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
数据分析
import pandas as pd
data = pd.read_excel(r"bingbing.xlsx")
data.head()
数据预处理
数据描述
data.describe()
| 等级 | 点赞 | |
|---|---|---|
| count | 1180.000000 | 1180.000000 |
| mean | 4.481356 | 2200.617797 |
| std | 1.041379 | 10872.524850 |
| min | 2.000000 | 1.000000 |
| 25% | 4.000000 | 4.000000 |
| 50% | 5.000000 | 9.000000 |
| 75% | 5.000000 | 203.750000 |
| max | 6.000000 | 158457.000000 |
删除空值
data.dropna()
删除空值
data.drop_duplicates()
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 Faker
c1 = (
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 Faker
c2 = (
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 Faker
c4 = (
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")
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