Planeamento

Aulas

Introduction

1

About this course, syllabus, assessment and bibliography
Introduction to data science with python
Programming environments
  • iPython
  • Jupyter notebook

Introduction to Python

2

Introduction to Python
  • Data types
  • data structures
  • functions and objects in python
Homework assignent

The basics of NumPy arrays

3

Numpy arrays
  • usage
  • array slicing
  • useful methods

Pandas and its data structures

4

Introducing Pandas and its main data structures

Pandas: loading, structuring and saving data

5

Pandas: loading, structuring and saving data

Operating on data and dealing with missing data

6

Operating on data and dealing with missing data

Intermediate Test

7

Intermediate Test

Hierarchical indexing

8

Hierarchical indexing
Introducing the Project assignment

Combining datasets

9

Combining datasets: concat, merge

Data aggregation and grouping, and Pivot Tables

10

Data aggregation and grouping
Pivot Tables

Vectorized string operations, sample plots

11

Vectorized string operations
Sample plots with matplotlib

Practical examples and Questions

12

Practical examples
Questions about the Project

Project support

13

Questions about the project

Working with time series

14

Statistical and predictive analysis
Working with time series

Project support

15

Questions about the Project

Project presentation: oral assessment

16

Project presentation: oral assessment