利用Python代码进行网络爬虫抓取，数据分析和可视化呈现，以下是对原有代码内容的新角度改写：

```python

# 导入所需库

import requests

import re

from bs4 import BeautifulSoup

import jieba

from wordcloud import WordCloud

from PIL import Image

import numpy as np

import matplotlib.pyplot as plt

import csv

# 设置结巴分词的日志级别

jieba.setLogLevel(jieba.logging.INFO)

# 定义获取网页内容的函数

def fetch_web_content(url):

try:

response = requests.get(url)

response.raise_for_status()

response.encoding = response.apparent_encoding

print(f"成功访问：{url}")

return response.text

except Exception as e:

print(f"访问失败：{e}")

return None

# 定义获取基金信息的函数

def gather_fund_info(url, info_container):

fund_codes = []

html_content = fetch_web_content(url)

if html_content is None:

return

soup = BeautifulSoup(html_content, 'html.parser')

fund_elements = soup.find_all('td', width="27%")

for element in fund_elements:

fund_code = re.findall(r"d{6}", element.a['href'])[0]

fund_codes.append(fund_code)

fund_info = [fund_code]

fund_detail_url = f"{url}{fund_code}"

fund_detail_html = fetch_web_content(fund_detail_url)

if fund_detail_html is None:

continue

fund_soup = BeautifulSoup(fund_detail_html, 'html.parser')

fund_name = fund_soup.h1.text.strip('<').strip('>').replace('<', '').replace('>', '')

fund_info.append(fund_name)

# 更多基金信息获取逻辑...

info_container.append(fund_info)

# 所有行业列表

all_industries = ["农林牧渔", "食品饮料", "生物医药", "建筑材料", "房地产", "家用电器", "电子", "公用事业", "重组", "交通运输", "医药生物", "轻工制造", "高铁", "采掘", "休闲服务", "汽车", "传媒", "美丽中国", "国资改革", "计算机", "纺织服装", "银行", "建筑装饰", "国防军工", "一带一路", "非银金融", "移动互联网", "机械设备", "通信", "环保概念", "化工", "钢铁", "高端装备制造", "有色金属", "电气设备", "综合"]

# 存储所有基金信息的容器

all_fund_info = []

# 主函数，启动爬虫

def main_crawler():

fund_url = 'https://www.howbuy.com/fund/'

gather_fund_info(fund_url, all_fund_info)

# 执行主函数

main_crawler()

# 使用结巴分词和词云进行数据可视化

# 相关处理逻辑...

# 数据分析和可视化

# 相关处理逻辑...

# 数据持久化，写入CSV文件

with open('d:\\ji.csv', 'w', newline='', encoding='gb18030') as csvfile:

writer = csv.writer(csvfile)

for info in all_fund_info:

writer.writerow(info)

# 打印输出基金信息

header_format = "{:<5} {:<18} {:<5} {:<4} {:<7} {:<5} {:<5} {:<5} {:<7} {:<4}"

print(header_format.format("基金代码", "基金名称", "单位净值", "涨跌幅", "基金排名", "3月涨幅", "1年涨幅", "基金规模", "成立日期", "所属行业"))

for info in all_fund_info:

print(header_format.format(*info))

```