Import Data from Text File to Table - MATLAB & Simulink - MathWorks Nordic (2024)

Read Text File as Table

You can import tabular data from a text file into a table using the readtable function. For example, the sample file outages.csv contains comma-separated column-oriented data.

Create a table from outages.csv. The resulting table contains one variable for each column in the file, and readtable treats the entries in the first line of the file as variable names. Display the first three rows and first five columns of the table using indexing.

T = readtable("outages.csv");T(1:3,1:6)

ans=3×6 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'}

Specify Delimiters

By default, readtable detects the file delimiter and uses it to split your data into table elements. readtable determines the delimiter by using the number of variables and the consistency of data type in columns in the first 250 nonempty lines of data. For example, because airlinesmall.csv contains comma-separated data, readtable detects the delimiter as "," and splits the data accordingly.

T = readtable("airlinesmall.csv");

If readtable does not select the delimiter you intended, you can specify the delimiter using the Delimiter name-value argument.

T = readtable("airlinesmall.csv",Delimiter=",");

Read Data with Column Headers

By default, readtable determines if your file has a row of headers to use as variable names. For example, the first two rows of the headersAndMissing.txt file contain variable names and headers. readtable keeps the first row of variable names and discards the second row of headers.

T = readtable("headersAndMissing.txt");

You can specify the number of header lines to skip at the beginning of the file by using the NumHeaderLines name-value argument. For example, specify the first row as a header line to skip before reading data.

T = readtable("headersAndMissing.txt",NumHeaderLines=1)

T=5×6 table string string_1 int int_1 int_2 boolean ___________ __________ ___ _____ _____ _______ {'Wu' } {'M' } 38 71 176 1 {'Johnson'} {'M' } 43 69 163 0 {'Sanchez'} {'F' } 38 64 131 0 {'Brown' } {'F' } NaN 67 133 0 {'Picard' } {0x0 char} NaN 64 119 0 

Read Data Without Column Headers

If your file does not have column headers, readtable assigns default variable names in the format Var1, Var2, ..., VarN. For example, mySpaceDelimTable.txt does not have column names in the first row, so readtable assigns the default variable names Var1 to Var5. View the first three rows of your table.

T = readtable("mySpaceDelimTable.txt");head(T,3)

 Var1 Var2 Var3 Var4 Var5 _____ ____ ____ ______ _________ {'M'} 45 45 {'NY'} {'true' } {'F'} 41 32 {'CA'} {'false'} {'M'} 40 34 {'MA'} {'false'}

If your file has column headers, but you do not want to read them in, specify the ReadVariableNames name-value argument as false.

T = readtable("headersAndMissing.txt",ReadVariableNames=false);

Fill Missing Data

If your file contains missing data, readtable fills the data gaps with the appropriate missing values. Gaps are considered missing data if they contain only white-space characters or the row ends before a variable is found. For example, in the file headersAndMissing.txt, the last two rows have gaps where the previous rows have data values. By default, readtable fills these gaps with appropriate missing values, such as NaN.

T = readtable("headersAndMissing.txt");

If you want to adjust how readtable handles missing data, use the MissingRule name-value argument. For example, to omit rows with missing data, specify MissingRule as "omitrow".

T = readtable("headersAndMissing.txt",MissingRule="omitrow");

Convert Date Locale

If your file contains date values in a date locale different from that of your system, readtable can convert and import the data values with your preferred date locale. For example, create a table from outages.csv by reading the file with a specified character encoding scheme and interpreting the date values using the United States English locale. Specify the character encoding scheme of the file using the Encoding name-value argument. Specify the format and locale of the input dates using the DateLocale name-value argument. View the first three rows of your table.

T = readtable("outages.csv", ... Encoding="ISO-8859-15", ... DateLocale="en_US");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'}

Read Hexadecimal and Binary Numbers

If your file contains hexadecimal or binary literals, readtable can read and store them as numeric variables in a table. The readtable function automatically reads hexadecimal and binary numbers when they include the 0x and 0b prefixes, respectively. The numeric values are stored using integer data types. You can also use import options to read such numbers when they do not have prefixes.

For example, create a table from the hexAndBinary.txt file. readtable detects the numbers with 0x and 0b prefixes and stores them as integers.

T = readtable("hexAndBinary.txt");

By default, readtable uses the smallest unsigned integer class possible to import hexadecimal and binary literals.

To specify the data types for storing the numeric values imported from hexadecimal and binary numbers, use the HexType and BinaryType name-value arguments. For example, store the values as signed 32-bit integers.

T = readtable("hexAndBinary.txt",HexType="int32",BinaryType="int32");

Configure Import Using Import Options

To further configure your import, you can use an import options object to control how readtable interprets your file. Compared to name-value arguments, an import options object provides more control, better performance, and reusability of the file import configuration.

The import options object contains properties that store information detected about the input file. You can address specific variables or use dot notation to address all variables. For example, create an import options object from outages.csv. View the VariableNames property of the import options object, which stores the detected variable names.

opts = detectImportOptions("outages.csv");opts.VariableNames

ans = 1x6 cell {'Region'} {'OutageTime'} {'Loss'} {'Customers'} {'RestorationTime'} {'Cause'}

To change the data types of specific variables, use the setvartype function. For example, change the data type of the Region variable to string.

opts = setvartype(opts,"Region","string");

To set options for specific variables, use the setvaropts function. For example, generate an error if the RestorationTime variable has an empty field.

opts = setvaropts(opts,"RestorationTime",EmptyFieldRule="error");

To specify a subset of variables to import, use the SelectedVariableNames property. For example, import only the Region and RestorationTime data.

opts.SelectedVariableNames = ["Region","RestorationTime"];

After you finish configuring your import options object, use it with readtable to import your file.

T = readtable("outages.csv",opts);head(T,3)

 Region RestorationTime ___________ ________________ "SouthWest" 2002-02-07 16:50 "SouthEast" NaT "SouthEast" 2003-02-17 08:14

For more information about using an import options object, see detectImportOptions.