好莱坞还...   \n2019-02-05 09:17:00  什么玩意儿,发动机和石头砸下来的声音从头震到尾,演技拙劣的儿女情长的片段令人作呕,吴京一副大...   \n\n                     gender          id           nick  replyCount  score  \\\ntime                                                                        \n2019-02-07 23:00:00       1  1055063063            杨某X          42      2   \n2019-02-06 17:21:00       1  1054564334         团拼丶小王子         108      1   \n2019-02-07 03:59:00       2  1054646769    CpJ26143934          35      4   \n2019-02-07 03:22:00       1  1054637652   meituanchzhh          33      1   \n2019-02-05 09:17:00       0  1053645922  westbrookFMVP          36      1   \n\n                                   time  upCount     userId  userLevel  \\\ntime                                                                     \n2019-02-07 23:00:00 2019-02-07 23:00:00       95   85500030          1   \n2019-02-06 17:21:00 2019-02-06 17:21:00       58    8675410          3   \n2019-02-07 03:59:00 2019-02-07 03:59:00       53   91570358          2   \n2019-02-07 03:22:00 2019-02-07 03:22:00       49   34052306          3   \n2019-02-05 09:17:00 2019-02-05 09:17:00       48  779520607          2   \n\n                     liucixin  guofan  quchuxiao  wujing  liguangjie  \\\ntime                                                                   \n2019-02-07 23:00:00     False   False      False    True       False   \n2019-02-06 17:21:00     False   False      False    True       False   \n2019-02-07 03:59:00     False   False       True    True       False   \n2019-02-07 03:22:00     False   False      False    True       False   \n2019-02-05 09:17:00     False   False      False    True       False   \n\n                     wumengda  zhaojinmai  \ntime                                       \n2019-02-07 23:00:00     False       False  \n2019-02-06 17:21:00     False       False  \n2019-02-07 03:59:00     False        True  \n2019-02-07 03:22:00     False       False  \n2019-02-05 09:17:00     False       False  "},"execution_count":234,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"for i in data[data['wujing']&(data['score']<5)].nlargest(5, 'upCount')['content']:\n    print(i+'\\n')","execution_count":235,"outputs":[{"name":"stdout","output_type":"stream","text":"太多人给这部片高分了,我必须给低分把这部电影的评分拉低,因为他不值得9点多分,顶多值6.5分样子,在国产片里面算不错的,剧情烂,东拉西扯的,地球你造发动机推动脱离太阳引力我也忍了,点燃木星就太扯了,点燃木星瞬间推动地球逃脱木星引力,那么大的冲击力地球生物不死绝鬼都不信!还有作为灾难科幻片,震撼人心的灾难场景基本没有,地球停海啸爆发,我一直在期待灾难爆发时刻人类逃亡的场景,但是从头到尾都没有!走到哪里都挂着国旗,又是打爱国情怀,很符合吴京蹭爱国热度的习惯,反正不会错,但是我就觉得很作!恶心!\n\n逻辑非常不严密,既然定位是科幻片,起码的逻辑得有吧?\n1.一个0.7级宇宙文明等级的星球,自己这块地的资源分配都没整明白,是哪来的能量去推着地球改变行星轨迹?\n2.点燃木星这脑洞是有多大?几十亿年有多少陨石彗星冲击都没点燃,你突发奇想放个火就能点燃了?全是氢气,是怎么点燃的?就这种气体混合比,怎么点燃的?麻烦把化学反应方程式告诉我一下。还不如说丢个炮仗上去炸一下,起码炮仗还能在无氧的环境下燃烧爆炸。\n3.就吴京这种个人英雄主义的演员拿来演这种格局庞大的科幻电影合适吗?单说人物设定,就这种人的军衔是怎么给的?是怎么选为航天员的?有没有做过心理测试?有没有做过性格评估?人类的命运最后是堵出来的?\n\n就这样吧,特效还行,科幻部分不做评价,就人物刻画来讲已经槽点满满了!刘启就是个狂躁症患者,什么都是别人的错,对着姥爷一口一个老东西,姥爷临死也没改口;韩朵朵就是一**少女,紧要关头还声情并茂朗读小作文;刘培强是我要救儿子……以为儿子死了:好,我放弃了,我听moss的回去休眠……哦!儿子没死,太好了,我要想办法,一定要救地球……🙄️🙄️🙄️\n\n开头以为是国产科幻大片,气象不凡,道具方面下了不少功夫,某些场景直追好莱坞。整体上离好莱坞还是差半个世纪。1⃣️演员。格式化表演,看不出“人”性内容,几处人物牺牲逻辑性和共鸣性不强,尤其吴京最后牺牲前一段烈士般台词,沿习战狼做派,略显矫情。2⃣️布景。感觉一直都是漫天飞雪、错杂纷乱,缺乏变化。整体风格压抑,没有情景沉入感、带入感。\n\n什么玩意儿,发动机和石头砸下来的声音从头震到尾,演技拙劣的儿女情长的片段令人作呕,吴京一副大义凛然的样子太过难受,什么中国第一部科幻,情节稀烂,特效主要靠音效,加上刻意塑造的中国式英雄,一分没得说\n\n"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"data[data['zhaojinmai']&(data['score']<5)].nlargest(5, 'upCount')","execution_count":237,"outputs":[{"data":{"text/html":"
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 contentgenderidnickreplyCountscoretimeupCountuserIduserLevelliucixinguofanquchuxiaowujingliguangjiewumengdazhaojinmai
time                 
2019-02-07 03:59:00 就这样吧,特效还行,科幻部分不做评价,就人物刻画来讲已经槽点满满了!刘启就是个狂躁症患者,什... 2 1054646769 CpJ26143934 35 4 2019-02-07 03:59:00 53 91570358 2 False False True True False False True
2019-02-06 15:46:00 刘慈欣《流浪地球》据说是硬科幻,设定感觉可以出一个系列,可导演和编剧讲故事的能力都差强人意,... 2 1054533126 pSU598729902 23 1 2019-02-06 15:46:00 35 1054238164 3 True False False False False False True
2019-02-05 05:53:00 能更尴尬么?韩朵朵尴尬,刘启尴尬,演技尴尬,剧情尴尬,MOSS 反转尴尬,除了三体 再也不看... 0 1053496256 刀客谭 21 1 2019-02-05 05:53:00 33 1010202977 3 True False True False False False True
2019-02-10 12:56:00 不感动啊…也没有满场子哭泣泣的!不过制作看得出来很精致,但独白很一般!韩朵朵喊救援时候太拖拉... 2 1056241443 崔家内小谁 0 4 2019-02-10 12:56:00 12 199632141 4 False False False False False False True
2019-02-10 16:33:00 男权主义太重了,我真的十分讨厌吧危机关头,把女生演绎的像个傻子,赖赖唧唧的,拖后腿,最后几分... 2 1055645215 @ 3 3 2019-02-10 16:33:00 2 1045118082 2 False False False False False False True
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","text/plain":"                                                               content  \\\ntime                                                                     \n2019-02-07 03:59:00  就这样吧,特效还行,科幻部分不做评价,就人物刻画来讲已经槽点满满了!刘启就是个狂躁症患者,什...   \n2019-02-06 15:46:00  刘慈欣《流浪地球》据说是硬科幻,设定感觉可以出一个系列,可导演和编剧讲故事的能力都差强人意,...   \n2019-02-05 05:53:00  能更尴尬么?韩朵朵尴尬,刘启尴尬,演技尴尬,剧情尴尬,MOSS 反转尴尬,除了三体 再也不看...   \n2019-02-10 12:56:00  不感动啊…也没有满场子哭泣泣的!不过制作看得出来很精致,但独白很一般!韩朵朵喊救援时候太拖拉...   \n2019-02-10 16:33:00  男权主义太重了,我真的十分讨厌吧危机关头,把女生演绎的像个傻子,赖赖唧唧的,拖后腿,最后几分...   \n\n                     gender          id          nick  replyCount  score  \\\ntime                                                                       \n2019-02-07 03:59:00       2  1054646769   CpJ26143934          35      4   \n2019-02-06 15:46:00       2  1054533126  pSU598729902          23      1   \n2019-02-05 05:53:00       0  1053496256           刀客谭          21      1   \n2019-02-10 12:56:00       2  1056241443         崔家内小谁           0      4   \n2019-02-10 16:33:00       2  1055645215             @           3      3   \n\n                                   time  upCount      userId  userLevel  \\\ntime                                                                      \n2019-02-07 03:59:00 2019-02-07 03:59:00       53    91570358          2   \n2019-02-06 15:46:00 2019-02-06 15:46:00       35  1054238164          3   \n2019-02-05 05:53:00 2019-02-05 05:53:00       33  1010202977          3   \n2019-02-10 12:56:00 2019-02-10 12:56:00       12   199632141          4   \n2019-02-10 16:33:00 2019-02-10 16:33:00        2  1045118082          2   \n\n                     liucixin  guofan  quchuxiao  wujing  liguangjie  \\\ntime                                                                   \n2019-02-07 03:59:00     False   False       True    True       False   \n2019-02-06 15:46:00      True   False      False   False       False   \n2019-02-05 05:53:00      True   False       True   False       False   \n2019-02-10 12:56:00     False   False      False   False       False   \n2019-02-10 16:33:00     False   False      False   False       False   \n\n                     wumengda  zhaojinmai  \ntime                                       \n2019-02-07 03:59:00     False        True  \n2019-02-06 15:46:00     False        True  \n2019-02-05 05:53:00     False        True  \n2019-02-10 12:56:00     False        True  \n2019-02-10 16:33:00     False        True  "},"execution_count":237,"metadata":{},"output_type":"execute_result"}]},{"metadata":{"trusted":false},"cell_type":"code","source":"for i in data[data['zhaojinmai']&(data['score']<5)].nlargest(5, 'upCount')['content']:\n    print(i+'\\n')","execution_count":238,"outputs":[{"name":"stdout","output_type":"stream","text":"就这样吧,特效还行,科幻部分不做评价,就人物刻画来讲已经槽点满满了!刘启就是个狂躁症患者,什么都是别人的错,对着姥爷一口一个老东西,姥爷临死也没改口;韩朵朵就是一**少女,紧要关头还声情并茂朗读小作文;刘培强是我要救儿子……以为儿子死了:好,我放弃了,我听moss的回去休眠……哦!儿子没死,太好了,我要想办法,一定要救地球……🙄️🙄️🙄️\n\n刘慈欣《流浪地球》据说是硬科幻,设定感觉可以出一个系列,可导演和编剧讲故事的能力都差强人意,镜头语言幼稚,几乎全程在快速地晃荡,人物情感没有张力,演员功力都弱弱的,都末日了,还不咸不淡的语气。。男主对他爹的大恨是从哪儿来的??不就是母亲放弃治疗吗?那个韩朵朵出来是干什么的?是让大家保护的“希望”化身??强行煽情的台词让我汗毛竖起。刻意卖的末世日情怀,我不想接。狂热的拥护。\n\n原来酒带上太空舱是为了炸掉智能机器人莫斯的。。被酒燃烧前莫斯的话是经典——想让人类保持理智是一种奢望。笑岔我。\n\n看到东方明珠塔被雪冻住了我就忍不住笑,不知道老美看到纽约被炸那么多次什么心情。\n\n无知导致浪漫。\n\n\n\n能更尴尬么?韩朵朵尴尬,刘启尴尬,演技尴尬,剧情尴尬,MOSS 反转尴尬,除了三体 再也不看刘慈欣的任何电影。失望。\n\n不感动啊…也没有满场子哭泣泣的!不过制作看得出来很精致,但独白很一般!韩朵朵喊救援时候太拖拉了!我都着急了!\n\n男权主义太重了,我真的十分讨厌吧危机关头,把女生演绎的像个傻子,赖赖唧唧的,拖后腿,最后几分钟通话光听她哭了,我叫韩朵朵,麻烦你想煽情的同时,台词有点说服力可以吗?4分全给特效,编、导、演都很差\n\n"}]}]
posted @ 2021-06-20 00:49  吴畅达  阅读(530)  评论(0编辑  收藏  举报