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rploader

RavenPack News Analytics file reader

Syntax

d = rploader(filename)
d = rploader(filename,Name,Value)
[d,h] = rploader(___)

Description

example

d = rploader(filename) reads the contents of the RavenPack® News Analytics data file specified by filename and returns the contents in the MATLAB® variable d.

example

d = rploader(filename,Name,Value) reads the contents of the file using additional options specified by one or more Name,Value pair arguments.

example

[d,h] = rploader(___) reads the contents of the file and retrieves the header information h in the file using any of the input arguments in the previous syntaxes.

Examples

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Open the RavenPack Data Feed Tool and create a RavenPack News Analytics data file. The resulting file is a comma-separated file. Open MATLAB. Navigate to the folder where the RavenPack News Analytics data file is located.

Read the data in the RavenPack News Analytics data file filename. Here, the file contains Global Macro News Analytics data.

filename = '2014-11-macro.csv';

d = rploader(filename);

d is a table that contains the RavenPack News Analytics data.

Display the first four columns of the first record of data.

d(1,1:4)
ans = 

       TIMESTAMP_UTC        RP_ENTITY_ID    ENTITY_TYPE    ENTITY_NAME
    ____________________    ____________    ___________    ___________

    24-Nov-2014 00:00:05    'F33A73'        'CMDT'         'Iron Ore' 

d is a table with a header that contains the column names. There is one row in the table for each record of news data. Here, the first four columns specify a news event on November 24, 2014 about Iron Ore.

List the columns in the data.

d.Properties.VariableNames
ans = 

  Columns 1 through 4

    'TIMESTAMP_UTC'    'RP_ENTITY_ID'    'ENTITY_TYPE'    'ENTITY_NAME'

  Columns 5 through 8

    'POSITION_NAME'    'RP_POSITION_ID'    'COUNTRY_CODE'    'RELEVANCE'

  Columns 9 through 13

    'TOPIC'    'GROUP'    'TYPE'    'SUB_TYPE'    'PROPERTY'

  Columns 14 through 19

    'EVALUATION_METHOD'    'MATURITY'    'CATEGORY'    'ESS'    'AES'    'AEV'

  Columns 20 through 24

    'ENS'    'ENS_SIMILARITY_GAP'    'ENS_KEY'    'ENS_ELAPSED'    'G_ENS'

  Columns 25 through 27

    'G_ENS_SIMILARITY...'    'G_ENS_KEY'    'G_ENS_ELAPSED'

  Columns 28 through 31

    'EVENT_SIMILARITY...'    'NEWS_TYPE'    'SOURCE'    'RP_STORY_ID'

  Columns 32 through 34

    'RP_STORY_EVENT_I...'    'RP_STORY_EVENT_C...'    'PRODUCT_KEY'

For details about each column in the table, see RavenPack News Analytics User Guide and Service Overview in the RavenPack Developer Zone Overview.

Open the RavenPack Data Feed Tool and create a RavenPack News Analytics data file. The resulting file is a comma-separated file. Open MATLAB. Navigate to the folder where the RavenPack News Analytics data file is located.

Read the data in the RavenPack News Analytics data file filename. Here, the file contains Global Macro News Analytics data. The RavenPack News Analytics entity name is Iron Ore.

filename = '2014-11-macro.csv';

d = rploader(filename,'entity_name',{'Iron Ore'});

d is a table that contains the RavenPack News Analytics data for Iron Ore.

Display the first four columns of the first record of data.

d(1,1:4)
ans = 

       TIMESTAMP_UTC        RP_ENTITY_ID    ENTITY_TYPE    ENTITY_NAME
    ____________________    ____________    ___________    ___________

    24-Nov-2014 00:00:05    'F33A73'        'CMDT'         'Iron Ore' 

d is a table with a header that contains the column names. There is one row in the table for each record of news data. Here, the first four columns specify a news event on November 24, 2014 about Iron Ore.

List the columns in the data.

d.Properties.VariableNames
ans = 

  Columns 1 through 4

    'TIMESTAMP_UTC'    'RP_ENTITY_ID'    'ENTITY_TYPE'    'ENTITY_NAME'

  Columns 5 through 8

    'POSITION_NAME'    'RP_POSITION_ID'    'COUNTRY_CODE'    'RELEVANCE'

  Columns 9 through 13

    'TOPIC'    'GROUP'    'TYPE'    'SUB_TYPE'    'PROPERTY'

  Columns 14 through 19

    'EVALUATION_METHOD'    'MATURITY'    'CATEGORY'    'ESS'    'AES'    'AEV'

  Columns 20 through 24

    'ENS'    'ENS_SIMILARITY_GAP'    'ENS_KEY'    'ENS_ELAPSED'    'G_ENS'

  Columns 25 through 27

    'G_ENS_SIMILARITY...'    'G_ENS_KEY'    'G_ENS_ELAPSED'

  Columns 28 through 31

    'EVENT_SIMILARITY...'    'NEWS_TYPE'    'SOURCE'    'RP_STORY_ID'

  Columns 32 through 34

    'RP_STORY_EVENT_I...'    'RP_STORY_EVENT_C...'    'PRODUCT_KEY'

For details about each column in the table, see RavenPack News Analytics User Guide and Service Overview in the RavenPack Developer Zone Overview.

Open the RavenPack Data Feed Tool and create a RavenPack News Analytics data file. The resulting file is a comma-separated file. Open MATLAB. Navigate to the folder where the RavenPack News Analytics data file is located.

Read the data in the RavenPack News Analytics data file filename. Here, the file contains Global Macro News Analytics data. Read 5000 records in the data file starting at record number 10,000.

filename = '2014-11-macro.csv';

d = rploader(filename,'start',10000,'records',5000);

d is a table that contains the RavenPack News Analytics data.

Display the first four columns of the first record of data.

d(1,1:4)
ans = 

       TIMESTAMP_UTC        RP_ENTITY_ID    ENTITY_TYPE        ENTITY_NAME     
    ____________________    ____________    ___________    ____________________

    24-Nov-2014 07:58:38    '0037F3'        'ORGA'         'State of Rajasthan'

d is a table with a header that contains the column names. There is one row in the table for each record of news data. Here, the first four columns specify a news event on November 24, 2014 about the State of Rajasthan.

List the columns in the data.

d.Properties.VariableNames
ans = 

  Columns 1 through 4

    'TIMESTAMP_UTC'    'RP_ENTITY_ID'    'ENTITY_TYPE'    'ENTITY_NAME'

  Columns 5 through 8

    'POSITION_NAME'    'RP_POSITION_ID'    'COUNTRY_CODE'    'RELEVANCE'

  Columns 9 through 13

    'TOPIC'    'GROUP'    'TYPE'    'SUB_TYPE'    'PROPERTY'

  Columns 14 through 19

    'EVALUATION_METHOD'    'MATURITY'    'CATEGORY'    'ESS'    'AES'    'AEV'

  Columns 20 through 24

    'ENS'    'ENS_SIMILARITY_GAP'    'ENS_KEY'    'ENS_ELAPSED'    'G_ENS'

  Columns 25 through 27

    'G_ENS_SIMILARITY...'    'G_ENS_KEY'    'G_ENS_ELAPSED'

  Columns 28 through 31

    'EVENT_SIMILARITY...'    'NEWS_TYPE'    'SOURCE'    'RP_STORY_ID'

  Columns 32 through 34

    'RP_STORY_EVENT_I...'    'RP_STORY_EVENT_C...'    'PRODUCT_KEY'

For details about each column in the table, see RavenPack News Analytics User Guide and Service Overview in the RavenPack Developer Zone Overview.

Open the RavenPack Data Feed Tool and create a RavenPack News Analytics data file. The resulting file is a comma-separated file. Open MATLAB. Navigate to the folder where the RavenPack News Analytics data file is located.

Read the data in the RavenPack News Analytics data file filename. Read the data from November 24, 2014 through November 25, 2014. Here, the file contains Equities News Analytics data.

filename = '2014-11-equities.csv';

d = rploader(filename,'date',{'11/24/2014','11/25/2014'});

d is a table that contains the RavenPack News Analytics data.

Display the first four columns of the first record of data.

d(1,1:4)
ans = 

       TIMESTAMP_UTC        RP_ENTITY_ID    ENTITY_TYPE           ENTITY_NAME        
    ____________________    ____________    ___________    __________________________

    24-Nov-2014 00:00:04    '355013'        'COMP'         'Panoramic Resources Ltd.'

d is a table with a header that contains the column names. There is one row in the table for each record of news data. Here, the first four columns specify a news event on November 24, 2014 about a company.

List the columns in the data.

d.Properties.VariableNames
ans = 

  Columns 1 through 4

    'TIMESTAMP_UTC'    'RP_ENTITY_ID'    'ENTITY_TYPE'    'ENTITY_NAME'

  Columns 5 through 8

    'POSITION_NAME'    'RP_POSITION_ID'    'COUNTRY_CODE'    'RELEVANCE'

  Columns 9 through 13

    'TOPIC'    'GROUP'    'TYPE'    'SUB_TYPE'    'PROPERTY'

  Columns 14 through 19

    'EVALUATION_METHOD'    'MATURITY'    'CATEGORY'    'ESS'    'AES'    'AEV'

  Columns 20 through 24

    'ENS'    'ENS_SIMILARITY_GAP'    'ENS_KEY'    'ENS_ELAPSED'    'G_ENS'

  Columns 25 through 27

    'G_ENS_SIMILARITY...'    'G_ENS_KEY'    'G_ENS_ELAPSED'

  Columns 28 through 31

    'EVENT_SIMILARITY...'    'NEWS_TYPE'    'SOURCE'    'RP_STORY_ID'

  Columns 32 through 35

    'RP_STORY_EVENT_I...'    'RP_STORY_EVENT_C...'    'PRODUCT_KEY'    'COMPANY'

  Columns 36 through 43

    'ISIN'    'CSS'    'NIP'    'PEQ'    'BEE'    'BMQ'    'BAM'    'BCA'

  Columns 44 through 46

    'BER'    'ANL_CHG'    'MCQ'

For details about each column in the table, see RavenPack News Analytics User Guide and Service Overview in the RavenPack Developer Zone Overview.

Open the RavenPack Data Feed Tool and create a RavenPack News Analytics data file. The resulting file is a comma-separated file. Open MATLAB. Navigate to the folder where the RavenPack News Analytics data file is located.

Read the data in the RavenPack News Analytics data file filename. Here, the file contains Global Macro News Analytics data. Read 5000 records in the data file starting at record number 10,000.

filename = '2014-11-macro.csv';

[d,h] = rploader(filename,'start',10000,'records',5000);

d is a table that contains the RavenPack News Analytics data.

h is a cell array that contains the header information.

Display the header information.

h
h = 

    'TIMESTAMP_UTC'
    'RP_ENTITY_ID'
    'ENTITY_TYPE'
    'ENTITY_NAME'
    'POSITION_NAME'
    'RP_POSITION_ID'
    'COUNTRY_CODE'
    'RELEVANCE'
    'TOPIC'
    'GROUP'
    'TYPE'
    'SUB_TYPE'
    'PROPERTY'
    'EVALUATION_METHOD'
    'MATURITY'
    'CATEGORY'
    'ESS'
    'AES'
    'AEV'
    'ENS'
    'ENS_SIMILARITY_GAP'
    'ENS_KEY'
    'ENS_ELAPSED'
    'G_ENS'
    'G_ENS_SIMILARITY_GAP'
    'G_ENS_KEY'
    'G_ENS_ELAPSED'
    'EVENT_SIMILARITY_KEY'
    'NEWS_TYPE'
    'SOURCE'
    'RP_STORY_ID'
    'RP_STORY_EVENT_INDEX'
    'RP_STORY_EVENT_COUNT'
    'PRODUCT_KEY'

For details, see RavenPack News Analytics User Guide and Service Overview in the RavenPack Developer Zone Overview.

Input Arguments

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RavenPack News Analytics data file, specified as a character vector or string scalar. To create this file, use the RavenPack Data Feed Tool to export news data into a comma-separated file.

Data Types: char | string

Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.

Example: 'date',{'11/24/2014'}

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Date or date range, specified as the comma-separated pair consisting of 'date' and a cell array or string array. If you specify one date, rploader returns news data for the day specified by the string scalar, character vector, date number, or datetime array in the cell array. To specify a date range, use 'date' and a string array that contains two string scalars or a cell array that contains two character vectors, date numbers, or datetime arrays separated by a comma. The dates in the date range are inclusive.

Example: 'date',{'11/24/2014','11/25/2014'}

Data Types: cell | string

RavenPack News Analytics entity identifier, specified as the comma-separated pair consisting of 'rp_entity_id' and a cell array of one or more character vectors or string array. The character vectors or string scalars denote the RavenPack entity identifiers. For details about the RavenPack entity identifiers, see RavenPack News Analytics User Guide and Service Overview in the RavenPack Developer Zone Overview.

Example: 'rp_entity_id',{'F33A73'}

Data Types: cell

RavenPack News Analytics entity name, specified as a comma-separated pair consisting of 'entity_name' and a cell array of one or more character vectors or string array of string scalars that denote RavenPack entity names. For details about the RavenPack entity names, see RavenPack News Analytics User Guide and Service Overview in the RavenPack Developer Zone Overview.

Example: 'entity_name',{'Iron Ore'}

Data Types: cell

Reading offset, specified as a numeric scalar to denote the record from which to start reading the RavenPack News Analytics data in the data file.

Example: 'start',100

Data Types: double

Number of records to read in the data file, specified as a numeric scalar.

Example: 'records',5000

Data Types: double

Output Arguments

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RavenPack News Analytics data, returned as a table. If no matching data is found based on the specified name-value pair arguments, d returns as an empty double.

Header information, returned as a cell array. The header information contains the titles of each column in the returned data d.

Introduced in R2015b

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