Python for Data Analysts
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Find top Python resources from global universities, cool projects, and learning materials for data analytics.

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Useful links: heylink.me/DataAnalytics
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๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ ๐—ผ๐—ป ๐—–๐—ต๐—ฎ๐˜๐—š๐—ฃ๐—ง ๐—ฃ๐—ฟ๐—ผ๐—บ๐—ฝ๐˜ ๐—˜๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—ฏ๐˜† ๐——๐—ฒ๐—ฒ๐—ฝ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด.๐—”๐—œ & ๐—ข๐—ฝ๐—ฒ๐—ป๐—”๐—œ๐Ÿ˜

๐Ÿ’ก Think ChatGPT is Just for Fun? Think Again๐Ÿ“Œ

In todayโ€™s AI-driven world, knowing how to communicate effectively with large language models (LLMs) is more than just a bonus โ€” itโ€™s a competitive edge๐Ÿ“Š๐ŸŽฏ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

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Use ChatGPT like a developer โ€” not just a casual userโœ…๏ธ
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Lists ๐Ÿ†š Tuples ๐Ÿ†š Dictionaries

What's the difference?

Lists are mutable.
Tuples are immutable.
Dictionaries are associative.

When should you use each?

Lists:
โŸถ When you want to add or remove elements
โŸถ When you want to sort elements
โŸถ When you want to slice elements

Tuples:
โŸถ When you want a constant object
โŸถ When you want to send multiple in a function
โŸถ When you want to return multiple from a function

Dictionaries:
โŸถ When you want to map keys to values
โŸถ When you want to loop over the keys
โŸถ When you want to validate if key exists

Now, pick your weapon of mass data analysis and become a Python pro!

Python Interview Q&A: https://topmate.io/coding/898340

Like for more โค๏ธ

ENJOY LEARNING ๐Ÿ‘๐Ÿ‘
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๐Ÿฑ ๐— ๐˜‚๐˜€๐˜-๐—™๐—ผ๐—น๐—น๐—ผ๐˜„ ๐—ฌ๐—ผ๐˜‚๐—ง๐˜‚๐—ฏ๐—ฒ ๐—–๐—ต๐—ฎ๐—ป๐—ป๐—ฒ๐—น๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—”๐˜€๐—ฝ๐—ถ๐—ฟ๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐˜๐—ถ๐˜€๐˜๐˜€ ๐—ถ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ๐Ÿ˜

Want to Become a Data Scientist in 2025? Start Here!๐ŸŽฏ

If youโ€™re serious about becoming a Data Scientist in 2025, the learning doesnโ€™t have to be expensive โ€” or boring!๐Ÿš€

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

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Perfect for beginners and aspiring prosโœ…๏ธ
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๐Ÿ–ฅ All Data Structures
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7 Must-Have Tools for Data Analysts in 2025:

โœ… SQL โ€“ Still the #1 skill for querying and managing structured data
โœ… Excel / Google Sheets โ€“ Quick analysis, pivot tables, and essential calculations
โœ… Python (Pandas, NumPy) โ€“ For deep data manipulation and automation
โœ… Power BI โ€“ Transform data into interactive dashboards
โœ… Tableau โ€“ Visualize data patterns and trends with ease
โœ… Jupyter Notebook โ€“ Document, code, and visualize all in one place
โœ… Looker Studio โ€“ A free and sleek way to create shareable reports with live data.

Perfect blend of code, visuals, and storytelling.

React with โค๏ธ for free tutorials on each tool

Share with credits: https://t.iss.one/sqlspecialist

Hope it helps :)
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๐ŸŽ“ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐—–๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ฒ๐—ฟ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—›๐—ฎ๐—ฟ๐˜ƒ๐—ฎ๐—ฟ๐—ฑ, ๐—ฆ๐˜๐—ฎ๐—ป๐—ณ๐—ผ๐—ฟ๐—ฑ, ๐— ๐—œ๐—ง & ๐—š๐—ผ๐—ผ๐—ด๐—น๐—ฒ๐Ÿ˜

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๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

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Perfect for students, self-learners, and career switchersโœ…๏ธ
Free Resources for Python

Codebasics python tutorials (first 16) โ€” 
https://www.youtube.com/playlist?list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0

Practice Python course
https://dabeaz-course.github.io/practical-python/Notes/Contents.html

Codebasics python HINDI tutorials โ€”
 https://www.youtube.com/playlist?list=PLPbgcxheSpE1DJKfdko58_AIZRIT0TjpO

Useful Python resources for beginners
https://t.iss.one/programming_guide/8

Python 3 Book for beginners
https://t.iss.one/pythondevelopersindia/272?single
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๐Ÿš€ Essential Python snippets to explore data:
 
1.   .head() - Review top rows
2.   .tail() - Review bottom rows
3.   .info() - Summary of DataFrame
4.   .shape - Shape of DataFrame
5.   .describe() - Descriptive stats
6.   .isnull().sum() - Check missing values
7.   .dtypes - Data types of columns
8.   .unique() - Unique values in a column
9.   .nunique() - Count unique values
10.   .value_counts() - Value counts in a column
11.   .corr() - Correlation matrix
โค4
๐—”๐—ฑ๐—ฑ ๐——๐—ฒ๐—น๐—ผ๐—ถ๐˜๐˜๐—ฒ ๐˜๐—ผ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ โ€” ๐—ก๐—ผ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ก๐—ฒ๐—ฒ๐—ฑ๐—ฒ๐—ฑ!๐Ÿ˜

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Python for Data Analytics - Quick Cheatsheet with Cod e Example ๐Ÿš€

1๏ธโƒฃ Data Manipulation with Pandas

import pandas as pd  
df = pd.read_csv("data.csv")
df.to_excel("output.xlsx")
df.head()
df.info()
df.describe()
df[df["sales"] > 1000]
df[["name", "price"]]
df.fillna(0, inplace=True)
df.dropna(inplace=True)


2๏ธโƒฃ Numerical Operations with NumPy

import numpy as np  
arr = np.array([1, 2, 3, 4])
print(arr.shape)
np.mean(arr)
np.median(arr)
np.std(arr)


3๏ธโƒฃ Data Visualization with Matplotlib & Seaborn


import matplotlib.pyplot as plt  
plt.plot([1, 2, 3, 4], [10, 20, 30, 40])
plt.bar(["A", "B", "C"], [5, 15, 25])
plt.show()
import seaborn as sns
sns.heatmap(df.corr(), annot=True)
sns.boxplot(x="category", y="sales", data=df)
plt.show()


4๏ธโƒฃ Exploratory Data Analysis (EDA)

df.isnull().sum()  
df.corr()
sns.histplot(df["sales"], bins=30)
sns.boxplot(y=df["price"])


5๏ธโƒฃ Working with Databases (SQL + Python)

import sqlite3  
conn = sqlite3.connect("database.db")
df = pd.read_sql("SELECT * FROM sales", conn)
conn.close()
cursor = conn.cursor()
cursor.execute("SELECT AVG(price) FROM products")
result = cursor.fetchone()
print(result)


React with โค๏ธ for more

Share with credits: https://t.iss.one/sqlspecialist

Hope it helps :)
โค12
๐—ฆ๐—ค๐—Ÿ ๐Ÿญ๐Ÿฌ๐Ÿฌ% ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜

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๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

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๐Ÿ’ฅ Start learning today and build the skills top companies want!โœ…๏ธ
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โค3