Understanding Anaconda and Conda

If you’ve just started learning Python, you might have heard names like Anaconda, Conda, VS Code, or PyCharm and wondered:

Do I need to install all of these? Aren’t they the same thing?

Let’s make this simple.

1. What Anaconda Actually Is#

Anaconda is a software that is developed by Anaconda Inc. It is like a big toolbox for people who use Python for data science.

When you install Anaconda, you’re not just installing Python. You’re also getting:

• hundreds of popular packages (like numpy, pandas, matplotlib, etc.),
• a package manager (called conda), and
• a few helper tools, like Anaconda Navigator and Jupyter Notebook.

So Anaconda is a bundle. It’s convenient because it saves you the trouble of manually installing everything one by one.

But there’s a catch: it’s big (several gigabytes) and sometimes more than you actually need if you just want to write Python scripts.

Because of this, many people prefer to install Python directly and use VS Code or PyCharm as their editors.

2. What About VS Code and PyCharm?#

This is where many beginners get confused.

VS Code and PyCharm are IDEs (Integrated Development Environments), meaning the places where you write and run your code.

But they don’t include Python themselves.

They need to use an existing Python environment on your computer.

You have three main ways to get that Python environment:

1. Install Python directly from python.org. This is the simplest and most common way as it gives you the official “system Python.”

2. Install Miniconda, a lightweight manager that lets you create isolated environments easily, which contains conda (it will be explained later).

3. Install Anaconda, the big “all-in-one” version with tons of data science tools preinstalled.

Even if you have VS Code or PyCharm, you still need Python underneath. But you can get Python either directly (from python.org) or through Anaconda / Miniconda, both ways work fine.

3. Then What Is Conda?#

Conda is the engine inside Anaconda. It is developed by the Anaconda team to work as a package and environment manager.

It helps you:

• install and update libraries (like pip does), and
• create separate environments so that different projects don’t mess with each other.

It is important to be aware that Conda can exist without Anaconda.

You can install Miniconda, which is a lightweight version that only gives you Python + Conda, without all the extra packages.

Then you install whatever you need, step by step. It’s cleaner, smaller, and more flexible.

In short:

• Anaconda = Conda + Python + a huge package collection
• Miniconda = Conda only, for virtual environment management

But Conda is not the only virtual environment tool that you can use. Instead, many people also use other tools. For details of their differences, please check here.

4. Do You Still Need Anaconda?#

It depends on your goal.

• If you are a beginner in data analysis or machine learning, and you want everything ready to go, Anaconda is the easiest start.

You install it once, and you’re ready to open Jupyter or VS Code and start coding.

• If you are a developer or researcher who likes a clean setup, you can install Miniconda or even just use Python + pip (the most commmon way for those who already have coding experience).

In both cases, VS Code or PyCharm are just your “workbenches”, i.e., where you write the code, not where Python lives.

5. Summary#

Think of it this way:

• Anaconda → the big “everything included” toolbox
• Conda → the manager that installs and switches between tools
• VS Code / PyCharm → the desks where you actually work

You can code without Anaconda, but you can’t code without Python. Anaconda just makes Python setup easier, especially at the beginning.