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Read excel file with number and text

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Marpe
Marpe 2022 年 11 月 23 日
回答済み: Seth Furman 2022 年 12 月 5 日
Hello,
I want to load an excel file (shared in attachments) which has numeric and text 'values' in it (text cells are also really important).
I tried using both readtable and xlsread but I never managed to replicate exactly the excel table in matlab (usually the text rows were NaN).
Here is my code.
datapath = '/…/';
d = dir(datapath);
nd = length(dir);
files=dir(fullfile(datapath,'*.xlsx'));
for n=2
file=fullfile(datapath,files(n).name);
int=readtable(file,"ReadVariableNames",true,"VariableNamingRule","preserve");
end
Thanks for your help,
Marine

採用された回答

Seth Furman
Seth Furman 2022 年 12 月 5 日
Table variables cannot contain a mix of numbers and text. In order to preserve the data, we must import each variable as text. detectImportOptions provides more advanced control over how data are read.
opts = detectImportOptions("BH_Model.xlsx",VariableNamesRange="A1:BO1",VariableNamingRule="preserve");
opts.VariableTypes = repmat("string",1,numel(opts.VariableTypes));
Table variables must all have the same number of rows, so extra rows are filled with missing strings.
readtable("BH_Model.xlsx",opts)
ans = 174×67 table
Date 11-Oct-2022 11-Oct-2022_1 11-Oct-2022_2 11-Oct-2022_3 11-Oct-2022_4 11-Oct-2022_5 12-Oct-2022 12-Oct-2022_1 12-Oct-2022_2 12-Oct-2022_3 12-Oct-2022_4 12-Oct-2022_5 12-Oct-2022_6 12-Oct-2022_7 12-Oct-2022_8 12-Oct-2022_9 12-Oct-2022_10 12-Oct-2022_11 20-Oct-2022 20-Oct-2022_1 20-Oct-2022_2 20-Oct-2022_3 20-Oct-2022_4 20-Oct-2022_5 20-Oct-2022_6 20-Oct-2022_7 20-Oct-2022_8 20-Oct-2022_9 20-Oct-2022_10 20-Oct-2022_11 20-Oct-2022_12 20-Oct-2022_13 20-Oct-2022_14 20-Oct-2022_15 20-Oct-2022_16 20-Oct-2022_17 21-Oct-2022 21-Oct-2022_1 21-Oct-2022_2 21-Oct-2022_3 21-Oct-2022_4 21-Oct-2022_5 21-Oct-2022_6 21-Oct-2022_7 21-Oct-2022_8 21-Oct-2022_9 25-Oct-2022 25-Oct-2022_1 25-Oct-2022_2 25-Oct-2022_3 25-Oct-2022_4 25-Oct-2022_5 25-Oct-2022_6 25-Oct-2022_7 25-Oct-2022_8 25-Oct-2022_9 25-Oct-2022_10 25-Oct-2022_11 26-Oct-2022 26-Oct-2022_1 26-Oct-2022_2 26-Oct-2022_3 26-Oct-2022_4 26-Oct-2022_5 26-Oct-2022_6 26-Oct-2022_7 ___________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ ______________ ______________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ ______________ ______________ ______________ ______________ ______________ ______________ ______________ ______________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ ______________ ______________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ _____________ "Date" "11-Oct-2022" "11-Oct-2022" "11-Oct-2022" "11-Oct-2022" "11-Oct-2022" "11-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "12-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "20-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "21-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "25-Oct-2022" "26-Oct-2022" "26-Oct-2022" "26-Oct-2022" "26-Oct-2022" "26-Oct-2022" "26-Oct-2022" "26-Oct-2022" "26-Oct-2022" "Animal" "Ku" "Ku" "Ku" "Ku" "Ku" "Ku" "Bi" "Bi" "Bi" "Bi" "Bi" "Bi" "Ne" "Ne" "Ne" "Ne" "Ne" "Ne" "Jo" "Jo" "Jo" "Jo" "Jo" "Jo" "La" "La" "La" "La" "La" "La" "Le" "Le" "Le" "Le" "Le" "Le" 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"BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "ECG" "BCG" "BCG" "BCG" "ECG" "BCG" "ECG" "BCG" "Intervals" "0.88" "0.74" "1.14" "0.74" "0.82" "0.78" "0.82" "0.8" "1.46" "0.56" "0.86" "0.92" "0.74" "0.5" "0.72" "0.62" "0.38" "0.58" "0.78" "0.7" "1" "1" "0.74" "1.42" "0.58" "0.64" "1" "1.08" "0.66" "1" "0.94" "0.76" "1.14" "1.18" "0.78" "0.84" "1.02" "1.06" "0.84" "0.84" "0.62" "0.4" "0.78" "0.74" "0.7" "0.58" "1.52" "1.2" "1.28" "1.02" "1.08" "1.04" "0.82" "0.88" "1.08" "0.62" "0.9" "1.1" "1.06" "0.5" "0.56" "0.66" "0.92" "0.92" "0.7" "0.74" "Intervals" "0.74" "0.8" "1" "1.06" "0.74" "0.82" "0.86" "0.86" "1.44" "0.84" "0.86" "0.8" "0.5" "0.56" "0.62" "0.66" "0.6" "0.66" "0.8" "0.84" "1" "1.02" "0.68" "0.68" "0.6" "0.54" "0.92" "1" "0.7" "0.4" "0.96" "1.06" "1.16" "1.28" "0.48" "0.68" "0.78" "0.68" "0.88" "0.86" "0.56" "0.48" "0.56" "0.62" "0.7" "0.66" "1.76" "1.52" "1.4" "0.44" "1.34" "0.98" "0.84" "0.86" "1.42" "0.7" "0.86" "0.64" "1.14" "0.88" "0.58" "0.72" "0.98" "0.96" "0.62" "0.92" "Intervals" "0.78" "0.84" "1.14" "1.06" "0.96" "0.68" "1.02" "1.08" "1.52" "1.52" "0.94" "0.88" "0.5" "0.5" "0.7" "0.66" "0.58" "0.56" "0.84" "0.82" "1.06" "1.06" "0.68" "0.82" "0.62" "0.62" "0.88" "1.28" "0.68" "0.48" "1" "0.98" "1.22" "1.12" "0.68" "0.72" "0.74" "0.74" "0.9" "0.92" "0.64" "0.58" "0.5" "0.66" "0.72" "0.7" "1.88" "1.9" "1.48" "1.14" "1.26" "1.5" "0.64" "0.84" "1.32" "1.2" "0.76" "0.86" "1.18" "0.58" "0.6" "1.14" "0.96" "0.94" "0.6" "0.78" "Intervals" "0.78" "0.34" "1.02" "1.1" "0.92" "0.94" "1.08" "1.04" "1.58" "0.58" "1.16" "1.22" "0.82" "0.5" "0.7" "0.68" "0.5" "0.54" "0.88" "0.96" "1.02" "1.06" "0.62" "0.36" "0.64" "0.58" "0.96" "1.44" "0.7" "0.9" "1.12" "1.04" "1.18" "1.22" "0.72" "0.76" "0.76" "0.76" "0.92" "0.92" "0.6" "0.66" "0.66" "0.72" "0.72" "0.72" "1.84" "1.84" "1.52" "1.2" "1.24" "0.92" "0.76" "0.78" "1.14" "1.04" "0.7" "0.86" "1.16" "0.68" "0.62" "1.22" "0.9" "0.62" "0.7" "0.68" 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"1.14" "0.66" "0.56" "0.82" "0.78" "0.58" "0.58" "0.84" "0.84" "1.08" "1.04" "0.64" "0.54" "0.72" "0.66" "1.04" "0.98" "0.6" "0.54" "1.14" "1.08" "1.32" "1.36" "0.52" "0.68" "0.84" "0.84" "0.96" "0.98" "0.64" "0.64" "0.76" "0.58" "0.86" "0.88" "1.48" "1.5" "1.72" "1.34" "0.96" "0.98" "0.64" "0.66" "0.96" "0.64" "0.68" "0.82" "1.1" "0.54" "0.72" "1.48" "1.22" "1.22" "0.78" "0.62" "Intervals" "0.86" "0.9" "1.2" "1.22" "0.8" "0.32" "1.28" "1.3" "1.52" "1.52" "1.36" "1.34" "0.48" "0.54" "0.78" "0.82" "0.68" "0.6" "0.88" "0.88" "1.16" "1.16" "0.66" "0.64" "0.74" "0.8" "1.04" "0.56" "0.64" "0.62" "1.12" "0.72" "1.32" "1.34" "0.72" "0.74" "0.84" "0.84" "1" "1.04" "0.62" "0.52" "0.64" "0.78" "0.78" "0.72" "1.42" "1.42" "1.8" "1.52" "1.02" "0.72" "0.62" "0.58" "0.96" "0.92" "0.86" "0.46" "1.06" "0.6" "0.74" "0.38" "1.12" "1.12" "0.78" "0.68" "Intervals" "0.92" "0.78" "1.24" "1.24" "0.78" "0.48" "1.16" "1.16" "1.5" "1.5" "1.48" "1.5" "0.46" "0.5" "0.88" "0.8" "0.5" "0.58" "0.92" "0.92" "1.14" 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