collecting data for chi squared test

1 view (last 30 days)
Christos Papagrigoriou
Christos Papagrigoriou on 29 Apr 2022
Answered: Voss on 30 Apr 2022
Hello,
I have this data. I import it into matlab and and I need to fill that table out. Can you please give me a hint on how to fill it in a time efficient manner.
  2 Comments
Rik
Rik on 29 Apr 2022
If you post the non-efficient code, we can help you optimize it.
Christos Papagrigoriou
Christos Papagrigoriou on 30 Apr 2022
Hello,
table1 = (strcmp(NSCLCR01RadiogenomicDATALABEL.KrasMutation, 'Mutant') & strcmp(NSCLCR01RadiogenomicDATALABEL.SmokingStatus, 'Current'), :);
It turns back a hollow table 0x17

Sign in to comment.

Sign in to answer this question.

Accepted Answer

Voss
Voss on 30 Apr 2022
Ran in:
C = readcell('NSCLCR01Radiogenomic_DATA_LABEL.xlsx');
C(:,[4 6 8 10 18:end]) = [];
headers = C(1,:);
C(1,:) = [];
t = cell2table(C,'VariableNames',headers)
t = 210×13 table
Case ID Patient affiliation Age at Histological Diagnosis Gender Smoking status Histology EGFR mutation status KRAS mutation status ALK translocation status Adjuvant Treatment Chemotherapy Radiation Recurrence ___________ ___________________ _____________________________ __________ ______________ __________________ ____________________ ____________________ ________________________ __________________ ____________ _________ __________ {'AMC-001'} {'Stanford'} 34 {'Male' } {'Nonsmoker'} {'Adenocarcinoma'} {'Wildtype' } {'Mutant' } {'Wildtype' } {'No' } {'No' } {'No'} {'yes'} {'AMC-002'} {'Stanford'} 33 {'Female'} {'Nonsmoker'} {'Adenocarcinoma'} {'Wildtype' } {'Wildtype' } {'Not collected'} {'No' } {'No' } {'No'} {'no' } {'AMC-003'} {'Stanford'} 69 {'Female'} {'Nonsmoker'} {'Adenocarcinoma'} {'Mutant' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'no' } {'AMC-004'} {'Stanford'} 80 {'Female'} {'Nonsmoker'} {'Adenocarcinoma'} {'Wildtype' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'no' } {'AMC-005'} {'Stanford'} 76 {'Male' } {'Former' } {'Adenocarcinoma'} {'Mutant' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'yes'} {'AMC-006'} {'Stanford'} 80 {'Female'} {'Former' } {'Adenocarcinoma'} {'Wildtype' } {'Not collected'} {'Not collected'} {'No' } {'No' } {'No'} {'no' } {'AMC-007'} {'Stanford'} 56 {'Female'} {'Nonsmoker'} {'Adenocarcinoma'} {'Wildtype' } {'Wildtype' } {'Not collected'} {'No' } {'No' } {'No'} {'no' } {'AMC-008'} {'Stanford'} 65 {'Female'} {'Former' } {'Adenocarcinoma'} {'Not collected'} {'Mutant' } {'Not collected'} {'No' } {'No' } {'No'} {'no' } {'AMC-009'} {'Stanford'} 61 {'Male' } {'Former' } {'Adenocarcinoma'} {'Wildtype' } {'Mutant' } {'Wildtype' } {'No' } {'No' } {'No'} {'no' } {'AMC-010'} {'Stanford'} 42 {'Female'} {'Nonsmoker'} {'Adenocarcinoma'} {'Mutant' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'no' } {'AMC-011'} {'Stanford'} 66 {'Female'} {'Former' } {'Adenocarcinoma'} {'Wildtype' } {'Mutant' } {'Wildtype' } {'Yes'} {'Yes'} {'No'} {'yes'} {'AMC-012'} {'Stanford'} 70 {'Female'} {'Nonsmoker'} {'Adenocarcinoma'} {'Mutant' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'yes'} {'AMC-013'} {'Stanford'} 67 {'Female'} {'Nonsmoker'} {'Adenocarcinoma'} {'Mutant' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'no' } {'AMC-014'} {'Stanford'} 78 {'Female'} {'Former' } {'Adenocarcinoma'} {'Wildtype' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'no' } {'AMC-015'} {'Stanford'} 58 {'Male' } {'Former' } {'Adenocarcinoma'} {'Wildtype' } {'Mutant' } {'Not collected'} {'No' } {'No' } {'No'} {'no' } {'AMC-016'} {'Stanford'} 65 {'Male' } {'Former' } {'Adenocarcinoma'} {'Wildtype' } {'Wildtype' } {'Wildtype' } {'No' } {'No' } {'No'} {'no' }
t_mutant_smokers = t(strcmp(t{:,'KRAS mutation status'},'Mutant') & strcmp(t{:,'Smoking status'},'Current'),:)
t_mutant_smokers = 8×13 table
Case ID Patient affiliation Age at Histological Diagnosis Gender Smoking status Histology EGFR mutation status KRAS mutation status ALK translocation status Adjuvant Treatment Chemotherapy Radiation Recurrence ___________ ___________________ _____________________________ __________ ______________ __________________ ____________________ ____________________ ________________________ __________________ ____________ _________ __________ {'R01-003'} {'VA' } 65 {'Male' } {'Current'} {'Adenocarcinoma'} {'Mutant' } {'Mutant'} {'Wildtype'} {'No' } {'No' } {'No' } {'no' } {'R01-024'} {'VA' } 52 {'Male' } {'Current'} {'Adenocarcinoma'} {'Unknown' } {'Mutant'} {'Unknown' } {'No' } {'No' } {'No' } {'yes'} {'R01-053'} {'VA' } 62 {'Male' } {'Current'} {'Adenocarcinoma'} {'Wildtype'} {'Mutant'} {'Wildtype'} {'No' } {'No' } {'No' } {'no' } {'R01-054'} {'VA' } 56 {'Male' } {'Current'} {'Adenocarcinoma'} {'Wildtype'} {'Mutant'} {'Wildtype'} {'Yes'} {'Yes'} {'Yes'} {'yes'} {'R01-095'} {'VA' } 74 {'Male' } {'Current'} {'Adenocarcinoma'} {'Wildtype'} {'Mutant'} {'Wildtype'} {'No' } {'No' } {'No' } {'no' } {'R01-097'} {'VA' } 70 {'Male' } {'Current'} {'Adenocarcinoma'} {'Wildtype'} {'Mutant'} {'Wildtype'} {'No' } {'No' } {'No' } {'no' } {'R01-116'} {'VA' } 54 {'Male' } {'Current'} {'Adenocarcinoma'} {'Wildtype'} {'Mutant'} {'Wildtype'} {'No' } {'No' } {'No' } {'no' } {'R01-137'} {'Stanford'} 50 {'Female'} {'Current'} {'Adenocarcinoma'} {'Wildtype'} {'Mutant'} {'Wildtype'} {'No' } {'No' } {'No' } {'no' }

More Answers (0)

Categories

Find more on Hypothesis Tests in Help Center and File Exchange

Tags

Products


Release

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!