Removing numerical data from txt file

Inport a txt file, and remove all numerical data, have only text left. when importing text file, the text gets surrounded by quotes.

Answer 1

[Sulaymon Eshkabilov]

Here is one of the possible solutions for this exercise regexprep():

Text=readlines('Citation.txt')  % Read data file with texts and numbers

Text = 27×1 string array
    "JOURNAL=Frontiers in Plant Science     "
    "→"
    "VOLUME=11      "
    "→"
    "YEAR=2020   "
    "→→"
    "URL=https://www.frontiersin.org/articles/10.3389/fpls.2020.613760     "
    "→  "
    "DOI=10.3389/fpls.2020.613760    "
    "→"
    "ISSN=1664-462X   "
    ""
    "ABSTRACT=Excessive nitrogen (N) application is widespread in Southern China. The effects of N fertilization on soil properties and crop physiology are poorly understood in "
    "tropical red loam soil. We conducted a field experiment to evaluate the effect of nitrogen fertilization rates on physiological attributes (chlorophyll, plant metabolic "
    "enzymes, soluble matters) on banana leaves, soil properties (soil enzymes, soil organic matter (SOM), soil available nutrients) as well as banana crop yield in a subtropical "
    "region of southern China. The N rates tested were 0 (N<sub>0</sub>), 145 (N<sub>145</sub>), 248 (N<sub>248</sub>), 352 (N<sub>352</sub>), 414 (N<sub>FT</sub>), and 455 (N<sub>455</sub>) "
    "g N per plant. The correlations among soil factors, leaf physiological factors and crop yield were evaluated. The results indiated that the high rates of N fertilization (N<sub>FT</sub> "
    "and N<sub>455</sub>) significantly decreased soil available potassium (K) content, available phosphorus (P) content, glutamine synthetase (GS) activity, and soluble protein and sugar "
    "contents compared with lower N rates. The N<sub>352</sub> treatment had the highest crop yields compared with higher N rates treatments, followed by the N<sub>455</sub> treatment. However, "
    "there were no significant differences in crop yields among N fertilization treatments. Factor analysis showed that the N<sub>352</sub> treatment had the highest integrated score for soil "
    "and leaf physiological factors among all treatments. Moreover, the N<sub>352</sub> treatment was the most effective in improving carbon and nitrogen metabolism in banana. Crop yield was "
    "significantly and positively linearly correlated with the integrated score (r = 0.823, p < 0.05). Path analysis revealed that invertase, SOM and sucrose synthase (SS) had a strong positive "
    "effect on banana yield. Canonical correspondence analysis (CCA) suggested that available K, invertase, acid phosphatase and available P were the most important factors impacting leaf"
    " physiological attributes. Cluster analysis demonstrated distinct differences in N application treatment related to variations in soil and leaf factors. This study suggested that excessive "
    "N fertilization had a negative effect on soil fertility, crop physiology and yield. The lower N rates were more effective in improving crop yield than higher rates of N fertilization. "
    "The N rate of 352 g N per plant (N<sub>352</sub>) was recommended to reduce excess N input while maintaining the higher yield for local farmers’ banana planting."
    ""

A = regexprep(Text, '\d+(?:_(?=\d))?', '') % All numbers removed

A = 27×1 string array
    "JOURNAL=Frontiers in Plant Science     "
    "→"
    "VOLUME=      "
    "→"
    "YEAR=   "
    "→→"
    "URL=https://www.frontiersin.org/articles/./fpls..     "
    "→  "
    "DOI=./fpls..    "
    "→"
    "ISSN=-X   "
    ""
    "ABSTRACT=Excessive nitrogen (N) application is widespread in Southern China. The effects of N fertilization on soil properties and crop physiology are poorly understood in "
    "tropical red loam soil. We conducted a field experiment to evaluate the effect of nitrogen fertilization rates on physiological attributes (chlorophyll, plant metabolic "
    "enzymes, soluble matters) on banana leaves, soil properties (soil enzymes, soil organic matter (SOM), soil available nutrients) as well as banana crop yield in a subtropical "
    "region of southern China. The N rates tested were  (N<sub></sub>),  (N<sub></sub>),  (N<sub></sub>),  (N<sub></sub>),  (N<sub>FT</sub>), and  (N<sub></sub>) "
    "g N per plant. The correlations among soil factors, leaf physiological factors and crop yield were evaluated. The results indiated that the high rates of N fertilization (N<sub>FT</sub> "
    "and N<sub></sub>) significantly decreased soil available potassium (K) content, available phosphorus (P) content, glutamine synthetase (GS) activity, and soluble protein and sugar "
    "contents compared with lower N rates. The N<sub></sub> treatment had the highest crop yields compared with higher N rates treatments, followed by the N<sub></sub> treatment. However, "
    "there were no significant differences in crop yields among N fertilization treatments. Factor analysis showed that the N<sub></sub> treatment had the highest integrated score for soil "
    "and leaf physiological factors among all treatments. Moreover, the N<sub></sub> treatment was the most effective in improving carbon and nitrogen metabolism in banana. Crop yield was "
    "significantly and positively linearly correlated with the integrated score (r = ., p < .). Path analysis revealed that invertase, SOM and sucrose synthase (SS) had a strong positive "
    "effect on banana yield. Canonical correspondence analysis (CCA) suggested that available K, invertase, acid phosphatase and available P were the most important factors impacting leaf"
    " physiological attributes. Cluster analysis demonstrated distinct differences in N application treatment related to variations in soil and leaf factors. This study suggested that excessive "
    "N fertilization had a negative effect on soil fertility, crop physiology and yield. The lower N rates were more effective in improving crop yield than higher rates of N fertilization. "
    "The N rate of  g N per plant (N<sub></sub>) was recommended to reduce excess N input while maintaining the higher yield for local farmers’ banana planting."
    ""

(2) another data file:

Atext=readlines('DATA_TEXT.txt')

Atext = 16×1 string array
    "ABSTRACT={The effects of N fertilization on soil properties and crop physiology are poorly understood in tropical red loam soil."
    " We conducted a field experiment to evaluate the effect of nitrogen fertilization rates on physiological attributes (chlorophyll, plant metabolic enzymes, soluble matters) on banana leaves, soil "
    "properties (soil enzymes, soil organic matter (SOM), soil available nutrients) as well as banana crop yield in a subtropical region of southern China. The N rates tested were 0 (N<sub>0</sub>), "
    "145 (N<sub>145</sub>), 248 (N<sub>248</sub>), 352 (N<sub>352</sub>), 414 (N<sub>FT</sub>), and 455 (N<sub>455</sub>) g N per plant. The correlations among soil factors, leaf physiological factors "
    "and crop yield were evaluated. The results indiated that the high rates of N fertilization (N<sub>FT</sub> and N<sub>455</sub>) significantly decreased soil available potassium (K) content, "
    "available phosphorus (P) content, glutamine synthetase (GS) activity, and soluble protein and sugar contents compared with lower N rates. The N<sub>352</sub> treatment had the highest crop yields "
    "compared with higher N rates treatments, followed by the N<sub>455</sub> treatment. However, there were no significant differences in crop yields among N fertilization treatments. "
    "Factor analysis showed that the N<sub>352</sub> treatment had the highest integrated score for soil and leaf physiological factors among all treatments. Moreover, the N<sub>352</sub> "
    "treatment was the most effective in improving carbon and nitrogen metabolism in banana. Crop yield was significantly and positively linearly correlated with the integrated score (r = 0.823, p < 0.05). "
    "{1 2 3 4 5 6 7 8 9 10}. 2023. Feb 18, 12:24 am."
    "Path analysis revealed that invertase, SOM and sucrose synthase (SS) had a strong positive effect on banana yield. Canonical correspondence analysis (CCA) suggested that available K, "
    "invertase, acid phosphatase and available P were the most important factors impacting leaf physiological attributes. Cluster analysis demonstrated distinct differences in N application "
    "treatment related to variations in soil and leaf factors. This study suggested that excessive N fertilization had a negative effect on soil fertility, crop physiology and yield. "
    "The lower N rates were more effective in improving crop yield than higher rates of N fertilization. The N rate of 352 g N per plant (N<sub>352</sub>) was recommended to reduce excess"
    " N input while maintaining the higher yield for local farmers’ banana planting.}"
    "}"

A = regexprep(Atext, '\d+(?:_(?=\d))?', '')

A = 16×1 string array
    "ABSTRACT={The effects of N fertilization on soil properties and crop physiology are poorly understood in tropical red loam soil."
    " We conducted a field experiment to evaluate the effect of nitrogen fertilization rates on physiological attributes (chlorophyll, plant metabolic enzymes, soluble matters) on banana leaves, soil "
    "properties (soil enzymes, soil organic matter (SOM), soil available nutrients) as well as banana crop yield in a subtropical region of southern China. The N rates tested were  (N<sub></sub>), "
    " (N<sub></sub>),  (N<sub></sub>),  (N<sub></sub>),  (N<sub>FT</sub>), and  (N<sub></sub>) g N per plant. The correlations among soil factors, leaf physiological factors "
    "and crop yield were evaluated. The results indiated that the high rates of N fertilization (N<sub>FT</sub> and N<sub></sub>) significantly decreased soil available potassium (K) content, "
    "available phosphorus (P) content, glutamine synthetase (GS) activity, and soluble protein and sugar contents compared with lower N rates. The N<sub></sub> treatment had the highest crop yields "
    "compared with higher N rates treatments, followed by the N<sub></sub> treatment. However, there were no significant differences in crop yields among N fertilization treatments. "
    "Factor analysis showed that the N<sub></sub> treatment had the highest integrated score for soil and leaf physiological factors among all treatments. Moreover, the N<sub></sub> "
    "treatment was the most effective in improving carbon and nitrogen metabolism in banana. Crop yield was significantly and positively linearly correlated with the integrated score (r = ., p < .). "
    "{         }. . Feb , : am."
    "Path analysis revealed that invertase, SOM and sucrose synthase (SS) had a strong positive effect on banana yield. Canonical correspondence analysis (CCA) suggested that available K, "
    "invertase, acid phosphatase and available P were the most important factors impacting leaf physiological attributes. Cluster analysis demonstrated distinct differences in N application "
    "treatment related to variations in soil and leaf factors. This study suggested that excessive N fertilization had a negative effect on soil fertility, crop physiology and yield. "
    "The lower N rates were more effective in improving crop yield than higher rates of N fertilization. The N rate of  g N per plant (N<sub></sub>) was recommended to reduce excess"
    " N input while maintaining the higher yield for local farmers’ banana planting.}"
    "}"

[Sophia Starzynski]

how can i get rid of the cells that used to hold those numbers

[Sulaymon Eshkabilov]

Please shart your text or dat file to give a proper solution or guidance.

[Sophia Starzynski]

here is the zip folder, the data are all in one column, I only need the notes on the files not the numerical data, and then compress into a spreadsheet.

Answer 2

[Sulaymon Eshkabilov]

Here is the solution:

 unzip('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1300600/CONTROLDS2247_SGI_PPCS_Battery_1142022_1218PM_Splice.zip')
 A = readlines('CONTROLDS2247_SGI_PPCS_Battery_1142022_1218PM_Splice.txt');
 Bnum = regexp(A,'\d*','Match');               % Only numbers
 Ctxt = regexprep(A, '\d+(?:_(?=\d))?', '');   %  Only texts taken out
 
 % Empty cells are cleaned up
 Index1 = (Ctxt(1:end,:)=='-.');
 Ctxt(Index1,:)=[];
 Index2 = (Ctxt(1:end,:)=='.');
 Ctxt(Index2,:)=[]                             % Only text strings are stored and all empty cells are removed   

Ctxt = 10311×1 string array
    "degcal_target_LE"
    "Collected"
    "// :: PM"
    "Delta T"
    "Right Eye Horizontal"
    "Left Eye Horizontal"
    "Left Eye Vertical"
    "Left Eye Pupil"
    "Right Eye Vertical"
    "Right Eye Pupil"
    "End Trial"
    "degcal_target_LE"
    "Collected"
    "// :: PM"
    "Delta T"
    "Right Eye Horizontal"
    "Left Eye Horizontal"
    "Left Eye Vertical"
    "Left Eye Pupil"
    "Right Eye Vertical"
    "Right Eye Pupil"
    "End Trial"
    "degcal_target_LE"
    "Collected"
    "// :: PM"
    "Delta T"
    "Right Eye Horizontal"
    "Left Eye Horizontal"
    "Left Eye Vertical"
    "Left Eye Pupil"

 % Write the cleaned strings into MS Excel
 xlswrite('OUT.xlsx', Ctxt)

[Sophia Starzynski]

is there a way to keep the time and date cell that appears after every collected.

Answer 3

[Sulaymon Eshkabilov]

Here is the solution to keep the time of data collected in the external file:

unzip('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1300600/CONTROLDS2247_SGI_PPCS_Battery_1142022_1218PM_Splice.zip')
 A = readlines('CONTROLDS2247_SGI_PPCS_Battery_1142022_1218PM_Splice.txt');
 Bnum = regexp(A,'\d*','Match');               % Only numbers
 Ctxt = regexprep(A, '\d+(?:_(?=\d))?', '');   %  Only texts taken out
 
 % Keep the dates:
 Index0 = Ctxt(1:end, :)=='// :: PM';
 Ctxt(Index0,:) = A(Index0,:);                   
 % Empty cells are cleaned up:
 Index1 = (Ctxt(1:end,:)=='-.');
 Ctxt(Index1,:)=[];
 Index2 = (Ctxt(1:end,:)=='.');
 Ctxt(Index2,:)=[]  

Ctxt = 10311×1 string array
    "degcal_target_LE"
    "Collected"
    "11/4/2022 12:24:23 PM"
    "Delta T"
    "Right Eye Horizontal"
    "Left Eye Horizontal"
    "Left Eye Vertical"
    "Left Eye Pupil"
    "Right Eye Vertical"
    "Right Eye Pupil"
    "End Trial"
    "degcal_target_LE"
    "Collected"
    "11/4/2022 12:24:34 PM"
    "Delta T"
    "Right Eye Horizontal"
    "Left Eye Horizontal"
    "Left Eye Vertical"
    "Left Eye Pupil"
    "Right Eye Vertical"
    "Right Eye Pupil"
    "End Trial"
    "degcal_target_LE"
    "Collected"
    "11/4/2022 12:24:48 PM"
    "Delta T"
    "Right Eye Horizontal"
    "Left Eye Horizontal"
    "Left Eye Vertical"
    "Left Eye Pupil"

  % Cleaned data is stored in an external file
 xlswrite('OUT.xlsx', Ctxt)    

[Sulaymon Eshkabilov]

The answer solution is acceptable :)