A dataset is not only used for storing information, but, usually, you also need to interact with it to find out useful information. Whenever the dataset has been stored in a database, the interactive process is more efficient in terms of memory and processing time. In this recipe, you will interact with a data table that has already been stored in a database in the PostgreSQL database server.
- Preface
- Installing and Configuring R and its Libraries
- Introduction
- Installing and configuring base R in Windows
- Installing and configuring base R in Linux
- Installing and configuring RStudio IDE in Windows
- Installing and configuring RStudio IDE in Linux
- Installing and configuring R tools for Visual Studio in Windows
- Installing R libraries from various sources
- Installing a specific version of R library
- Data Structures in R
- Introduction
- Creating a vector and accessing its properties
- Creating a matrix and accessing its properties
- Creating a data frame and accessing its properties
- Creating an array and accessing its properties
- Creating a list from a combination of vector, matrix, and data frame
- Converting a matrix to a data frame and a data frame to a matrix
- Writing Customized Functions
- Conditional and Iterative Operations
- Introduction
- The use of the if conditional statement
- The use of the if…else conditional operator
- The use of the ifelse vectorised conditional operator
- Writing a function using the switch operator
- Comparing the performance of switch and series of the if…else statements
- Using for loop for iterations
- Vectorised operation versus for loop
- R Objects and Classes
- Querying, Filtering, and Summarizing
- Introduction
- Using the pipe operator for data processing
- Efficient and fast summarization using the dplyr verbs
- Using the customized function within the dplyr verbs
- Using the select verb for data processing
- Using the filter verb for data processing
- Using the arrange verb for data processing
- Using mutate for data processing
- Using summarise to summarize dataset
- R for Text Processing
- Introduction
- Extracting unstructured text data from a plain web page
- Extracting text data from an HTML page
- Extracting text data from an HTML page using the XML library
- Extracting text data from PubMed
- Importing unstructured text data from a plain text file
- Importing plain text data from a PDF file
- Pre-processing text data for topic modeling and sentiment analysis
- Creating a word cloud to explore unstructured text data
- Using regular expression in text processing
- R and Databases
- Parallel Processing in R
Interacting with the PostgreSQL database from R
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.