Python Projects & Free Books
前往频道在 Telegram
📈 Telegram 频道 Python Projects & Free Books 的分析概览
频道 Python Projects & Free Books (@pythonfreebootcamp) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 40 926 名订阅者,在 技术与应用 类别中位列第 3 337,并在 印度 地区排名第 10 047 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 40 926 名订阅者。
根据 05 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 175,过去 24 小时变化为 29,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 4.03%。内容发布后 24 小时内通常能获得 0.77% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 649 次浏览,首日通常累积 314 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 5。
- 主题关注点: 内容集中在 learning, analyst, framework, link:-, structure 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“Python Interview Projects & Free Courses
Admin: @Coderfun”
凭借高频更新(最新数据采集于 07 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。
40 926
订阅者
+2924 小时
+517 天
+17530 天
帖子存档
https://topmate.io/analyst/907371
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Python code To download from Youtube ⚙
from pytube import YouTube
# Enter the YouTube video URL
url = "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
# Create a YouTube object with the URL
yt = YouTube(url)
# Select the highest resolution video
video = yt.streams.get_highest_resolution()
# Set the output directory and filename
output_dir = "/storage/emulated/0/Documents/"
filename = yt.title+".mp4"
# Download the video
video.download(output_dir, filename)
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Essential Python Libraries for Data Analytics 😄👇
Python Free Resources: https://t.me/pythondevelopersindia
1. NumPy:
- Efficient numerical operations and array manipulation.
2. Pandas:
- Data manipulation and analysis with powerful data structures (DataFrame, Series).
3. Matplotlib:
- 2D plotting library for creating visualizations.
4. Scikit-learn:
- Machine learning toolkit for classification, regression, clustering, etc.
5. TensorFlow:
- Open-source machine learning framework for building and deploying ML models.
6. PyTorch:
- Deep learning library, particularly popular for neural network research.
7. Django:
- High-level web framework for building robust, scalable web applications.
8. Flask:
- Lightweight web framework for building smaller web applications and APIs.
9. Requests:
- HTTP library for making HTTP requests.
10. Beautiful Soup:
- Web scraping library for pulling data out of HTML and XML files.
As a beginner, you can start with Pandas and Numpy libraries for data analysis. If you want to transition from Data Analyst to Data Scientist, then you can start applying ML libraries like Scikit-learn, Tensorflow, Pytorch, etc. in your data projects.
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Hope it helps :)
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Tips to Merge two dictionary
boy={"ram":70,"Sundar":80}
girl={"riya":80,"Sonali":70}
student=boy | girl
print(student)Scrap Image from bing using BeautifulSoup
import requests
from bs4 import BeautifulSoup as BSP
def split_url(url):
return url.split('&')[0]
def get_image_urls(search_query):
url = f"https://cn.bing.com/images/search?q={search_query}&first=1&cw=1177&ch=678"
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"
}
rss = requests.get(url, headers=headers)
soup = BSP(rss.content, "html.parser")
all_img = []
for img in soup.find_all('img'):
img_url = img.get('src2')
if img_url and img_url.startswith('https://tse2.mm.bing.net/'):
img_url = split_url(img_url)
all_img.append(img_url)
return all_img
print(get_image_urls("cat"))
sample response :
['https://tse2.mm.bing.net/th?q=Cat+Portrait', ...']
Scrap Image from google using BeautifulSoup
import requests
from bs4 import BeautifulSoup as BSP
def get_image_urls(search_query):
url = f"https://www.google.com/search?q={search_query}&tbm=isch"
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3"
}
rss = requests.get(url, headers=headers)
soup = BSP(rss.content, "html.parser")
all_img = []
for img in soup.find_all('img'):
src = img['src']
if not src.endswith("gif"):
all_img.append(src)
return all_img
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