EGY XXX a – Python for Statistics, Data
Analysis and Econometrics
Course outline (under review)
Part I
1
Introduction
1.1
Background
1.2
Conventions
1.3
Essential python scientific packages
1.4
Setup
1.5
Exercises
2
Built-in Data Types
2.1
Variable names and native data
types
2.2
Dates & Time
3
Arrays
3.1
Arrays: Single and multi-dimensional
3.2
Array processing
3.3
Importing functions through
packages and libraries
3.4
Calling Functions
4
Basic Mathematical operators
4.1
Operators (on scalars and
arrays: +, - ,* and /)
4.2
Exponentiation (**)
4.3
Parentheses
4.4
Transpose
4.5
Operator Precedence
5
Basic Functions and Numerical
Indexing
5.1
Array functions
5.2
Mathematical functions
5.3
Set functions
5.4
Sorting and extreme values
5.5
‘Not a number’ (NaN) functions
6
Importing and Exporting Data
6.1
Importing Data using pandas
6.2
Importing Data without pandas
6.3
Saving or Exporting Data using
pandas (and without)
7
Logical Operators and Find
7.1
>, >=, <, <=, ==,
!=
7.2
and, or,
not and xor
7.3
Multiple tests
7.4
is*
8
Flow Control, Loops and
Exception Handling
8.1
Whitespace and Flow Control
8.2
if : : : elif : : : else
8.3
for
8.4
while
8.5
try : : : except
9
Creating Function and Modules
9.1
Functions
9.2
Modules
10
Object-Oriented Programming
(OOP)
10.1 Introduction
10.2 Class basics
11
File System Operations
11.1 Changing the working directory
11.2 Creating and deleting directories
11.3 Listing the contents of a directory
11.4 Copying, moving
and deleting files
11.5 Executing other programs
11.6 Creating and opening archives
12
Reading and writing files
13
Graphics
13.1 seaborn library
13.2 2D Plotting
13.3 Advanced 2D Plotting
13.4 3D Plotting
13.5 General Plotting Functions
13.6 Exporting Plots
Part II
14
Statistical
data structure - pandas library
14.1 Data structures
14.2 Statistical functions
14.3 Time-series data
14.4 Importing and exporting data
14.5 Graphics
15
Probability and Statistics
Functions
15.1 Simulating random variables
15.2 Simulation and random number generation
15.3 Continuous random variables
15.4 Descriptive statistics functions
15.5 Statistical testing
16
Statistical Analysis with – statsmodels
library
16.1
Regression
16.2
Simple linear regression
16.3
Multiple linear regression
16.4
Statistical inference
16.5
Diagnostics and testing
16.6
Other models: Generalized linear models,
logistic regression