In this section, we will look at some basic characteristics of data and how to read, preprocess, and cleanse datasets. We have seen some of these aspects earlier in Chapter 3, Data Wrangling with R, and this section is intended to provide a high-level view of the relevant topics.
Preparing data for analysis
by Ricardo Anjoleto Farias, Nataraj Dasgupta, Vitor Bianchi Lanzetta
Hands-On Data Science with R
- Title Page
- Copyright and Credits
- About Packt
- Contributors
- Preface
- Getting Started with Data Science and R
- Descriptive and Inferential Statistics
- Data Wrangling with R
- Introduction to data wrangling with R
- Data extraction, transformation, and load
- Basic tools of data wrangling
- Using base R for data manipulation and analysis
- Applying families of functions 
- Using data.table for data manipulation
- Reading and writing files with data.table
- A special note on dates and/or time
- Miscellaneous topics
- Tutorial – looking at airline flight times data
- Summary
- Quiz
- KDD, Data Mining, and Text Mining
- Data Analysis with R
- Machine Learning with R
- Forecasting and ML App with R
- Neural Networks and Deep Learning
- Markovian in R
- Visualizing Data
- Going to Production with R
- Large Scale Data Analytics with Hadoop
- R on Cloud
- The Road Ahead
- Other Books You May Enjoy
Preparing data for analysis
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.