Publications by Rongen Zhang
UnstructuredDataMgmt-Summer2021-Lab2
CIS 4730Unstructured Data Management Lab: Data types Rongen Zhang Recap The RStudio environment Basic operators Basic data types Define variables variable_name <- some_value target <- data Agenda Advanced data types Vector List Matrix Data frame R Data Types Numeric Character Logic Factor Vector: a set of values, all of the same data typ...
4600 sym R (6780 sym/135 pcs)
Web Crawling
CIS 4730Unstructured Data Management Lab: Web scraping Rongen Zhang Getting data from the Web There are many ways to obtain data from the Internet; let’s consider four categories: click-and-download on the internet as a “flat” file, such as .csv, .xls install-and-play an API for which someone has written a handy R package API-query publi...
4951 sym R (15709 sym/30 pcs)
Publish Document
CIS 4730Unstructured Data Management Lab: Web scraping Rongen Zhang Getting data from the Web There are many ways to obtain data from the Internet; let’s consider four categories: click-and-download on the internet as a “flat” file, such as .csv, .xls install-and-play an API for which someone has written a handy R package API-query publi...
4951 sym R (15713 sym/30 pcs)
Lab 05 Data Manipulation
CIS 4730Unstructured Data Management Lab: Data manipulation Rongen Zhang The tidyverse The tidyverse is a collection of R packages designed for data science. https://www.tidyverse.org/ Install the complete tidyverse with: install.packages("tidyverse") Load the tidyverse into the R environment library(tidyverse) ## ── Attaching package...
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CIS 4730 - Lab 03
CIS 4730Unstructured Data Management Lab: Data input, output, and summary Rongen Zhang Agenda Data input Data output Data summary Summarizing data with figures Getting data into R Importing data into R is fairly simple. We can use built-in functions or libraries to read data from the following sources: Text file (.txt) Comma-separated values...
6663 sym R (10506 sym/50 pcs) 14 img
Lab 04 Flow Control
CIS 4730 Unstructured Data Management Lab: Flow control Rongen Zhang Flow control if-else for while function if-else An if statement consists of a logic condition (TRUE or FALSE) followed by one or more statements. # Template in words if(a logic condition) { Get inside the curly brackets and run this block when the condition is true } #...
3378 sym R (2911 sym/37 pcs) 1 tbl
Lab 06 Text Processing
CIS 4730Unstructured Data Management Lab: Text processing Rongen Zhang Agenda String manipulation Regular expression Package stringr The stringr package provides a cohesive set of functions designed to make working with strings as easy as possible. stringr is included in the tidyverse but it is not loaded automatically with library(tidyverse)...
5353 sym R (4260 sym/89 pcs)
Classification and Clustering
CIS 4730Unstructured Data Management Text Classification and Clustering Rongen Zhang Text Classification and Clustering Supervised Learning: Text classification k-nearest neighbor (KNN) Support vector machine (SVM) Unsupervised Learning: Text clustering K-means Hierarchical clustering Data for this lab session We will use the iris data set...
3115 sym R (6313 sym/37 pcs) 7 img
Web Crawling
CIS 4730Unstructured Data Management Lab: Web scraping Rongen Zhang Getting data from the Web There are many ways to obtain data from the Internet; let’s consider four categories: click-and-download on the internet as a “flat” file, such as .csv, .xls install-and-play an API for which someone has written a handy R package API-query publi...
4929 sym R (14230 sym/29 pcs) 1 img
Lab 03 Data Input Output and Summary
CIS 4730Unstructured Data Management Lab: Data input, output, and summary Rongen Zhang Agenda Data input Data output Data summary Summarizing data with figures Getting data into R Importing data into R is fairly simple. We can use built-in functions or libraries to read data from the following sources: Text file (.txt) Comma-separated values...
6639 sym R (10181 sym/48 pcs) 14 img