Project Docs
  • 👋Welcome to End2End Data Science Project Documentation
  • About us
    • 💡Who we are
  • Project Guides
    • 📪Project Pipeline Overview
    • 📎Understanding Projects
  • Fundamentals
    • 🛠️Getting started
      • 💻Step 1: Github
        • Working with Git & Github
          • Setting up your repository & project
          • Git Branching
          • Push & Pull
          • Pull Request
        • Resources
        • Exercise
      • 💻Step 2: Python Setup
      • 💻Step 3: Conda Environment
        • Working with Conda Environment
        • Resources
      • 💻Step 4: MySQL, Postgres & Oracle DB
        • Quick review on SQL
        • Exercises (Under development)
      • 💻Step 5: Project Setup
      • 💻Step 6: AWS & GCP
        • Automation
      • 📉Step 7: Final Presentation
      • 🚀Step 8: Docker
        • Creating Docker Image
        • Useful Docker commands
  • 📔Interesting articles
    • Data Engineering
    • Data Science
    • ML & MLOps
  • 📔Resources
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On this page
  • Creating a new folder for your project
  • Creating environment
  • Activating an existing environment
  • Installing packages into an existing environment
  • Deactivating the current environment
  • Remove/Delete Conda environment
  1. Fundamentals
  2. Getting started
  3. Step 3: Conda Environment

Working with Conda Environment

To create your first conda environment, follow the examples below after opening Terminal or command prompt, depending on your operating system.

Creating a new folder for your project

$ cd ~/Desktop
$ mkdir conda_tutorial
$ cd conda_tutorial

Creating environment

$ conda create --name <your env name>
# replace "your env name" with whatever name you would like to call 
#    for your environment. It is always a good practice to name it 
#    the same as your project

Activating an existing environment

$ conda activate <your env name>

Installing packages into an existing environment

$ conda install pip

# you can install pip and then use pip to install packages or can 
#    directly install using conda as follows
$ conda install pandas==<version>
        # OR 
$ pip install numpy==<version_num>

Deactivating the current environment

$ conda deactivate
# it is a good practice to always deactivate environment when not working on the project

Remove/Delete Conda environment

$ conda remove -n <env_name> --all
PreviousStep 3: Conda EnvironmentNextResources

Last updated 11 months ago

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