数据爬取+可视化实战_告白气球_词云展示----酷狗音乐

一、前言

歌词上做文本分析，数据存储在网页上，需要爬取数据下来，词云展示在工作中也变得日益重要，接下来将数据爬虫与可视化结合起来，做个词云展示案例。

二、代码

# -*- coding:utf-8 -*-
# 酷狗音乐 通过获取每首歌歌词ID，生成该歌手的词云
import requests
import sys
import re
import os
from wordcloud import WordCloud
import matplotlib.pyplot as plt
import jieba
from PIL import Image
import numpy as np
from lxml import etreeheaders = {'Referer'  :'https://www.kugou.com','Host'     :'www.kugou.com','Accept'   :'*/*','User-Agent':'Chrome/10'}# 得到一首歌的歌词
def get_song_lyric(headers,lyric_url):res = requests.request('GET', lyric_url, headers=headers)if 'lrc' in res.json():lyric = res.json()['lrc']['lyric']new_lyric = re.sub(r'[\d:.[\]]','',lyric)return new_lyricelse:return ''print(res.json())
# 去掉停用词
#def remove_stop_words(f):
#    stop_words = ['还', '人', '着', '又', '就', '在', '也', '不', '会', '和', '是', '没', '说', '们', '谁', '这','对', '而', '不是', '什么', '有限公司', '编写','室', '声', '去', '经纪', '一切', '想', '才', '都', '你', '的', '了', '我', '有', '着这', '让', '看', '作词', '作曲', '编曲', 'Arranger', '录音', '混音', '人声', 'Vocal', '弦乐', 'Keyboard', '键盘', '编辑', '助理', 'Assistants', 'Mixing', 'Editing', 'Recording', '音乐', '制作', 'Producer', '发行', 'produced', 'and', 'distributed']
#    for stop_word in stop_words:
#        f = f.replace(stop_word, '')
#    return f
# 生成词云
def create_word_cloud(f):print('根据词频，开始生成词云!')#f = remove_stop_words(f)cut_text = " ".join(jieba.cut(f,cut_all=False, HMM=True))wc = WordCloud(font_path="./SimHei.ttf",max_words=100,width=2000,height=1200,)print(cut_text)wordcloud = wc.generate(cut_text)# 写词云图片wordcloud.to_file("wordcloud.jpg")# 显示词云文件plt.imshow(wordcloud)plt.axis("off")plt.show()# 所有歌词
all_word = ''
# 获取每首歌歌词
song_id = '536570450'
song_name = '魔术与歌曲：告白气球'# 歌词API URL
lyric_url = 'http://music.163.com/api/song/lyric?os=pc&id=' + song_id + '&lv=-1&kv=-1&tv=-1'
lyric = get_song_lyric(headers, lyric_url)
all_word = all_word + ' ' + lyric
print(song_name)
#根据词频 生成词云
create_word_cloud(all_word)