Click "Estimate requirements" button before using this Data Access URL

In addition to using the above ad hoc .parquet request generation capability you may also script up requests by activity__name, inherently reducing server-side memory and time requirements. Here is an example of reading Dorado data survey-by-survey into a Matlab session:

% File: read_parquet.m
% Read parquet files from STOQS and report the time it takes
campaign_url = "https://stoqs.mbari.org/stoqs_all_dorado";
api_call = "/api/measuredparameter.parquet?collect=name&activity__name__contains=";
surveys = ["Dorado389_2020_006_06_006_06_decim", "Dorado389_2020_035_00_035_00_decim"];
wo = weboptions('CertificateFilename', '', 'Timeout', 300);
for i=1:length(surveys),
    tic;
    disp(strcat("Reading ", surveys(i), " as .parquet"));
    parquet_url = strcat(campaign_url, api_call, surveys(i));
    file = websave(strcat(surveys(i), '.parquet'), parquet_url, wo);
    disp(strcat("Wrote ", file));
    toc;
    tic;
    info = parquetinfo(file);
    T = parquetread(file);
    disp(strcat("Read ", file));
    toc;
end
disp(info.VariableNames)

—————————————————

>> read_parquet
Reading Dorado389_2020_006_06_006_06_decim as .parquet
Wrote /u/mccann/matlab/Dorado389_2020_006_06_006_06_decim.parquet
Elapsed time is 14.278701 seconds.
Read /u/mccann/matlab/Dorado389_2020_006_06_006_06_decim.parquet
Elapsed time is 0.410685 seconds.
Reading Dorado389_2020_035_00_035_00_decim as .parquet
Wrote /u/mccann/matlab/Dorado389_2020_035_00_035_00_decim.parquet
Elapsed time is 14.070438 seconds.
Read /u/mccann/matlab/Dorado389_2020_035_00_035_00_decim.parquet
Elapsed time is 0.097718 seconds.
    Columns 1 through 11

    "adinos"    "altitude"    "bbp420 (m-1)"    "bbp700 (m-1)"    "bg_biolum (ph L^..."    "biolume"    "diatoms"    "fl700_uncorr"    "fluo"    "hdinos"    "intflash (ph s^{..."

    Columns 12 through 19

    "mepCountList (co..."    "nbflash_high (L^..."    "nbflash_low (L^{..."    "nitrate (micromo..."    "oxygen (ml/l)"    "pitch (degree)"    "profile"    "roll (degree)"

    Columns 20 through 30

    "salinity"    "sepCountList (co..."    "sigmat"    "spice"    "temperature (Cel..."    "yaw (degree)"    "platform"    "timevalue"    "depth"    "latitude"    "longitude"
                                                    

Here is visualize_parquet.ipynb which shows how to read and visualize parquet data in Python.
Here is parquet2csv.py which you can execute at the command line to convert parquet data to a comma separated value file.

Set colormap from standard_name: