<jupyter_start><jupyter_text>Ingest ERDDAP Data to output to Calvin (ODV)- erddap has an odvText option but for the ALAMO's it seems to skip profiles on ingest- clearly files without lat/lon get skipped but some others do as well.Need to modify the header file:```//https://ferret.pmel.noaa.gov/alamo/erddap/images/info.html//2021-06-14T22:36:36//UTF-8//ERDDAP - Version 2.11//https://data.pmel.noaa.gov/alamo/erddap/tabledap/arctic_heat_alamo_profiles_11010.html//ODV Spreadsheet V4.6//GeneralField//Profiles//label="Cruise" value_type="INDEXED_TEXT" is_primary_variable="F" //label="Station" value_type="INDEXED_TEXT" is_primary_variable="F" //label="Type" value_type="TEXT:2" is_primary_variable="F" //label="Longitude [degrees_east]" value_type="DOUBLE" is_primary_variable="F" comment="Longitude of the station, best estimate" //label="Latitude [degrees_north]" value_type="DOUBLE" is_primary_variable="F" comment="Latitude of the station, best estimate" //label="profileid" value_type="INDEXED_TEXT" is_primary_variable="F" //label="yyyy-mm-ddThh:mm:ss.sss" value_type="DOUBLE" is_primary_variable="T" comment="Time" //label="FLOAT_SERIAL_NO" value_type="INDEXED_TEXT" is_primary_variable="F" comment="Unique  instrument identifier (e.g. instrument serial number)" //label="CYCLE_NUMBER" value_type="INTEGER" is_primary_variable="F" comment="Instrument dive cycle number" //label="PRES [decibar]" value_type="DOUBLE" is_primary_variable="F" comment="Sea water pressure, equals 0 at sea-level" //label="TEMP [degree_Celsius]" value_type="DOUBLE" is_primary_variable="F" comment="Sea temperature in-situ ITS-90 scale" //label="PSAL [PSU]" value_type="DOUBLE" is_primary_variable="F" comment="Practical salinity" Cruise	Station	Type	Longitude [degrees_east]	Latitude [degrees_north]	profileid	yyyy-mm-ddThh:mm:ss.sss	FLOAT_SERIAL_NO	CYCLE_NUMBER	PRES [decibar]	TEMP [degree_Celsius]	PSAL [PSU]```<jupyter_code>from erddapy import ERDDAP
import pandas as pd
import numpy as np
server_url='https://data.pmel.noaa.gov/alamo/erddap/'

e = ERDDAP(server=server_url)

df = pd.read_csv(e.get_search_url(response='csv', search_for='11010'))
dfm2 = {}
for dataset_id in sorted(df['Dataset ID'].values):
    print(f'{dataset_id}')

    try:
        e = ERDDAP(server=server_url,
            protocol='tabledap',
            response='csv'
        )
        e.dataset_id=dataset_id
    except HTTPError:
        print('Failed to generate url {}'.format(dataset_id))
        continue
    try:
        dftemp = e.to_pandas(
                            index_col='time (UTC)',
                            parse_dates=True,
                            skiprows=(1,)  # units information can be dropped.
                            )
        dftemp.columns = [x[1].split()[0] for x in enumerate(dftemp.columns)]

        ##resample as daily data 
        dfm2.update({dataset_id: dftemp})
    except:
        pass
dfm2['arctic_heat_alamo_profiles_11010'].groupby('profileid').count().plot(figsize=(12,2))
dfm2['arctic_heat_alamo_profiles_11010'].dropna().groupby('profileid').count()
# dfm2['arctic_heat_alamo_profiles_11010']['profileid'].plot()
dfm2['arctic_heat_alamo_profiles_11010'].dropna().to_csv('arctic_heat_alamo_profiles_11010_pandas.csv')<jupyter_output><empty_output>
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