readtable('filename.csv') is not importing all columns
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I have the following attached csv file. The csv file has two columns X and Y. In the columns X, Y, I have several values in one cell
On the using the following matlab commands:
M = readtable('intima_coords.csv');
data = array2table(M)
MATLAB is returning only one column and ignoring the other.
What should be done to read both the colums?
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Answers (1)
Simon Chan
on 30 Jan 2022
The data in the csv file contains both strings and numbers.
I would use function readcell to retrieve the data as strings and convert them to number in a number of steps as follows:
rawdata = readcell('intima_coords.csv'); % Use readcell
% The second row contains the required X & Y data
data = cellfun(@(x) strtrim(erase(x,{'[',']'})),rawdata(2,:),'uni',0); % Remove the characters such as '[' & ']'
datacell = cellfun(@(x) str2double(strsplit(x,' ')),data,'uni',0); % Split them and convert to numbers
% datacell{1} contains the data X
% datacell{2} contains the data Y
plot(datacell{1},datacell{2},'g*'); % Try to plot the data
grid on
3 Comments
Simon Chan
on 31 Jan 2022
I use the following code which may easier to explain, actually they are doing the same thing:
rawdata = readcell('intima_coords.csv');
xydata = rawdata(2,:);
for k = 1:2
erase_characters = erase(xydata{k},{'[',']'});
erase_space = strtrim(erase_characters);
split_space = strsplit(erase_space,' ');
datacell{1,k} = str2double(split_space);
end
The XY data you are looking for are on the second row of the data after readcell and they are character vector like the following:
xydata{1}
'[ 5.68064747e-01 8.85456026e-01 1.21352549e+00 8.85456026e-01
5.68064747e-01 1.21352549e+00 8.81677878e-01 8.81677878e-01
1.00000000e+00 1.42658477e+00 1.42658477e+00 1.20536680e-01
4.63525492e-01 1.20536680e-01 4.63525492e-01 1.50000000e+00
-3.54604887e-01 -7.48510748e-01 -8.81677878e-01 -7.48510748e-01
-3.54604887e-01 -8.81677878e-01 -9.70941817e-01 -9.70941817e-01
-1.50000000e+00 -4.63525492e-01 -4.63525492e-01 -1.42658477e+00
-1.42658477e+00 -1.21352549e+00 -1.21352549e+00 7.71806935e-15
-5.23722504e-15 -1.94548764e-01 -1.94548764e-01 -1.09671525e+00
-1.09671525e+00]'
Step 1 is to erase the characters '[' and ']' (In the beginning and at the end of the character vector) using function erase
erase_characters = erase(xydata{k},{'[',']'});
erase_characters =
' 5.68064747e-01 8.85456026e-01 1.21352549e+00 8.85456026e-01
5.68064747e-01 1.21352549e+00 8.81677878e-01 8.81677878e-01
1.00000000e+00 1.42658477e+00 1.42658477e+00 1.20536680e-01
4.63525492e-01 1.20536680e-01 4.63525492e-01 1.50000000e+00
-3.54604887e-01 -7.48510748e-01 -8.81677878e-01 -7.48510748e-01
-3.54604887e-01 -8.81677878e-01 -9.70941817e-01 -9.70941817e-01
-1.50000000e+00 -4.63525492e-01 -4.63525492e-01 -1.42658477e+00
-1.42658477e+00 -1.21352549e+00 -1.21352549e+00 7.71806935e-15
-5.23722504e-15 -1.94548764e-01 -1.94548764e-01 -1.09671525e+00
-1.09671525e+00'
Step 2 is to remove the leading whitespace on the strings using function strtrim. Otherwise it will create an extra number when split the string in the next step.
erase_space = strtrim(erase_characters);
erase_space =
'5.68064747e-01 8.85456026e-01 1.21352549e+00 8.85456026e-01
5.68064747e-01 1.21352549e+00 8.81677878e-01 8.81677878e-01
1.00000000e+00 1.42658477e+00 1.42658477e+00 1.20536680e-01
4.63525492e-01 1.20536680e-01 4.63525492e-01 1.50000000e+00
-3.54604887e-01 -7.48510748e-01 -8.81677878e-01 -7.48510748e-01
-3.54604887e-01 -8.81677878e-01 -9.70941817e-01 -9.70941817e-01
-1.50000000e+00 -4.63525492e-01 -4.63525492e-01 -1.42658477e+00
-1.42658477e+00 -1.21352549e+00 -1.21352549e+00 7.71806935e-15
-5.23722504e-15 -1.94548764e-01 -1.94548764e-01 -1.09671525e+00
-1.09671525e+00'
Step 3 is to split the string with delimiter ' ' (actually a space between them) using function strsplit
split_space = strsplit(erase_space,' ')
split_space =
Columns 1 through 5
{'5.68064747e-01'} {'8.85456026e-01'} {'1.21352549e+00'} {'8.85456026e-01↵'} {'5.68064747e-01'}
Columns 6 through 10
{'1.21352549e+00'} {'8.81677878e-01'} {'8.81677878e-01↵'} {'1.00000000e+00'} {'1.42658477e+00'}
Columns 11 through 15
{'1.42658477e+00'} {'1.20536680e-01↵'} {'4.63525492e-01'} {'1.20536680e-01'} {'4.63525492e-01'}
Columns 16 through 20
{'1.50000000e+00↵'} {'-3.54604887e-01'} {'-7.48510748e-01'} {'-8.81677878e-01'} {'-7.48510748e-01↵'}
Columns 21 through 25
{'-3.54604887e-01'} {'-8.81677878e-01'} {'-9.70941817e-01'} {'-9.70941817e-01↵'} {'-1.50000000e+00'}
Columns 26 through 30
{'-4.63525492e-01'} {'-4.63525492e-01'} {'-1.42658477e+00↵'} {'-1.42658477e+00'} {'-1.21352549e+00'}
Columns 31 through 35
{'-1.21352549e+00'} {'7.71806935e-15↵'} {'-5.23722504e-15'} {'-1.94548764e-01'} {'-1.94548764e-01'}
Columns 36 through 37
{'-1.09671525e+00↵'} {'-1.09671525e+00'}
Finally convert them into numbers using function str2double
datacell{1}
Columns 1 through 12
0.5681 0.8855 1.2135 0.8855 0.5681 1.2135 0.8817 0.8817 1.0000 1.4266 1.4266 0.1205
Columns 13 through 24
0.4635 0.1205 0.4635 1.5000 -0.3546 -0.7485 -0.8817 -0.7485 -0.3546 -0.8817 -0.9709 -0.9709
Columns 25 through 36
-1.5000 -0.4635 -0.4635 -1.4266 -1.4266 -1.2135 -1.2135 0.0000 -0.0000 -0.1945 -0.1945 -1.0967
Column 37
-1.0967
The function cellfun just doing the same thing without using for loop.
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