Visão Geral

O curso de Programação em Python para Análise de Dados ensina aos analistas de dados como pesquisar, manipular e analisar dados usando a poderosa linguagem de programação Python.

Objetivo

Todos os alunos aprenderão a:

• Extrair dados de arquivos binários ou outros fluxos de dados binários
• Crie estruturas de dados usando classes e tuplas nomeadas
• Pesquise e substitua texto por expressões regulares
• Leia e grave CSV e outros formatos de dados
• Serialize dados para selecionar arquivos, JSON e XML
• Consumir e processar dados da Web
• Lidar com dados ausentes
• Compartilhe dados com planilhas do Excel
• Analisar dados com SciPy / NumPy

Materiais

Conteúdo Programatico

INTRODUCTION

FILE I/O

• Opening a file
• Iterating over lines
• Reading characters or bytes
• Reading all lines
• Formatted output
• Using fileinput

CLASSES

• Defining classes
• Constructors
• Instance methods and data
• Class/static methods and data

GENERATORS AND OTHER ITERABLES

• Iterables
• Saving memory with generators
• Generator expressions
• Generator functions
• Generator classes
• Stacking generators

DATA STRUCTURES

• How to store data
• The basics: lists and tuples
• Named access with dictionaries
• Named tuples: best of both worlds
• Using classes as data structures

SERIALIZING DATA

• Pickle
• JSON
• CSV
• XML

CONSUMING DATA FROM THE WEB

• Web data sources
• Data via URL
• RESTful data
• Screen-scraping

EXCEL SPREADSHEETS

• The xlrd, xlwr, and xlutil modules
• Reading an existing spreadsheet
• Creating a spreadsheet from scratch
• Modifying an existing spreadsheet

DATES AND TIMES

• Python date and time objects
• The time module
• Using calendars
• Converting between formats
• Parsing and printing
• Time zones

REGULAR EXPRESSIONS

• RE syntax overview
• Basic patterns
• RE objects
• Searching and matching
• Compilation flags
• Grouping
• Replacing text
• Splitting a string

WORKING WITH BINARY DATA

• Isn’t all data binary?
• Binary file handling
• Parsing raw data
• Writing a binary stream

ANALYZING DATASETS

• Sorting data
• Filtering values
• Basic statistics
• Leveraging SciPy/NumPy
• Using pandas

BIGGER DATA – WORKING WITH PYTABLES

• About HDF5 data
• Using PyTables
• Reading a dataset
• Pulling data
• Updating the dataset
• Writing to HDF5

CONCLUSION