Now located at https://github.com/JeffPaine/beautiful_idiomatic_python.
Github gists don't support Pull Requests or any notifications, which made it impossible for me to maintain this (surprisingly popular) gist with fixes, respond to comments and so on. In the interest of maintaining the quality of this resource for others, I've moved it to a proper repo. Cheers!
This is my default career advice for people starting out in geo/GIS, especially remote sensing, adapted from a response to a letter in 2013.
I'm currently about to start a Geography degree at the University of [Redacted] at [Redacted] with a focus in GIS, and I've been finding that I have an interest in working with imagery. Obviously I should take Remote Sensing and other similar classes, but I'm the type of person who likes to self learn as well. So my question is this: What recommendations would you give to a student who is interested in working with imagery? Are there any self study paths that you could recommend?
I learned on my own and on the job, and there are a lot of important topics in GIS that I don’t know anything about, so I can’t give comprehensive advice. I haven’t arrived anywhere; I’m just ten minutes ahead in the convoy we’re both in. Take these recommendations critically.
Find interesting people. You’ll learn a lot more from a great professor (or mentor, or friend, or conference) o
| import os | |
| import urllib | |
| import urllib2 | |
| import base64 | |
| import json | |
| import sys | |
| import argparse | |
| try: | |
| import requests | |
| except ImportError: |
A personal diary of DataFrame munging over the years.
Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)
This is a collection of information on PostgreSQL and PostGIS for what I tend to use most often.
This list of resources is all about acquring and processing aerial imagery. It's generally broken up in three ways: how to go about this in Photoshop/GIMP, using command-line tools, or in GIS software, depending what's most comfortable to you. Often these tools can be used in conjunction with each other.
CartoDB Build Day
Hello!
Data: Denver Traffic Accidents
Go to your traffic_accidents table and let's start by creating a new visualization
key things
This page can always be found at: http://bit.ly/cdb-harvard
