head
Get top rows of table, timetable, or tall array
Description
head(___)
displays the first eight, or the
first k
, rows of A
without returning a
value.
Examples
Return First Eight Rows of Table
Create a table by reading data from a spreadsheet. Display the size of the table, showing that it has 1468 rows.
T = readtable("outages.csv","TextType","string"); size(T)
ans = 1×2
1468 6
Return another table that has the first eight rows of T
.
T2 = head(T)
T2=8×6 table
Region OutageTime Loss Customers RestorationTime Cause
___________ ________________ ______ __________ ________________ _________________
"SouthWest" 2002-02-01 12:18 458.98 1.8202e+06 2002-02-07 16:50 "winter storm"
"SouthEast" 2003-01-23 00:49 530.14 2.1204e+05 NaT "winter storm"
"SouthEast" 2003-02-07 21:15 289.4 1.4294e+05 2003-02-17 08:14 "winter storm"
"West" 2004-04-06 05:44 434.81 3.4037e+05 2004-04-06 06:10 "equipment fault"
"MidWest" 2002-03-16 06:18 186.44 2.1275e+05 2002-03-18 23:23 "severe storm"
"West" 2003-06-18 02:49 0 0 2003-06-18 10:54 "attack"
"West" 2004-06-20 14:39 231.29 NaN 2004-06-20 19:16 "equipment fault"
"West" 2002-06-06 19:28 311.86 NaN 2002-06-07 00:51 "equipment fault"
Display First Three Rows of Table
Create a table from a file with 1468 rows.
T = readtable("outages.csv","TextType","string"); size(T)
ans = 1×2
1468 6
Display the first three rows. If you do not specify an output argument, head
does not return a value. It only displays the top of the table.
head(T,3)
Region OutageTime Loss Customers RestorationTime Cause ___________ ________________ ______ __________ ________________ ______________ "SouthWest" 2002-02-01 12:18 458.98 1.8202e+06 2002-02-07 16:50 "winter storm" "SouthEast" 2003-01-23 00:49 530.14 2.1204e+05 NaT "winter storm" "SouthEast" 2003-02-07 21:15 289.4 1.4294e+05 2003-02-17 08:14 "winter storm"
Extract and View Top of Tall Table
Create a tall table. Then extract and view the first eight rows of data.
Create a tall table for the airlinesmall.csv
data set. Select a subset of the table variables to work with.
varnames = ["Year","Month","ArrDelay","DepDelay","UniqueCarrier"]; ds = tabularTextDatastore("airlinesmall.csv","TreatAsMissing","NA",... "SelectedVariableNames",varnames,"TextType","string"); T = tall(ds)
T = Mx5 tall table Year Month ArrDelay DepDelay UniqueCarrier ____ _____ ________ ________ _____________ 1987 10 8 12 "PS" 1987 10 8 1 "PS" 1987 10 21 20 "PS" 1987 10 13 12 "PS" 1987 10 4 -1 "PS" 1987 10 59 63 "PS" 1987 10 3 -2 "PS" 1987 10 11 -1 "PS" : : : : : : : : : :
To extract the first eight rows of data, use head
. The result is a tall table with eight rows.
tt = head(T)
tt = 8x5 tall table Year Month ArrDelay DepDelay UniqueCarrier ____ _____ ________ ________ _____________ 1987 10 8 12 "PS" 1987 10 8 1 "PS" 1987 10 21 20 "PS" 1987 10 13 12 "PS" 1987 10 4 -1 "PS" 1987 10 59 63 "PS" 1987 10 3 -2 "PS" 1987 10 11 -1 "PS"
Collect the data into memory using the gather
function. The result is an ordinary table with eight rows.
t8 = gather(tt)
t8=8×5 table
Year Month ArrDelay DepDelay UniqueCarrier
____ _____ ________ ________ _____________
1987 10 8 12 "PS"
1987 10 8 1 "PS"
1987 10 21 20 "PS"
1987 10 13 12 "PS"
1987 10 4 -1 "PS"
1987 10 59 63 "PS"
1987 10 3 -2 "PS"
1987 10 11 -1 "PS"
Retrieve Specified Number of Rows in Tall Array
Preview the first 20 rows of data in a tall table.
Create a tall table for the airlinesmall.csv
data set. Select a subset of the variables to work with, and treat "NA"
values as missing data so that datastore
replaces them with NaN
values. Use head
to view the first 20 rows of data.
varnames = ["Year","Month","ArrDelay","DepDelay","UniqueCarrier"]; ds = tabularTextDatastore("airlinesmall.csv","TreatAsMissing","NA",... "SelectedVariableNames",varnames,"TextType","string"); T = tall(ds)
T = Mx5 tall table Year Month ArrDelay DepDelay UniqueCarrier ____ _____ ________ ________ _____________ 1987 10 8 12 "PS" 1987 10 8 1 "PS" 1987 10 21 20 "PS" 1987 10 13 12 "PS" 1987 10 4 -1 "PS" 1987 10 59 63 "PS" 1987 10 3 -2 "PS" 1987 10 11 -1 "PS" : : : : : : : : : :
tt = head(T,20)
tt = 20x5 tall table Year Month ArrDelay DepDelay UniqueCarrier ____ _____ ________ ________ _____________ 1987 10 8 12 "PS" 1987 10 8 1 "PS" 1987 10 21 20 "PS" 1987 10 13 12 "PS" 1987 10 4 -1 "PS" 1987 10 59 63 "PS" 1987 10 3 -2 "PS" 1987 10 11 -1 "PS" : : : : : : : : : :
Collect the results into memory to view the data.
t20 = gather(tt)
t20=20×5 table
Year Month ArrDelay DepDelay UniqueCarrier
____ _____ ________ ________ _____________
1987 10 8 12 "PS"
1987 10 8 1 "PS"
1987 10 21 20 "PS"
1987 10 13 12 "PS"
1987 10 4 -1 "PS"
1987 10 59 63 "PS"
1987 10 3 -2 "PS"
1987 10 11 -1 "PS"
1987 10 3 3 "PS"
1987 10 2 1 "PS"
1987 10 16 15 "PS"
1987 10 3 9 "PS"
1987 10 39 15 "PS"
1987 10 57 32 "TW"
1987 10 0 -3 "TW"
1987 10 -14 0 "TW"
⋮
Input Arguments
A
— Input array
table | timetable | tall array
Input array, specified as a table, timetable, or tall array.
k
— Number of rows to extract
scalar
Number of rows to extract, specified as a positive scalar integer. If
A
has fewer than k
rows, then
head
returns all of A
.
Output Arguments
B
— Requested rows
table | timetable | tall array
Requested rows, returned as a table, timetable, or tall array. The data
type of B
is the same as A
.
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
This function fully supports tall arrays. For more information, see Tall Arrays.
You can use head
and tail
with tall
arrays of any valid underlying data type (single
,
double
, int8
, datetime
,
table
, and so on).
If you are unsure whether the result returned by gather(A)
will fit in memory, then use gather(head(A))
or
gather(tail(A))
. These commands still fully evaluate the tall
array A
, but only return a small subset of the result in
memory.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version History
Introduced in R2016bR2022b: Calling head
without specified output argument does not store output in ans
When you call head
without a specified output argument,
head
displays the selected rows of the table but it does not
store the output in the ans
variable. In previous releases,
calling head
without a specified output argument causes the
output to be stored in ans
.
Calling head
in a live script is usually not recommended.
Instead, display the table or timetable by typing the variable name with no semicolon. The
live editor provides a widget that enables you to examine the entire table or timetable.
However, if you do call head
in a live script, it is recommended
that you assign the output to a variable so that the live script creates a widget for the
output.
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