Python for Data Analysts
前往频道在 Telegram
Find top Python resources from global universities, cool projects, and learning materials for data analytics. For promotions: @coderfun Useful links: heylink.me/DataAnalytics
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网络:📈 Telegram 频道 Python for Data Analysts 的分析概览
频道 Python for Data Analysts (@pythonanalyst) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 51 569 名订阅者，在 技术与应用 类别中位列第 2 585，并在 印度 地区排名第 6 735 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 51 569 名订阅者。
根据 30 十月, 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 -222，过去 24 小时变化为 -13，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 5.96%。内容发布后 24 小时内通常能获得 0.97% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 0 次浏览，首日通常累积 498 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 0。
- 主题关注点： 内容集中在 visualization, panda, analyst, sql, analytic 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：
“Find top Python resources from global universities, cool projects, and learning materials for data analytics.
For promotions: @coderfun
Useful links: heylink.me/DataAnalytics”
凭借高频更新（最新数据采集于 31 十月, 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。
51 569
订阅者
-1324 小时
-707 天
-22230 天
帖子存档
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🔰 Learning Python for Data Analysis and Visualization
⏱ 21 Hours 📦 110 Lessons
Learn python and how to use it to analyze,visualize and present data. Includes tons of sample code and hours of video!
Taught By: Jose Portilla
Download Full Course: https://t.me/pythonanalyst/26
Download All Courses: https://t.me/DataAnalystInterview
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Python Generators
In Python, a generator is a function that returns an iterator that produces a sequence of values when iterated over.
Generators are useful when we want to produce a large sequence of values, but we don't want to store all of them in memory at once.
There is a lot of complexity in creating iteration in Python; we need to implement iter() and next() method to keep track of internal states.
It is a lengthy process to create iterators. That's why the generator plays an essential role in simplifying this process. If there is no value found in iteration, it raises StopIteration exception.
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Output of this code?
x = lambda a, b, c : a + b + c
print(x(5, 6, 2))
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What will be the output of this code in python?
x = lambda a, b : a * b
print(x(5, 6))
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Example:
Add 10 to argument a, and return the result:
x = lambda a : a + 10
print(x(5))
Output will be 1551 561
Python Lambda:
A lambda function is a small anonymous function.
A lambda function can take any number of arguments, but can only have one expression.
lambda arguments : expression
The expression is executed and the result is returned.
Use lambda functions when an anonymous function is required for a short period of time.
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Syntax:
newlist = [expression for item in iterable if condition == True]
The return value is a new list, leaving the old list unchanged.
The condition is like a filter that only accepts the items that valuate to True. The condition is optional and can be omitted.
The iterable can be any iterable object, like a list, tuple, set etc.
The expression is the current item in the iteration, but it is also the outcome, which you can manipulate before it ends up like a list item in the new list.
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👉 List comprehensions: List comprehension offers a shorter syntax when you want to create a new list based on the values of an existing list.
Example:
Based on a list of fruits, you want a new list, containing only the fruits with the letter "a" in the name.
Without list comprehension you will have to write a for statement with a conditional test inside:
fruits = ["apple", "banana", "cherry", "kiwi", "mango"]
newlist = []
for x in fruits:
if "a" in x:
newlist.append(x)
print(newlist)
With list comprehension you can do all that with only one line of code:
fruits = ["apple", "banana", "cherry", "kiwi", "mango"]
newlist = [x for x in fruits if "a" in x]
print(newlist)