Combining and reading data from Excel (.xlsx) into Matlab - excel

Question

There are two parts of my query:
1) I have multiple .xlsx files stored in a folder, a total of 1 year's worth (~ 365 .xlsx files). They are named according to date: ' A_ddmmmyyyy.xlsx' (e.g. A_01Jan2016.xlsx). Each .xlsx has 5 columns of data: Date, Quantity, Latitude, Longitude, Measurement. The problem is, each .xlsx file consists about 400,000 rows of data and although I have scripts in Excel to merge them, the inherent row restriction in Excel prevents me from merging all the data together.
(i) Is there a way to read recursively the data from each .xlsx sheet into MATLAB, and specifying the variable name (i.e. Date, Quantity etc) for each column(variable) within MATLAB (there are no column headings in the .xlsx files)?
(ii) How can I merge the data for each column from each .xlsx together?
Thank you
Jefferson

Answer 1

Let's go by parts
First I do not recommend to join all your files data in one column, there is no need to have this information all together you can work separately with this, using for example datastore
working in matlab in mya directory:
>> pwd
ans =
/home/anquegi/learn/matlab/stackoverflow
I have a folder with a folder that have two sample excel files:
>> ls
20_hz.jpg big_data_store_analysis.m excel_files octave-workspace sample-file.log
40_hz.jpg chirp_signals.m NewCode.m sample.csv
>> ls excel_files/
A_01Jan2016.xlsx A_02Jan2016.xlsx
the content of each file is :
Date Quantity Latitude Longitude Measurement
1 1 1 1 1
2 2 2 2 2
3 3 3 3 3
4 4 4 4 4
5 5 5 5 5
6 6 6 6 6
7 7 7 7 7
8 8 8 8 8
9 9 9 9 9
10 10 10 10 10
11 11 11 11 11
12 12 12 12 12
13 13 13 13 13
14 14 14 14 14
15 15 15 15 15
16 16 16 16 16
17 17 17 17 17
18 18 18 18 18
19 19 19 19 19
20 20 20 20 20
21 21 21 21 21
22 22 22 22 22
Only to who how it will work.
Reading the data:
>> ssds = spreadsheetDatastore('./excel_files')
ssds =
SpreadsheetDatastore with properties:
Files: {
'/home/anquegi/learn/matlab/stackoverflow/excel_files/A_01Jan2016.xlsx';
'/home/anquegi/learn/matlab/stackoverflow/excel_files/A_02Jan2016.xlsx'
}
Sheets: ''
Range: ''
Sheet Format Properties:
NumHeaderLines: 0
ReadVariableNames: true
VariableNames: {'Date', 'Quantity', 'Latitude' ... and 2 more}
VariableTypes: {'double', 'double', 'double' ... and 2 more}
Properties that control the table returned by preview, read, readall:
SelectedVariableNames: {'Date', 'Quantity', 'Latitude' ... and 2 more}
SelectedVariableTypes: {'double', 'double', 'double' ... and 2 more}
ReadSize: 'file'
Now you have all your data in tables let's see a preview
>> data = preview(ssds)
data =
Date Quantity Latitude Longitude Measurement
____ ________ ________ _________ ___________
1 1 1 1 1
2 2 2 2 2
3 3 3 3 3
4 4 4 4 4
5 5 5 5 5
6 6 6 6 6
7 7 7 7 7
8 8 8 8 8
The preview is a good point to get sample data to work.
You do not need to merge you can work throught all the elements:
>> ssds.VariableNames
ans =
'Date' 'Quantity' 'Latitude' 'Longitude' 'Measurement'
>> ssds.VariableTypes
ans =
'double' 'double' 'double' 'double' 'double'
% let's get all the Latitude elements that have Date equal 1, in this case the tow files are the same, so we wil get two elements with value 1
>> reset(ssds)
accum = [];
while hasdata(ssds)
T = read(ssds);
accum(end +1) = T(T.Date == 1,:).Latitude;
end
>> accum
accum =
1 1
So you need to work with datastore and tables, is a bit tricky but very useful, you also would like to control the readsize and other variables in datastore objects. but this is a good way working with large data files in matlab
For older versions of matlab you can use a more traditional approximation:
folder='./excel_files';
filetype='*.xlsx';
f=fullfile(folder,filetype);
d=dir(f);
for k=1:numel(d);
data{k}=xlsread(fullfile(folder,d(k).name));
end
Now you have the data stored in data
folder='./excel_files';
filetype='*.xlsx';
f=fullfile(folder,filetype);
d=dir(f);
for k=1:numel(d);
data{k}=xlsread(fullfile(folder,d(k).name));
end
data
data =
[22x5 double] [22x5 double]
data{1}
ans =
1 1 1 1 1
2 2 2 2 2
3 3 3 3 3
4 4 4 4 4
5 5 5 5 5
6 6 6 6 6
7 7 7 7 7
8 8 8 8 8
9 9 9 9 9
10 10 10 10 10
11 11 11 11 11
12 12 12 12 12
13 13 13 13 13
14 14 14 14 14
15 15 15 15 15
16 16 16 16 16
17 17 17 17 17
18 18 18 18 18
19 19 19 19 19
20 20 20 20 20
21 21 21 21 21
22 22 22 22 22
But be carefull with a lot of large file