matlab：使用readmatrix导入时转换CSV列中的值

我有一个包含以下数据的CSV文件：

20180101 170000;1.200370;1.201000;1.200370;1.201000;0
20180101 170100;1.200830;1.200950;1.200170;1.200300;0
20180101 170200;1.200350;1.200430;1.200350;1.200430;0
20180101 170300;1.200410;1.200500;1.200310;1.200460;0
20180101 170400;1.200490;1.200490;1.200460;1.200480;0
20180101 170500;1.200500;1.200500;1.200480;1.200480;0
20180101 170600;1.200500;1.200690;1.200320;1.200480;0
20180101 170700;1.200480;1.200540;1.200270;1.200500;0
20180101 170800;1.200510;1.200870;1.200470;1.200870;0
20180101 170900;1.200820;1.200970;1.200760;1.200940;0
20180101 171000;1.200940;1.200950;1.200760;1.200770;0
20180101 171100;1.200840;1.200880;1.200840;1.200880;0
20180101 171200;1.200880;1.200880;1.200790;1.200790;0
20180101 171300;1.200800;1.200800;1.200800;1.200800;0
20180101 171400;1.200770;1.200930;1.200770;1.200930;0
20180101 171500;1.200920;1.201050;1.200360;1.200360;0
20180101 171600;1.200380;1.200380;1.200380;1.200380;0
20180101 171700;1.200390;1.200390;1.200380;1.200380;0
20180101 171800;1.200420;1.200450;1.200400;1.200450;0
20180101 171900;1.200410;1.200500;1.200410;1.200500;0
20180101 172000;1.200530;1.200530;1.200440;1.200450;0
20180101 172200;1.200450;1.200450;1.200450;1.200450;0
20180101 172300;1.200450;1.200550;1.200450;1.200550;0

第一列是日期，格式为

YYYYMMDD HHmmss

我想使用

readmatrix

命令在matlab中导入csv文件。我得到的是

data = readmatrix("\Data.csv");
>> data(1:20,:)

ans =

       NaN    1.2004    1.2010    1.2004    1.2010         0
       NaN    1.2008    1.2009    1.2002    1.2003         0
       NaN    1.2004    1.2004    1.2004    1.2004         0
       NaN    1.2004    1.2005    1.2003    1.2005         0
       NaN    1.2005    1.2005    1.2005    1.2005         0
       NaN    1.2005    1.2005    1.2005    1.2005         0
       NaN    1.2005    1.2007    1.2003    1.2005         0
       NaN    1.2005    1.2005    1.2003    1.2005         0
       NaN    1.2005    1.2009    1.2005    1.2009         0
       NaN    1.2008    1.2010    1.2008    1.2009         0
       NaN    1.2009    1.2009    1.2008    1.2008         0
       NaN    1.2008    1.2009    1.2008    1.2009         0
       NaN    1.2009    1.2009    1.2008    1.2008         0
       NaN    1.2008    1.2008    1.2008    1.2008         0
       NaN    1.2008    1.2009    1.2008    1.2009         0
       NaN    1.2009    1.2010    1.2004    1.2004         0
       NaN    1.2004    1.2004    1.2004    1.2004         0
       NaN    1.2004    1.2004    1.2004    1.2004         0
       NaN    1.2004    1.2005    1.2004    1.2005         0
       NaN    1.2004    1.2005    1.2004    1.2005         0

未正确导入日期

既然文件很大，而且我不想修改它（它在公共存储库中，我应该创建一个本地副本，而且文件不仅很大，而且我有很多），那么有没有办法使用

readmatrix

来正确读取datetime列

---

如果不可能，我应该怎么做才能修改文件（我将创建一个本地副本），使其可以通过

readmatrix

导入？

您可能需要对

textscan

使用不同的方法。（如果单击“创建代码”，这就是MATLAB的UIOpenGUI所使用的）

readmatrix的问题在于它不能处理不同的数据类型。如果你试图用一个数字矩阵来表示一个日期时间向量，这一点就很明显了

因此，您需要使用talbe、单元格或拆分读数

function Dat = importfile(filename, startRow, endRow)
%IMPORTFILE Import numeric data from a text file as a matrix.
%   DAT = IMPORTFILE(FILENAME) Reads data from text file FILENAME for the
%   default selection.
%
%   DAT = IMPORTFILE(FILENAME, STARTROW, ENDROW) Reads data from rows
%   STARTROW through ENDROW of text file FILENAME.
%
% Example:
%   Dat = importfile('CSVFILE.csv', 1, 23);
%
%    See also TEXTSCAN.

% Auto-generated by MATLAB on 2020/03/07 21:59:43

%% Initialize variables.
delimiter = ';';
if nargin<=2
    startRow = 1;
    endRow = inf;
end

%% Read columns of data as text:
% For more information, see the TEXTSCAN documentation.
formatSpec = '%s%s%s%s%s%s%[^\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));

for col = [2,3,4,5,6]
    % Converts text in the input cell array to numbers. Replaced non-numeric
    % text with NaN.
    rawData = dataArray{col};
    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, col) = numbers{1};
                raw{row, col} = numbers{1};
            end
        catch
            raw{row, col} = rawData{row};
        end
    end
end

% Convert the contents of columns with dates to MATLAB datetimes using the
% specified date format.
try
    dates{1} = datetime(dataArray{1}, 'Format', 'dd-MMM-yyyy HH:mm:ss', 'InputFormat', 'dd-MMM-yyyy HH:mm:ss');
catch
    try
        % Handle dates surrounded by quotes
        dataArray{1} = cellfun(@(x) x(2:end-1), dataArray{1}, 'UniformOutput', false);
        dates{1} = datetime(dataArray{1}, 'Format', 'dd-MMM-yyyy HH:mm:ss', 'InputFormat', 'dd-MMM-yyyy HH:mm:ss');
    catch
        dates{1} = repmat(datetime([NaN NaN NaN]), size(dataArray{1}));
    end
end

dates = dates(:,1);

%% Split data into numeric and string columns.
rawNumericColumns = raw(:, [2,3,4,5,6]);

%% 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

%% Create output variable
Dat = table;
Dat.date = dates{:, 1};
Dat.a = cell2mat(rawNumericColumns(:, 1));
Dat.b = cell2mat(rawNumericColumns(:, 2));
Dat.c = cell2mat(rawNumericColumns(:, 3));
Dat.d = cell2mat(rawNumericColumns(:, 4));
Dat.e = cell2mat(rawNumericColumns(:, 5));

end

最后，所有内容都打包在一个漂亮的表中，并根据我的规范重命名

%% Create output variable
Dat = table;
Dat.date = dates{:, 1};
Dat.a = cell2mat(rawNumericColumns(:, 1));
Dat.b = cell2mat(rawNumericColumns(:, 2));
Dat.c = cell2mat(rawNumericColumns(:, 3));
Dat.d = cell2mat(rawNumericColumns(:, 4));
Dat.e = cell2mat(rawNumericColumns(:, 5));

我希望这有帮助。您关心的是内存效率，在扫描csv文件时进行转换，而不是作为后续步骤（如自动生成功能所示）

%% Create output variable
Dat = table;
Dat.date = dates{:, 1};
Dat.a = cell2mat(rawNumericColumns(:, 1));
Dat.b = cell2mat(rawNumericColumns(:, 2));
Dat.c = cell2mat(rawNumericColumns(:, 3));
Dat.d = cell2mat(rawNumericColumns(:, 4));
Dat.e = cell2mat(rawNumericColumns(:, 5));