function companiesnames = importCompanyData(filename, startRow, endRow)
%IMPORTFILE Import numeric data from a text file as a matrix.
%   COMPANIESNAMESINDUSTRIES = IMPORTFILE(FILENAME) Reads data from text
%   file FILENAME for the default selection.
%
%   COMPANIESNAMESINDUSTRIES = IMPORTFILE(FILENAME, STARTROW, ENDROW) Reads
%   data from rows STARTROW through ENDROW of text file FILENAME.
%
% Example:
%   companiesnamesindustries = importfile('companies-names-industries.csv', 2, 12605);
%
%    See also TEXTSCAN.

% Auto-generated by MATLAB on 2017/09/25 19:09:20

%% Initialize variables.
delimiter = ',';
if nargin<=2
    startRow = 2;
    endRow = inf;
end

%% Read columns of data as text:
% For more information, see the TEXTSCAN documentation.
formatSpec = '%q%q%*q%q%[^\n\r]';

%% Open the text file.
fileID = fopen(filename,'r');

%% Read columns of data according to the format.
% This call is based on the structure of the file used to generate this
% code. If an error occurs for a different file, try regenerating the code
% from the Import Tool.
dataArray = textscan(fileID, formatSpec, endRow(1)-startRow(1)+1, 'Delimiter', delimiter, 'TextType', 'string', 'HeaderLines', startRow(1)-1, 'ReturnOnError', false, 'EndOfLine', '\r\n');
for block=2:length(startRow)
    frewind(fileID);
    dataArrayBlock = textscan(fileID, formatSpec, endRow(block)-startRow(block)+1, 'Delimiter', delimiter, 'TextType', 'string', 'HeaderLines', startRow(block)-1, 'ReturnOnError', false, 'EndOfLine', '\r\n');
    for col=1:length(dataArray)
        dataArray{col} = [dataArray{col};dataArrayBlock{col}];
    end
end

%% Close the text file.
fclose(fileID);

%% Convert the contents of columns containing numeric text to numbers.
% Replace non-numeric text with NaN.
raw = repmat({''},length(dataArray{1}),length(dataArray)-1);
for col=1:length(dataArray)-1
    raw(1:length(dataArray{col}),col) = mat2cell(dataArray{col}, ones(length(dataArray{col}), 1));
end
numericData = NaN(size(dataArray{1},1),size(dataArray,2));

% Converts text in the input cell array to numbers. Replaced non-numeric
% text with NaN.
rawData = dataArray{1};
for row=1:size(rawData, 1)
    % Create a regular expression to detect and remove non-numeric prefixes and
    % suffixes.
    regexstr = '(?<prefix>.*?)(?<numbers>([-]*(\d+[\,]*)+[\.]{0,1}\d*[eEdD]{0,1}[-+]*\d*[i]{0,1})|([-]*(\d+[\,]*)*[\.]{1,1}\d+[eEdD]{0,1}[-+]*\d*[i]{0,1}))(?<suffix>.*)';
    try
        result = regexp(rawData(row), regexstr, 'names');
        numbers = result.numbers;
        
        % Detected commas in non-thousand locations.
        invalidThousandsSeparator = false;
        if numbers.contains(',')
            thousandsRegExp = '^\d+?(\,\d{3})*\.{0,1}\d*$';
            if isempty(regexp(numbers, thousandsRegExp, 'once'))
                numbers = NaN;
                invalidThousandsSeparator = true;
            end
        end
        % Convert numeric text to numbers.
        if ~invalidThousandsSeparator
            numbers = textscan(char(strrep(numbers, ',', '')), '%f');
            numericData(row, 1) = numbers{1};
            raw{row, 1} = numbers{1};
        end
    catch
        raw{row, 1} = rawData{row};
    end
end


%% Split data into numeric and string columns.
rawNumericColumns = raw(:, 1);
rawStringColumns = string(raw(:, [2,3]));


%% Replace non-numeric cells with NaN
R = cellfun(@(x) ~isnumeric(x) && ~islogical(x),rawNumericColumns); % Find non-numeric cells
rawNumericColumns(R) = {NaN}; % Replace non-numeric cells

%% Make sure any text containing <undefined> is properly converted to an <undefined> categorical
idx = (rawStringColumns(:, 2) == "<undefined>");
rawStringColumns(idx, 2) = "";

%% Create output variable
companiesnames = table;
companiesnames.SECID = cell2mat(rawNumericColumns(:, 1));
companiesnames.Name = rawStringColumns(:, 1);
companiesnames.Industry = categorical(rawStringColumns(:, 2));

