Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools
David Mertz
Informasi Umum
Kode
22.21.428
Klasifikasi
005.7 - Data in Computer Systems
Jenis
Buku - Elektronik (E-Book)
Subjek
Data Analysis
No. Rak
3
Dilihat
5 kali
Informasi Lainnya
Abstraksi
Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way.
In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with.
Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for
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Pengarang
| Nama | David Mertz |
| Jenis | Perorangan |
| Penyunting | |
| Penerjemah |
Penerbit
| Nama | Packt Publishing Ltd |
| Kota | UK |
| Tahun | 2021 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
