R DATA STRUCTURES 2
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Multi-mode data structures like lists and data frames allow R to store different data types together. Lists are containers that can hold any R object and are created using the list function. Data frames are a special type of list that can only hold vectors of the same length and are created using the data.frame function. Both lists and data frames can be subscripted and referenced using names, integer indices, logical vectors, and character strings to select elements.
![LISTS
Multi-mode data structures are required to manipulate data containing different types of
data elements e.g. CSVs, RDBMS tables, Excel sheets etc.
Definition
Container for any type of R objects
Creation
Using list function
Naming elements is optional
Original objects are copied
Can be avoided by creating objects on fly
Referencing elements
Using name
[[]]
[]](https://image.slidesharecdn.com/rmultimodeds-161124200107/85/R-DATA-STRUCTURES-2-2-320.jpg)
![LISTS
Subscripting or Referencing
Blanks
Positive / Negative
Logical
Character
Difference between [[]] and []
LIST$ELEMENT is same as LIST[[ELEMENT_IDX]]
Adding new elements to list via $ or [[x]]
Combining lists](https://image.slidesharecdn.com/rmultimodeds-161124200107/85/R-DATA-STRUCTURES-2-4-320.jpg)
![DATA FRAME
Subscripting or Referencing
DATAFRAME$VECTOR
All vector subscripting paradigms apply
Referencing as a matrix
Specification
Blank [] : all elements
Positive integers: keep those elements
Negative integers: drop those elements return rest
Logical: keep only those which are TRUE in position
Character: keep whose names are specified
Without the , DATAFRAME[spec]
Return all rows but specified columns
Preserving the dimensions (drop = F)](https://image.slidesharecdn.com/rmultimodeds-161124200107/85/R-DATA-STRUCTURES-2-7-320.jpg)
![DATA FRAME
Subscripting or Referencing
DATAFRAME$VECTOR
All vector subscripting paradigms apply
Referencing as a matrix
Specification
Blank [] : all elements
Positive integers: keep those elements
Negative integers: drop those elements return rest
Logical: keep only those which are TRUE in position
Character: keep whose names are specified
Without the , DATAFRAME[spec]
Return all rows but specified columns](https://image.slidesharecdn.com/rmultimodeds-161124200107/85/R-DATA-STRUCTURES-2-8-320.jpg)
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R DATA STRUCTURES 2
- 2. LISTS Multi-mode data structures are required to manipulate data containing different types of data elements e.g. CSVs, RDBMS tables, Excel sheets etc. Definition Container for any type of R objects Creation Using list function Naming elements is optional Original objects are copied Can be avoided by creating objects on fly Referencing elements Using name [[]] []
- 3. LISTS Attributes Length Names Mode
- 4. LISTS Subscripting or Referencing Blanks Positive / Negative Logical Character Difference between [[]] and [] LIST$ELEMENT is same as LIST[[ELEMENT_IDX]] Adding new elements to list via $ or [[x]] Combining lists
- 5. LISTS Paradigms (how to use R lists) List-apply (lapply) maps a function over a vector returning each return value as an element of an unnamed list Simple-apply (sapply) maps a function over a vector returning each return value as an element of a vector Most functions return output in form of named list
- 6. DATA FRAME Definition Named list that can hold only vectors of same length Creation Using data.frame function passing vectors Attributes Mode Length Names Adding new columns to a data frame
- 7. DATA FRAME Subscripting or Referencing DATAFRAME$VECTOR All vector subscripting paradigms apply Referencing as a matrix Specification Blank [] : all elements Positive integers: keep those elements Negative integers: drop those elements return rest Logical: keep only those which are TRUE in position Character: keep whose names are specified Without the , DATAFRAME[spec] Return all rows but specified columns Preserving the dimensions (drop = F)
- 8. DATA FRAME Subscripting or Referencing DATAFRAME$VECTOR All vector subscripting paradigms apply Referencing as a matrix Specification Blank [] : all elements Positive integers: keep those elements Negative integers: drop those elements return rest Logical: keep only those which are TRUE in position Character: keep whose names are specified Without the , DATAFRAME[spec] Return all rows but specified columns
- 9. END NOTES Matrices and arrays are essentially vectors with dimensions Thus they can be morphed into one another
Editor's Notes
- #3: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.
- #4: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.
- #5: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.
- #6: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.
- #7: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.
- #8: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.
- #9: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.
- #10: For effectively using R for gaining insights from data one needs to have working knowledge of the standard data types and data structures in R.