Hands-on data preprocessing in Python learn how to effectively prepare data for successful data analytics
Get your raw data cleaned up and ready for processing to design better data analytic solutions Key Features Develop the skills to perform data cleaning, data integration, data reduction, and data transformation Make the most of your raw data with powerful data transformation and massaging techniques...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing
[2022]
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009645695906719 |
Tabla de Contenidos:
- Table of Contents Review of the Core Modules of NumPy and Pandas Review of Another Core Module - Matplotlib Data – What Is It Really? Databases Data Visualization Prediction Classification Clustering Analysis Data Cleaning Level I - Cleaning Up the Table Data Cleaning Level II - Unpacking, Restructuring, and Reformulating the Table Data Cleaning Level III- Missing Values, Outliers, and Errors Data Fusion and Data Integration Data Reduction Data Transformation and Massaging Case Study 1 - Mental Health in Tech Case Study 2 - Predicting COVID-19 Hospitalizations Case Study 3: United States Counties Clustering Analysis Summary, Practice Case Studies, and Conclusions.
