The structure of data frames

Data frame construction 



# First create a few vectors from which we construct the data frame:
population  <- c(55619400,1885400,5424800,3125000)
area.sq.m   <- c(50301,5460,30090,8023)
GVA.cap     <- c(28096,20000,24800,19900)
# then we use 'data.frame' to construct the data frame:
UK <- data.frame(population,area.sq.m,GVA.cap)
UK

  population area.sq.m GVA.cap
1 55619400   50301     28096
2  1885400    5460     20000
3  5424800   30090     24800
4  3125000    8023     19900



names(UK)
names(UK) <- c("Population","Area","GVA")
UK

[1] "population" "area.sq.m"  "GVA.cap"

  Population Area  GVA
1 55619400   50301 28096
2  1885400    5460 20000
3  5424800   30090 24800
4  3125000    8023 19900



row.names(UK)

[1] "1" "2" "3" "4"



row.names(UK) <- c("England",
                   "Northern Ireland",
                   "Scotland",
                   "Wales")
UK

                 Population Area  GVA
England          55619400   50301 28096
Northern Ireland  1885400    5460 20000
Scotland          5424800   30090 24800
Wales             3125000    8023 19900



# It is also possible to set the names and row names in the data frame explicitly, when this
# appears more convenient:
UK <- data.frame(
           Population = c(55619400,1885400,5424800,3125000),
           Area = c(50301,5460,30090,8023),
           GVA = c(28096,20000,24800,19900),
           row.names = c("England",
                         "Northern Ireland",
                         "Scotland",
                         "Wales"))
UK

                 Population Area  GVA
England          55619400   50301 28096
Northern Ireland  1885400    5460 20000
Scotland          5424800   30090 24800
Wales             3125000    8023 19900



nrow(UK)

[1] 4



ncol(UK)

[1] 3



dim(UK)

[1] 4 3

In what follows we treat the data frame ‘UK’ as a list: 



# Here we get the variable 'Population':
UK$Population

[1] 55619400  1885400  5424800  3125000



# Analoguously, one can use the double bracket-operator ('[[]]')
# to get the variable 'Population':
UK[["Population"]]

[1] 55619400  1885400  5424800  3125000



# Also the single bracket-operator works as with lists.
# We get a data frame of the first two variables in
# the data frame
UK[1:2]

                 Population Area
England          55619400   50301
Northern Ireland  1885400    5460
Scotland          5424800   30090
Wales             3125000    8023



# Now we get a data frame with the variables named 'Population' and
# 'GVA'
UK[c("Population","GVA")]

                 Population GVA
England          55619400   28096
Northern Ireland  1885400   20000
Scotland          5424800   24800
Wales             3125000   19900

In the next few lines show the selection of rows and columns of a data frame 



# We select the first two rows of the
# data frame 'UK' by just using their numbers:
UK[1:2,]

                 Population Area  GVA
England          55619400   50301 28096
Northern Ireland  1885400    5460 20000



# By referring to row names, we select Scotland and Wales:
UK[c("Scotland","Wales"),]

         Population Area  GVA
Scotland 5424800    30090 24800
Wales    3125000     8023 19900



# As in a previous example, we select the first two columns ...
UK[,1:2]

                 Population Area
England          55619400   50301
Northern Ireland  1885400    5460
Scotland          5424800   30090
Wales             3125000    8023



# and the variables named 'Population' and 'GVA'
UK[,c("Population","GVA")]

                 Population GVA
England          55619400   28096
Northern Ireland  1885400   20000
Scotland          5424800   24800
Wales             3125000   19900

Downloadable R script and interactive version

Explanation

The link with the “jupyterhub” icon directs you to an interactive Jupyter1 notebook, which runs inside a Docker container2. There are two variants of the interative notebook. One shuts down after 60 seconds and does not require a sign it. The other requires sign in using your ORCID3 credentials, yet shuts down only after 24 hours. (There is no guarantee that such a container persists that long, it may be shut down earlier for maintenance purposes.) After shutdown all data within the container will be reset, i.e. all files created by the user will be deleted.4

Above you see a rendered version of the Jupyter notebook.5

1

For more information about Jupyter see http://jupyter.org. The Jupyter notebooks make use of the IRKernel package.

2

For more information about Docker see https://docs.docker.com/. The container images were created with repo2docker, while containers are run with docker spawner.

3

ORCID is a free service for the authentication of researchers. It also allows to showcase publications and contributions to the academic community such as peer review.. See https://info.orcid.org/what-is-orcid/ for more information.

4

The Jupyter notebooks come with NO WARRANTY whatsoever. They are provided for educational and illustrative purposes only. Do not use them for production work.

5

The notebook is rendered with the help of the nbsphinx extension.