Homework 10: Cartopy¶

1) Plot data from NARR¶

NARR is NCEP's North American Regional Reanalysis, a widely used product for studying the weather and climate of the continental US. The data is available from NOAA's Earth System Research Laboratory via OPeNDAP, meaing that xarray can opent the data "remotely" without downloading a file.

Speed, Performance, and Profiling in Python¶

1) Write a function to find the maximum of a list of numbers using pure core python (no numpy)¶

Assignment 8 : Xarray Groupby¶

Here will will calculate the NINO 3.4 index of El Nino variabillity and use it to analyze datasets.

First read this page from NOAA. It tells you the following.

• The Nino 3.4 region is defined as the region between +/- 5 deg. lat, 170 W - 120 W lon.
more ...

Assignment 7 : Xarray¶

In this assignment, we will use Xarray to analyze top-of-atmosphere radiation data from NASA's CERES project.

Public domain, by NASA, from Wikimedia Commons

I have pre-downloaded and subsetted a portion of this dataset for use in our class. You can download it here: http://ldeo.columbia.edu/~rpa/CERES_EBAF-TOA_Edition4.0_200003-201701.condensed.nc. The size of the data file is 702.53 MB. It will take a minute or two to download.

Assignment 6: Pandas Groupby with Hurricane Data¶

Import pandas and matplotlib

Assignment 4: More Matplotlib¶

The goal here is to replicate the figures you see as closely as possible.

In order to get some data, you will have to run the code in the cells below. Don't worry about how this code works. In the end, it will give you some numpy arrays, which you will use in your plots. You are not allowed to use any packages other than numpy and matplotlib to complete your assignment.

Assignment 3 - Numpy and Matplotlib¶

Due Thursday September 27¶

1 Creating and Manipulating Arrays¶

First import numpy and matplotlib

Assignment 2: Python Functions and Classes¶

Part I: Exploring the Python Standard Library¶

Skim the documentation for the datetime module

1. Import the datetime module¶

Assignment 1¶

Part 1: Files, Git, GitHub¶

Use JupyterLab to launch a terminal and use the terminal to do the following tasks:

1. Create a new directory called resume within your home directory
2. Create an empty file within this directory called Readme.md

Now use JupyterLab to edit the file:

1. Navigate to the directory in the file browser
more ...