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.

Selamat datang di kursus ini!

Mengimpor seluruh file teks

Mengimpor berkas teks baris demi baris

Pentingnya flat file dalam data science

Kuis cepat: apa sebenarnya flat file itu?

Mengapa kita menyukai flat file dan Zen of Python

Mengimpor flat file menggunakan NumPy

Menyesuaikan impor NumPy Anda

Mengimpor berbagai tipe data

Mengimpor berkas flat menggunakan pandas

Menggunakan pandas untuk mengimpor flat file sebagai DataFrame (1)

Menggunakan pandas untuk mengimpor flat file sebagai DataFrame (2)

Menyesuaikan impor pandas Anda

Pemikiran akhir tentang impor data

Introduction and flat files

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.

Introduction to other file types

Not so flat any more

Loading a pickled file

Listing sheets in Excel files

Importing sheets from Excel files

Customizing your spreadsheet import

Importing SAS/Stata files using pandas

How to import SAS7BDAT

Importing SAS files

Using read_stata to import Stata files

Importing Stata files

Importing HDF5 files

Using File to import HDF5 files

Using h5py to import HDF5 files

Extracting data from your HDF5 file

Importing MATLAB files

Loading .mat files

The structure of .mat in Python

Importing data from other file types

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.

Introduction to relational databases

Pop quiz: The relational model

Creating a database engine in Python

Creating a database engine

What are the tables in the database?

Querying relational databases in Python

The Hello World of SQL Queries!

Customizing the Hello World of SQL Queries

Filtering your database records using SQL's WHERE

Ordering your SQL records with ORDER BY

Querying relational databases directly with pandas

Pandas and The Hello World of SQL Queries!

Pandas for more complex querying

Advanced querying: exploiting table relationships

The power of SQL lies in relationships between tables: INNER JOIN

Filtering your INNER JOIN

Final Thoughts

Working with relational databases in Python

Chinook (SQLite)

LIGO (HDF5)

Battledeath (XLSX)

Extent of infectious diseases (DTA)

Gene expressions (MATLAB)

MNIST

Sales (SAS7BDAT)

Seaslugs

Titanic

Course Glossary

Sebagai data scientist, Anda perlu membersihkan data, melakukan wrangling dan munging, memvisualisasikan, membangun model prediktif, serta menafsirkan model tersebut. Namun sebelum itu, Anda harus mengetahui cara memasukkan data ke dalam Python. Di kursus ini, Anda akan mempelajari berbagai cara mengimpor data ke Python: dari flat file seperti .txt dan .csv; dari file yang berasal dari perangkat lunak lain seperti spreadsheet Excel, serta file Stata, SAS, dan MATLAB; serta dari basis data relasional seperti SQLite dan PostgreSQL.

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Intermediate Python

Anda akan belajar cara membaca data ke Python: dari file CSV, spreadsheet Excel, hingga database SQLite & PostgreSQL.

Pengantar Mengimpor Data di Python

Pelajari cara mengimpor data ke dalam Python dari berbagai sumber, seperti Excel, SQL, SAS, dan langsung dari web.

Mengimpor flat file menggunakan NumPy

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