/ncar_pandas_tutorial

Example of using Pandas

Primary LanguageJupyter Notebook

NCAR pandas Tutorial

Welcome to the UCAR/NCAR Xdev pandas tutorial repository. This tutorial is scheduled for Wednesday, May 26 2021 at 1:00 pm MDT / 1900 UTC and will be led by Drew Camron and Max Grover.

Prerequisites

A basic knowledge of Python, NumPy, and Matpolotlib is required. Comfort with Jupyter notebook or Jupyter lab, and conda/pip is helpful. Familiarity with tabular data, e.g. .csv files, is important to understanding pandas and its strengths.

Setup

  1. Clone or otherwise download this repository using the green Code button above
  2. If you've already done this, you may want to make sure you're up-to-date with a git pull or re-download if necessary.
  3. Install conda
  4. From your terminal (macOS, Linux) or git bash/Anaconda Prompt/Powershell (Windows), execute the following from within this directory: conda env create -f environment.yml
  5. Activate your new python environment with conda activate ncar_pandas_tutorial
  6. Launch jupyter lab from this prompt
  7. Open pandas_seminar.ipynb if you'll be coding along or pandas_fullNotebook.ipynb if you will only be reading along today.

If you have preferred ways to maintain your own environment or otherwise interact with Python, you'll only need to make sure you have pandas and matplotlib installed, and download our notebooks and the enso_data.csv file. Creating this environment and launching Jupyter lab can also be done in the Anaconda Navigator GUI.

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