Data & File Management in R - part 1 | R Programming Training & Certification | Uplatz

As we progress, we'll also cover practical examples and tips to ensure you can apply these techniques to real-world scenarios. From basic file operations to more advanced data manipulation, this video is packed with valuable insights to help you become proficient in R programming. Don't forget to subscribe to our channel for more in-depth tutorials and updates on our training series. Stay tuned for part two where we'll delve deeper into data cleaning and transformation techniques.

In R Programming, handling of files such as reading and writing files can be done by using in-built functions present in R base package. Managing directory from R becomes handy when automating batch processes, and helps with managing disk spaces when extracting and manipulating large volumes of data. Working with directories might be a cumbersome work for the first time users in R Programming. However, through this video, students will be well aware of all the functionalities involved in the data and file management in R.

Some of the key R functions are:
file_copy(), dir_copy(), link_copy(): Copy files, directories or links
file_create(), dir_create(), link_create(): Create files, directories, or links
file_delete(), dir_delete(), link_delete(): Delete files, directories, or links
file_access(), file_exists(), dir_exists(), link_exists(): Query for existence and access permissions
file_chmod(): Change file permissions
file_chown(): Change owner or group of a file
file_info(): Query file metadata
file_move(): Move or rename files

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Syllabus
1. Understanding of R System
2. Installation and configuration of R-Environment and R-Studio
3. Understanding R Packages, their installation and management
4. Understanding of nuts and bolts of R:
a. R program Structure
b. R Data Type, Command Syntax and Control Structures
c. File Operations in R
5. Application of R Programming in Daily life problems
6. Preparing Data in R
a. Data Cleaning
b. Data imputation
c. Data conversion
7. Visualizing data using R with different type of graphs and charts
8. Applying R Advance features to solve complex problems and finetuning R Processes

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