Introduction

Python Fundamentals

Figure 1

Value of 65.0 with weight_kg label stuck on it

Figure 2

Value of 65.0 with weight_kg label stuck on it, and value of 143.0 with weight_lb label stuck on it

Figure 3

Value of 100.0 with label weight_kg stuck on it, and value of 143.0 with label weight_lbstuck on it

Data Transformation

Figure 1

'data' is a 3 by 3 numpy array containing row 0: ['A', 'B', 'C'], row 1: ['D', 'E', 'F'], androw 2: ['G', 'H', 'I']. Starting in the upper left hand corner, data[0, 0] = 'A', data[0, 1] = 'B',data[0, 2] = 'C', data[1, 0] = 'D', data[1, 1] = 'E', data[1, 2] = 'F', data[2, 0] = 'G',data[2, 1] = 'H', and data[2, 2] = 'I',in the bottom right hand corner.

List and Dictionary Methods

Loops and Conditional Logic

Figure 1

Line graphs showing average, maximum, and minimum inflammation across all patients over a 40-day period.

Figure 2

Loop variable 'num' being assigned the value of each element in the list odds in turn andthen being printed

Figure 3

A flowchart diagram of the if-else construct that tests if variable num is greater than 100

Figure 4

A flowchart diagram of a conditional section with multiple elif conditions and some > possible outcomes.

Figure 5

A flowchart diagram of a conditional section with multiple if statements and some possible outcomes.

Alternatives to Loops

Creating Functions

Figure 1

Labeled parts of a Python function definition

Data Analysis

Visualizations

Errors and Exceptions