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InicioPythonIntroduction to Importing Data in Python

Introduction to Importing Data in Python

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

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Descripción del curso

As a data scientist, you will need to clean data, wrangle and munge it, visualize it, build predictive models, and interpret these models. Before you can do so, however, you will need to know how to get data into Python. In this course, you'll learn the many ways to import data into Python: from flat files such as .txt and .csv; from files native to other software such as Excel spreadsheets, Stata, SAS, and MATLAB files; and from relational databases such as SQLite and PostgreSQL.
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  1. 1

    Introduction and flat files

    Gratuito

    In this chapter, you'll learn how to import data into Python from all types of flat files, which are a simple and prevalent form of data storage. You've previously learned how to use NumPy and pandas—you will learn how to use these packages to import flat files and customize your imports.

    Reproducir Capítulo Ahora
    Welcome to the course!
    50 xp
    Exploring your working directory
    50 xp
    Importing entire text files
    100 xp
    Importing text files line by line
    100 xp
    The importance of flat files in data science
    50 xp
    Pop quiz: examples of flat files
    50 xp
    Pop quiz: what exactly are flat files?
    50 xp
    Why we like flat files and the Zen of Python
    50 xp
    Importing flat files using NumPy
    50 xp
    Using NumPy to import flat files
    100 xp
    Customizing your NumPy import
    100 xp
    Importing different datatypes
    100 xp
    Working with mixed datatypes (1)
    50 xp
    Working with mixed datatypes (2)
    100 xp
    Importing flat files using pandas
    50 xp
    Using pandas to import flat files as DataFrames (1)
    100 xp
    Using pandas to import flat files as DataFrames (2)
    100 xp
    Customizing your pandas import
    100 xp
    Final thoughts on data import
    50 xp
  2. 2

    Importing data from other file types

    You've learned how to import flat files, but there are many other file types you will potentially have to work with as a data scientist. In this chapter, you'll learn how to import data into Python from a wide array of important file types. These include pickled files, Excel spreadsheets, SAS and Stata files, HDF5 files, a file type for storing large quantities of numerical data, and MATLAB files.

    Reproducir Capítulo Ahora
    Introduction to other file types
    50 xp
    Not so flat any more
    50 xp
    Loading a pickled file
    100 xp
    Listing sheets in Excel files
    100 xp
    Importing sheets from Excel files
    100 xp
    Customizing your spreadsheet import
    100 xp
    Importing SAS/Stata files using pandas
    50 xp
    How to import SAS7BDAT
    50 xp
    Importing SAS files
    100 xp
    Using read_stata to import Stata files
    50 xp
    Importing Stata files
    100 xp
    Importing HDF5 files
    50 xp
    Using File to import HDF5 files
    50 xp
    Using h5py to import HDF5 files
    100 xp
    Extracting data from your HDF5 file
    100 xp
    Importing MATLAB files
    50 xp
    Loading .mat files
    100 xp
    The structure of .mat in Python
    100 xp
  3. 3

    Working with relational databases in Python

    In this chapter, you'll learn how to extract meaningful data from relational databases, an essential skill for any data scientist. You will learn about relational models, how to create SQL queries, how to filter and order your SQL records, and how to perform advanced queries by joining database tables.

    Reproducir Capítulo Ahora
    Introduction to relational databases
    50 xp
    Pop quiz: The relational model
    50 xp
    Creating a database engine in Python
    50 xp
    Creating a database engine
    100 xp
    What are the tables in the database?
    100 xp
    Querying relational databases in Python
    50 xp
    The Hello World of SQL Queries!
    100 xp
    Customizing the Hello World of SQL Queries
    100 xp
    Filtering your database records using SQL's WHERE
    100 xp
    Ordering your SQL records with ORDER BY
    100 xp
    Querying relational databases directly with pandas
    50 xp
    Pandas and The Hello World of SQL Queries!
    100 xp
    Pandas for more complex querying
    100 xp
    Advanced querying: exploiting table relationships
    50 xp
    The power of SQL lies in relationships between tables: INNER JOIN
    100 xp
    Filtering your INNER JOIN
    100 xp
    Final Thoughts
    50 xp
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Sets De Datos

Chinook (SQLite)LIGO (HDF5)Battledeath (XLSX)Extent of infectious diseases (DTA)Gene expressions (MATLAB)MNISTSales (SAS7BDAT)SeaslugsTitanic

Colaboradores

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Francisco Castro

Requisitos Previos

Intermediate Python
Hugo Bowne-Anderson HeadshotHugo Bowne-Anderson

Data Scientist

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