Walker Python Data Cleaning Cookbook

Modern techniques and Python tools to detect and remove dirty data and extract key insights
1. Auflage 2020
ISBN: 978-1-80056-459-6
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 436 Seiten

No detailed description available for "Python Data Cleaning Cookbook".

Autoren/Hrsg.

Walker, Michael

Walker, Michael B

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur

Inhaltsverzeichnis

Table of Contents - Anticipating Data Cleaning Issues when Importing Tabular Data into pandas
- Anticipating Data Cleaning Issues when Importing HTML and JSON into Pandas
- Taking the Measure of Your Data
- Identifying Issues in Subsets of Data
- Using Visualizations for Exploratory Data Analysis
- Cleaning and Wrangling Data with Pandas Data Series Operations
- Fixing Messy Data When Aggregating
- Addressing Data Issues When Combining Data Frames
- Tidying and Reshaping Data
- User Defined Functions and Classes to Automate Data Cleaning

Über Autor(innen)

Walker Michael:
Michael Walker has worked as a data analyst for over 30 years at a variety of educational institutions. He is currently the CIO at College Unbound in Providence, Rhode Island, in the United States. He has also taught data science, research methods, statistics, and computer programming to undergraduates since 2006.