Python is a language that you can start programming in tonight, and tomorrow you can analyze data and build graphs. It reads almost like English, forgives minor mistakes, and has a huge ecosystem of libraries for the web, automation, and Data Science.
Why Python?
Simple syntax.
Less "brackets and semicolons", more logic and meaning.
A huge ecosystem.
From bots to neural networks: requests, FastAPI, pandas, numpy, matplotlib, scikit-learn, PyTorch.
Cross-platform.
Works equally well on Windows, macOS, and Linux.
Strong community.
Any question already has an answer and a ready-made code example.
"Understood - done": Python in 30 seconds
# Hello, data world
name = "Anya"
scores = [85, 92, 78]
avg = sum(scores) / len(scores)
print(f"Hi {name}! Average score: {avg:.1f}")
Conclusion: Привет, Аня! Средний балл: 85.0
Where is Python useful right now?
Task | What to do | Libraries/tools |
|---|---|---|
Routine automation | Scripts, parsing, reports | os, pathlib, requests, BeautifulSoup |
Web development | APIs and websites | FastAPI, Django, Flask |
Data Science & Analytics | Tables, charts, metrics | pandas, numpy, matplotlib, seaborn |
Machine learning | ML Classics | scikit-learn |
Deep learning | Neural networks | PyTorch, TensorFlow |
Scripts for DevOps | Infrastructure | fabric, invoke, CLI utilities |
Python for Data Science: from CSV to Model
Loading data: CSV/Excel/DB →
pandas.read_csv()Cleaning: gaps, types, duplicates
EDA: quick slices and aggregates (
groupby,describe)Visualization:
matplotlib/seabornBasic model:
scikit-learn(train/test split, metrics)
Mini-project: "Sales for the month in one line"
import pandas as pd
df = pd.read_csv("sales.csv") # columns: date, city, product, amount
report = df.groupby("city")["amount"].sum().sort_values(ascending=False)
print(report.head())
Idea: Add a filter by month, save report.to_csv("report.csv"), and then save the visualization:
import matplotlib.pyplot as plt
report.head(5).plot(kind="bar")
plt.title("Top 5 cities by sales")
plt.xlabel("City"); plt.ylabel("Amount")
plt.tight_layout(); plt.show()
Installation and tools
Python 3.12+ from python.org or through your OS package manager.
Editor: VS Code (extensions: Python, Jupyter).
Virtual environments:
python -m venv .venv→ activation by OS.Installing packages:
pip install pandas numpy matplotlib scikit-learn
Basic Types Cheat Sheet
Type | Example | Why do you need it? |
|---|---|---|
int | 42 | integers |
float | 3.14 | fractional |
str | "hello" | text |
bool | True / False | Logic |
list | [1, 2, 3] | ordered collection |
dict | {"name": "Ann"} | "key → value" dictionary |
In the attachment Code you take short lessons, get achievements, do mini-projects and discuss solutions in the community. There are separate tracks for Python: from zero to the first model and visualization.
And we also have an active Telegram channel, where we discuss cool ideas, share experiences and analyze tasks together — learning becomes not only useful, but also fun
💬
Have you tried pandas yet? Write in the comments which table you want to "tame" first — sales, logs, finances, or something else?