# R - Data Table

### Table of Contents

## About

A data table is an enhanced data.frame.

data.tables (and data.frames) are internally lists as well, but with all its columns of equal length and with a class attribute.

## Articles Related

## Create

- data.table function

```
DT = data.table(
ID = c("b","b","b","a","a","c"),
a = 1:6,
b = 7:12,
c = 13:18)
```

- fread()

## Syntax

- Take DT, filter rows using i, then calculate j, grouped by by.

```
DT[i, j, (by|keyby)]
DT[ i, j, by ] # + extra arguments
| | |
| | -------> grouped by what?
| -------> what to do?
---> on which rows?
```

R | SQL |
---|---|

i | where (subset, filtering) and order with the order() function |

j | select columns * the data.table way: DT[, .(colA, colB)] * the data.frame way: DT[, c(“colA”, “colB”), with = FALSE] |

j | compute DT[, .(sumA = sum(colA), meanB = mean(colB))] |

by | group by |

keyby | group by ordered |

### Filter (Subset)

- Columns can be referred to as if they are variables. In data.frames a comma at the end is necessary but not here

`ans <- flights[origin == "JFK" & month == 6L]`

- Indexing. Get the first two rows from flights.

`ans <- flights[1:2]`

### Order

#### Without group by

Sort flights first by column origin in ascending order, and then by dest in descending order

`ans <- flights[order(origin, -dest)]`

#### With group by

- data.table retains the original order of groups (by design) but we can force it with the keyby keyword.

```
flights[carrier == "AA",
.(mean(arr_delay), mean(dep_delay)),
keyby = .(origin, dest, month)]
```

keyby() is applied after performing the operation, i.e., on the computed result and sets a key after ordering by setting an attribute called sorted.

### Select

- Select one column

```
# return it as a vector.
ans <- flights[, arr_delay]
# return as a data.table
ans <- flights[, list(arr_delay)]
ans <- flights[, .(arr_delay)] # The point is an alias to list.
```

- Select two columns

`ans <- flights[, .(arr_delay, dep_delay)]`

- Specify alias (ie rename them)

`ans <- flights[, .(delay_arr = arr_delay, delay_dep = dep_delay)]`

### Compute

- How many trips have had total delay < 0?. Computation gets by default the name Vn (ie V1, V2,…)

`ans <- flights[, sum((arr_delay + dep_delay) < 0)]`

- Calculate the average arrival and departure delay for all flights with “JFK” as the origin airport in the month of June.

```
ans <- flights[origin == "JFK" & month == 6L,
.(m_arr = mean(arr_delay), m_dep = mean(dep_delay))]
```

- How many trips have been made in 2014 from “JFK” airport in the month of June?

```
ans <- flights[origin == "JFK" & month == 6L, length(dest)] # length = count (can have any argument)
ans <- flights[origin == "JFK" & month == 6L, .N] #.N is an alias for length
```

### Grouping

- the number of trips corresponding to each origin airport?

`ans <- flights[, .(.N), by = .(origin)]`

* the number of trips for each origin airport for carrier code “AA”

`ans <- flights[carrier == "AA", .N, by = origin]`

- the total number of trips for each origin, dest pair for carrier code “AA”

`ans <- flights[carrier == "AA", .N, by = .(origin,dest)]`

- the average arrival and departure delay for each orig,dest pair for each month for carrier code “AA”

```
ans <- flights[carrier == "AA",
.(mean(arr_delay), mean(dep_delay)),
by = .(origin, dest, month)]
```

- Expression in the group by statement (output will be two boolean columns)

`ans <- flights[, .N, .(dep_delay>0, arr_delay>0)]`

### Subset of Data (Partition)

.SD for Subset of Data:

- is a data.table that holds the data for the current group defined using by.
- contains all the columns except the grouping columns by default.
- preserves the original order

Example:

- print

`DT[, print(.SD), by = col]`

- compute on (multiple) columns with lapply.

`DT[, lapply(.SD, mean), by = ID]`

- specify the SD columns (By default, it contains all the columns other than the grouping variables)

```
flights[carrier == "AA", ## Only on trips with carrier "AA"
lapply(.SD, mean), ## compute the mean
by = .(origin, dest, month), ## for every 'origin,dest,month'
.SDcols = c("arr_delay", "dep_delay")] ## for just those specified in .SDcols
```

- the first two rows for each month?

`ans <- flights[, head(.SD, 2), by = month]`

### Chaining

- Group by + order by

`ans <- flights[carrier == "AA", .N, by = .(origin, dest)][order(origin, -dest)]`

- The expression can also be chained vertically.

```
DT[ ...
][ ...
][ ...
]
```