Chapter 6 Data frames

(R data frames)

6.1 Overview

6.1.1 Abstract:

Introduction to data frames: how to create, and modify them and how to retrieve data.

6.1.2 Objectives:

This unit will:

introduce R data frames;
cover a number of basic operations.

6.1.3 Outcomes:

After working through this unit you:

know how to create and manipulate data frames;
can extract rows, columns, and append new data rows;

6.1.4 Deliverables:

Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.

Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don’t overlook these.

Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page.

6.1.5 Prerequisites

RPR-Objects-Vectors (R scalars and vectors)

6.2 Data frames

6.3 Task 16 - Basic operations

Load the R-Exercise_BasicSetup project in RStudio if you don’t already have it open. Type init() as instructed after the project has loaded. Continue below.

Data frames are probably the most important type of data object for bioinformatics in R; they emulate our mental model of data in a spreadsheet and can be used to implement entity-relationship datamodels.

Usually the result of reading external data from an input file is a data frame. The file below is included with the R-Exercise-BasicSetup project files - it is called plasmidData.tsv, and you can click on it in the Files Pane to open and inspect it.

plasmid

This data set uses tabs as column separators and it has a header line. Similar files can be exported from Excel or other spreadsheet programs.

Read this as a data frame as follows:

( plasmidData <- read.table(
                    file.path("data_files","plasmidData.tsv"),
                    sep="\t",
                    header=TRUE,
                    stringsAsFactors = FALSE) )

##       Name Size   Marker   Ori
## 1    pUC19 2686      Amp ColE1
## 2   pBR322 4361 Amp, Tet ColE1
## 3 pACYC184 4245 Tet, Cam  p15A
##                                           Sites
## 1 EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII
## 2                          EcoRI, ClaI, HindIII
## 3                                 ClaI, HindIII

objectInfo(plasmidData)

## object contents:      Name Size   Marker   Ori
## 1    pUC19 2686      Amp ColE1
## 2   pBR322 4361 Amp, Tet ColE1
## 3 pACYC184 4245 Tet, Cam  p15A
##                                           Sites
## 1 EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII
## 2                          EcoRI, ClaI, HindIII
## 3                                 ClaI, HindIII
## 
## structure of object:
## 'data.frame':    3 obs. of  5 variables:
##  $ Name  : chr  "pUC19" "pBR322" "pACYC184"
##  $ Size  : int  2686 4361 4245
##  $ Marker: chr  "Amp" "Amp, Tet" "Tet, Cam"
##  $ Ori   : chr  "ColE1" "ColE1" "p15A"
##  $ Sites : chr  "EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII" "EcoRI, ClaI, HindIII" "ClaI, HindIII"
## 
## attributes:

## $names
## [1] "Name"   "Size"   "Marker" "Ori"    "Sites" 
## 
## $class
## [1] "data.frame"
## 
## $row.names
## [1] 1 2 3

Note the argument stringsAsFactors = FALSE. If this is TRUE instead, R will convert all strings in the input to factors and this may lead to problems. Make it a habit to turn this behaviour off, you can always turn a column of strings into factors when you actually mean to have factors.

You can view the data frame contents by clicking on the spreadsheet icon behind its name in the Environment Pane.

plasmid

6.4 Basic operations

Here are some basic operations with the data frame. Try them and experiment. If you break it by mistake, you can just recreate it by reading the source file again:

use column 1 as rownames

rownames(plasmidData) <- plasmidData[ , 1]

nrow(plasmidData)

## [1] 3

ncol(plasmidData)

## [1] 5

objectInfo(plasmidData)

## object contents:             Name Size   Marker   Ori
## pUC19       pUC19 2686      Amp ColE1
## pBR322     pBR322 4361 Amp, Tet ColE1
## pACYC184 pACYC184 4245 Tet, Cam  p15A
##                                                  Sites
## pUC19    EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII
## pBR322                            EcoRI, ClaI, HindIII
## pACYC184                                 ClaI, HindIII
## 
## structure of object:
## 'data.frame':    3 obs. of  5 variables:
##  $ Name  : chr  "pUC19" "pBR322" "pACYC184"
##  $ Size  : int  2686 4361 4245
##  $ Marker: chr  "Amp" "Amp, Tet" "Tet, Cam"
##  $ Ori   : chr  "ColE1" "ColE1" "p15A"
##  $ Sites : chr  "EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII" "EcoRI, ClaI, HindIII" "ClaI, HindIII"
## 
## attributes:

## $names
## [1] "Name"   "Size"   "Marker" "Ori"    "Sites" 
## 
## $class
## [1] "data.frame"
## 
## $row.names
## [1] "pUC19"    "pBR322"   "pACYC184"

assign one row to a variable. This is also a data frame! One row. It has to be, because it contains elements of type chr and of type int!

x <- plasmidData[2, ]
objectInfo(x)

## object contents:         Name Size   Marker   Ori                Sites
## pBR322 pBR322 4361 Amp, Tet ColE1 EcoRI, ClaI, HindIII
## 
## structure of object:
## 'data.frame':    1 obs. of  5 variables:
##  $ Name  : chr "pBR322"
##  $ Size  : int 4361
##  $ Marker: chr "Amp, Tet"
##  $ Ori   : chr "ColE1"
##  $ Sites : chr "EcoRI, ClaI, HindIII"
## 
## attributes:

## $names
## [1] "Name"   "Size"   "Marker" "Ori"    "Sites" 
## 
## $row.names
## [1] "pBR322"
## 
## $class
## [1] "data.frame"

retrieve one row: different syntax, same thing

plasmidData["pBR322", ]

##          Name Size   Marker   Ori                Sites
## pBR322 pBR322 4361 Amp, Tet ColE1 EcoRI, ClaI, HindIII

retrieve one column - two different methods

plasmidData[ , 2]

## [1] 2686 4361 4245

plasmidData[ , "Size"]

## [1] 2686 4361 4245

remove one row

plasmidData <- plasmidData[-2, ]
objectInfo(plasmidData)

## object contents:             Name Size   Marker   Ori
## pUC19       pUC19 2686      Amp ColE1
## pACYC184 pACYC184 4245 Tet, Cam  p15A
##                                                  Sites
## pUC19    EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII
## pACYC184                                 ClaI, HindIII
## 
## structure of object:
## 'data.frame':    2 obs. of  5 variables:
##  $ Name  : chr  "pUC19" "pACYC184"
##  $ Size  : int  2686 4245
##  $ Marker: chr  "Amp" "Tet, Cam"
##  $ Ori   : chr  "ColE1" "p15A"
##  $ Sites : chr  "EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII" "ClaI, HindIII"
## 
## attributes:

## $names
## [1] "Name"   "Size"   "Marker" "Ori"    "Sites" 
## 
## $row.names
## [1] "pUC19"    "pACYC184"
## 
## $class
## [1] "data.frame"

add it back at the end

plasmidData <- rbind(plasmidData, x)  
objectInfo(plasmidData)

## object contents:             Name Size   Marker   Ori
## pUC19       pUC19 2686      Amp ColE1
## pACYC184 pACYC184 4245 Tet, Cam  p15A
## pBR322     pBR322 4361 Amp, Tet ColE1
##                                                  Sites
## pUC19    EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII
## pACYC184                                 ClaI, HindIII
## pBR322                            EcoRI, ClaI, HindIII
## 
## structure of object:
## 'data.frame':    3 obs. of  5 variables:
##  $ Name  : chr  "pUC19" "pACYC184" "pBR322"
##  $ Size  : int  2686 4245 4361
##  $ Marker: chr  "Amp" "Tet, Cam" "Amp, Tet"
##  $ Ori   : chr  "ColE1" "p15A" "ColE1"
##  $ Sites : chr  "EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII" "ClaI, HindIII" "EcoRI, ClaI, HindIII"
## 
## attributes:

## $names
## [1] "Name"   "Size"   "Marker" "Ori"    "Sites" 
## 
## $row.names
## [1] "pUC19"    "pACYC184" "pBR322"  
## 
## $class
## [1] "data.frame"

add a new row from scratch:

plasmidData <- rbind(plasmidData, 
                     data.frame(Name = "pMAL-p5x", Size = 5752,
                                Marker = "Amp",Ori = "pMB1",
                                Sites = "SacI, AvaI, ..., HindIII",
                                stringsAsFactors = FALSE))
objectInfo(plasmidData)

## object contents:             Name Size   Marker   Ori
## pUC19       pUC19 2686      Amp ColE1
## pACYC184 pACYC184 4245 Tet, Cam  p15A
## pBR322     pBR322 4361 Amp, Tet ColE1
## 1        pMAL-p5x 5752      Amp  pMB1
##                                                  Sites
## pUC19    EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII
## pACYC184                                 ClaI, HindIII
## pBR322                            EcoRI, ClaI, HindIII
## 1                             SacI, AvaI, ..., HindIII
## 
## structure of object:
## 'data.frame':    4 obs. of  5 variables:
##  $ Name  : chr  "pUC19" "pACYC184" "pBR322" "pMAL-p5x"
##  $ Size  : num  2686 4245 4361 5752
##  $ Marker: chr  "Amp" "Tet, Cam" "Amp, Tet" "Amp"
##  $ Ori   : chr  "ColE1" "p15A" "ColE1" "pMB1"
##  $ Sites : chr  "EcoRI, SacI, SmaI, BamHI, XbaI, PstI, HindIII" "ClaI, HindIII" "EcoRI, ClaI, HindIII" "SacI, AvaI, ..., HindIII"
## 
## attributes:

## $names
## [1] "Name"   "Size"   "Marker" "Ori"    "Sites" 
## 
## $row.names
## [1] "pUC19"    "pACYC184" "pBR322"   "1"       
## 
## $class
## [1] "data.frame"

6.5 Task 17 - modify data frame

The rowname of the new row of plasmidData is now “1”. It should be “pMAL-p5x”. Fix this.

6.6 Self-evaluation

6.7 Further reading, links and resources

If in doubt, ask!
If anything about this learning unit is not clear to you, do not proceed blindly but ask for clarification. Post your question on the course mailing list: others are likely to have similar problems. Or send an email to your instructor.

Author: Boris Steipe boris.steipe@utoronto.ca
Created: 2017-08-05
Modified: 2018-05-05
Version: 1.0.1
Version history:
1.0.1 Maintenance
1.0 Completed to first live version
0.1 Material collected from previous tutorial

6.7.1 Updated Revision history

Revision	Author	Date	Message
5152496	Ruth Isserlin	2019-12-25	Fixed issue with task numbering because of a remove all elements call in the 2nd chapter
fab47ae	Ruth Isserlin	2019-12-24	initial check in of R basics book

BCB420 - Computational System Biology