Data Driven Decision Making – Global Homework Experts

Session 2
Data Driven Decision Making – DDDM
Agenda for this/next week
Recap session one
Introduction to Python programming language
The importance of Python for data management applications
Module Assessment
Reminder: see Blackboard for assessment details
To start with…
Recap on session one
Learning Outcomes
On completion of this workshop you will be able to:
Install a Python programming environment
Write and execute Python scripts
Access and query data sets using Python scripts
Reflect on the applicability of these topics to different organisations
Now that we have Python installed, it is possible to program using the language.
It is possible to edit a python program, using an editor such as atom. Or it is possible to
use the python command line (e.g. cmder) to get a sense of the language, and to control
the server.
In this session we will have a look at some of the more fundamental language constructs
using the command line interface.
Introduction to Python
Python is a high-level programming language
Open source and community driven
“Batteries Included”
a standard distribution includes many modules
Dynamic typed
Source can be compiled or run just-in-time
Similar to perl, tcl, ruby
Why Python?
Unlike AML and Avenue, there is a considerable base of developers already
using the language
“Tried and true” language that has been in development since 1991
Can interface with the Component Object Model (COM) used by Windows
Can interface with Open Source GIS toolsets
Why not Visual Basic?
Visual Basic is still the method of configuring and customizing ArcMap
If you have a button on the toolbar, it’s VB
Python scripts can be placed in ArcToolbox
Python can be run from the command line without ArcMap or ArcCatalog
being open
Using just the GIS Engine, lower overhead
Rapid prototyping, ease of authoring, etc.
Python Interfaces
IDLE – a cross-platform Python development environment
PythonWin – a Windows only interface to Python
Python Shell – running ‘python’ from the Command Line opens this interactive

Example Python
Hello World
print “hello world”
Prints hello world to
standard out
Open IDLE and try it out
Follow along using IDLE
More than just printing
Python is an object oriented language
Practically everything can be treated as an object
“hello world” is a string
Strings, as objects, have methods that return the result of a function on the

String Methods
Assign a string to a variable
In this case “hw
String Methods
The string held in your variable remains the same
The method returns an altered string
Changing the variable requires reassignment
hw = hw.upper()
hw now equals “HELLO WORLD”
Other Python Objects
Lists (mutable sets of strings)
var = [] # create list
var = [‘one’, 2, ‘three’, ‘banana’]
Tuples (immutable sets)
var = (‘one’, 2, ‘three’, ‘banana’)
Dictionaries (associative arrays or ‘hashes’)
var = {} # create dictionary
var = {‘lat’: 40.20547, ‘lon’: -74.76322}
var[‘lat’] = 40.2054
Each has its own set of methods
Think of a list as a stack of cards, on which your
information is written
The information stays in the order you place it in until
you modify that order
Methods return a string or subset of the list or modify
the list to add or remove components
Written as var[index], index refers to order within set
(think card number, starting at 0)
You can step through lists as part of a loop
List Methods
Adding to the List
var[n] = object
replaces n with object
adds object to the end of the list
Removing from the List
var[n] = []
empties contents of card, but preserves order
removes card at n
removes n and returns its value
Lists in ArcToolbox
You will create lists:
Layers as inputs
Attributes to match
Arrays of objects
You will work with lists:
List of field names
List of selected features
Like a list, tuples are iterable arrays of objects
Tuples are immutable –
once created, unchangeable
To add or remove items, you must redeclare
Example uses of tuples
County Names
Land Use Codes
Ordered set of functions
Dictionaries are sets of key & value pairs
Allows you to identify values by a descriptive name instead of order in a list
Keys are unordered unless explicitly sorted
Keys are unique:
var[‘item’] = “apple”
var[‘item’] = “banana”
print var[‘item’] prints just banana
Indentation and Blocks
Python uses whitespace and indents to denote blocks of code
Lines of code that begin a block end in a colon:
Lines within the code block are indented at the same level
To end a code block, remove the indentation
You’ll want blocks of code that run only when certain conditions are met
Conditional Branching
if and else
if variable == condition:
#do something based on v == c
#do something based on v != c
elif allows for additional branching
if condition:
another condition:

else: #none of the above

Looping with For
For allows you to loop over a block of code a set number of times
For is great for manipulating lists:
a = [‘cat’, ‘window’, ‘defenestrate’]
for x in a:
print x, len(x)
cat 3
window 6
defenestrate 12

Looping with For
We could use a for loop to perform geoprocessing tasks on each layer in a list
We could get a list of features in a feature class and loop over each, checking
Anything in a sequence or list can be used in a For loop
Just be sure not to modify the list while looping
Modules are additional pieces of code that further extend Python’s
A module typically has a specific function
additional math functions, databases, network…
Python comes with many useful modules
arcgisscripting is the module we will use to load ArcGIS toolbox functions into

Modules are accessed using import
import sys, os # imports two modules
Modules can have subsets of functions
os.path is a subset within os
Modules are then addressed by modulename.function()
sys.argv # list of arguments
filename = os.path.splitext(“points.txt”)
filename[1] # equals “.txt”
Files are manipulated by creating a file object
f = open(“points.txt”, “r”)
The file object then has new methods
print f.readline() # prints line from file
Files can be accessed to read or write
f = open(“output.txt”, “w”)
f.write(“Important Output!”)
Files are iterable objects, like lists
Error Capture
Check for type assignment errors, items not in a list, etc.
Try & Except
a block of code that might have an error
code to execute if an error occurs in “try”
Allows for graceful failure
– important in ArcGIS

Install Anaconda
Datascience toolkit
Run the setup and install it
© 2021 ULaw and ULBS 29
Jupyter Notebook
IDE for runing Data Analytics experiments in Python
Data Format – .ipybn
Every Jupyter Notebook, with .ipybn extension, combines code with other rich
media, such as narrative text, images, mathematical equations, and so on.
Using Notebooks is now a major part of the data science workflow at
companies across the globe.
© 2021 ULaw and ULBS 30
Thank you
References and additional Python resources
Python Homepage
Dive Into Python
Learning Python, 3rd Edition
Getting Started Writing Geoprocessing Scripts
Available on ESRI’s support page

order now