Python爬取 冰冰 第一条B站视频的千条评论，绘制词云图，看看大家说了什么吧

B站当日弹幕获取冰冰B站视频弹幕爬取原理解析

数据分析

import pandas as pd

data = pd.read_excel(r"bingbing.xlsx")
data.head()

原文链接

数据预处理

数据描述

data.describe()

删除空值

data.dropna()

1180 rows × 5 columns

删除空值

data.drop_duplicates()

1179 rows × 5 columns

可视化

点赞TOP20

df1 = data.sort_values(by="点赞",ascending=False).head(20)

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.faker import Fakerc1 = (Bar().add_xaxis(df1["评论"].to_list()).add_yaxis("点赞数", df1["点赞"].to_list(), color=Faker.rand_color()).set_global_opts(title_opts=opts.TitleOpts(title="评论热度Top20"),datazoom_opts=[opts.DataZoomOpts(), opts.DataZoomOpts(type_="inside")],).render_notebook()
)
c1

等级分布

data.等级.value_counts().sort_index(ascending=False)

6    165
5    502
4    312
3    138
2     63
Name: 等级, dtype: int64

from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Fakerc2 = (Pie().add("",[list(z) for z in zip([str(i) for i in range(2,7)], [63,138,312,502,165])],radius=["40%", "75%"],).set_global_opts(title_opts=opts.TitleOpts(title="等级分布"),legend_opts=opts.LegendOpts(orient="vertical", pos_top="15%", pos_left="2%"),).set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")).render_notebook()
)
c2

性别分布

data.性别.value_counts().sort_index(ascending=False)

from pyecharts import options as opts
from pyecharts.charts import Pie
from pyecharts.faker import Fakerc4 = (Pie().add("",[list(z) for z in zip(["男","女","保密"], ["404",'103','673'])],radius=["40%", "75%"],).set_global_opts(title_opts=opts.TitleOpts(title="性别分布"),legend_opts=opts.LegendOpts(orient="vertical", pos_top="15%", pos_left="2%"),).set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")).render_notebook())
c4

绘制词云图

from wordcloud import WordCloud
import jieba
from tkinter import _flatten
from matplotlib.pyplot import imread
from PIL import Image, ImageDraw, ImageFont
import matplotlib.pyplot as plt
with open('stoplist.txt', 'r', encoding='utf-8') as f:stopWords = f.read()
with open('停用词.txt','r',encoding='utf-8') as t:stopWord = t.read()
total = stopWord.split() + stopWords.split()
def my_word_cloud(data=None, stopWords=None, img=None):dataCut = data.apply(jieba.lcut)  # 分词dataAfter = dataCut.apply(lambda x: [i for i in x if i not in stopWords])  # 去除停用词wordFre = pd.Series(_flatten(list(dataAfter))).value_counts()  # 统计词频mask = plt.imread(img)plt.figure(figsize=(20,20))wc  = WordCloud(scale=10,font_path='C:/Windows/Fonts/STXINGKA.TTF',mask=mask,background_color="white",)wc.fit_words(wordFre)plt.imshow(wc)plt.axis('off')
my_word_cloud(data=data["评论"],stopWords=stopWords,img="1.jpeg")

天气好冷，我整个人都是冰冰的