✅ Top 5 Mistakes to Avoid When Learning Python ❌🐍
1️⃣ Skipping the Basics
Many learners rush to libraries like Pandas or Django. First, master Python syntax, data types, loops, functions, and OOP. It builds the foundation.
2️⃣ Ignoring Indentation Rules
Python uses indentation to define code blocks. One wrong space can break your code — always stay consistent (usually 4 spaces).
3️⃣ Not Practicing Enough
Watching tutorials alone won’t help. Code daily. Start with small scripts like a calculator, quiz app, or text-based game.
4️⃣ Avoiding Errors Instead of Learning from Them
Tracebacks look scary but are helpful. Read and understand error messages. They teach you more than error-free code.
5️⃣ Relying Too Much on Copy-Paste
Copying code without understanding kills learning. Try writing code from scratch and explain it to yourself line-by-line.
💬 Tap ❤️ for more!
1️⃣ Skipping the Basics
Many learners rush to libraries like Pandas or Django. First, master Python syntax, data types, loops, functions, and OOP. It builds the foundation.
2️⃣ Ignoring Indentation Rules
Python uses indentation to define code blocks. One wrong space can break your code — always stay consistent (usually 4 spaces).
3️⃣ Not Practicing Enough
Watching tutorials alone won’t help. Code daily. Start with small scripts like a calculator, quiz app, or text-based game.
4️⃣ Avoiding Errors Instead of Learning from Them
Tracebacks look scary but are helpful. Read and understand error messages. They teach you more than error-free code.
5️⃣ Relying Too Much on Copy-Paste
Copying code without understanding kills learning. Try writing code from scratch and explain it to yourself line-by-line.
💬 Tap ❤️ for more!
❤5👍1👏1
This media is not supported in your browser
VIEW IN TELEGRAM
The #Python library #PandasAI has been released for simplified data analysis using AI.
You can ask questions about the dataset in plain language directly in the #AI dialogue, compare different datasets, and create graphs. It saves a lot of time, especially in the initial stage of getting acquainted with the data. It supports #CSV, #SQL, and Parquet.
And here's the link 😍
You can ask questions about the dataset in plain language directly in the #AI dialogue, compare different datasets, and create graphs. It saves a lot of time, especially in the initial stage of getting acquainted with the data. It supports #CSV, #SQL, and Parquet.
And here's the link 😍