commands/python/conda/setup-conda-data-analysis.md

metadata

description: Set up conda environment for data analysis
tags:
  - python
  - conda
  - data-analysis
  - jupyter
  - pandas
  - project
  - gitignored

You are helping the user set up a conda environment for data analysis.

Process

1. Create base environment

   conda create -n data-analysis python=3.11 -y
   conda activate data-analysis
   

2. Install core data analysis libraries

   conda install -c conda-forge pandas numpy scipy -y
   

3. Install visualization libraries

   conda install -c conda-forge matplotlib seaborn plotly -y
   pip install altair
   pip install bokeh
   

4. Install Jupyter ecosystem

   conda install -c conda-forge jupyter jupyterlab ipywidgets -y
   pip install jupyterlab-git
   pip install jupyterlab-lsp
   

5. Install statistical and ML libraries

   conda install -c conda-forge scikit-learn statsmodels -y
   pip install scipy
   pip install pingouin        # Statistics
   

6. Install data processing tools

   conda install -c conda-forge openpyxl xlrd -y  # Excel support
   pip install pyarrow fastparquet  # Parquet support
   pip install sqlalchemy      # Database connectivity
   pip install beautifulsoup4  # Web scraping
   pip install requests        # HTTP requests
   

7. Install data manipulation tools

   pip install polars          # Fast DataFrame library
   pip install dask            # Parallel computing
   pip install vaex            # Big data processing
   

8. Install database drivers

   pip install psycopg2-binary  # PostgreSQL
   pip install pymongo          # MongoDB
   pip install redis            # Redis
   

9. Install development tools

   pip install black           # Code formatting
   pip install pylint          # Linting
   pip install ipdb            # Debugging
   

10. Configure Jupyter extensions

• Enable useful extensions
• Set up theme preferences
• Configure autosave

11. Create example notebook

• Offer to create ~/notebooks/data-analysis-template.ipynb with common imports

Output

Provide a summary showing:

• Environment name and setup status
• Installed libraries grouped by category
• Jupyter Lab configuration
• Example import statements
• Suggested workflows
• Links to documentation