Query Dataset

import sys
import os
import numpy as np
import pandas as pd
import xarray as xr
from pprint import pprint
from datetime import datetime

Database (with Description)

database = xr.open_dataset('http://engaging-opendap.mit.edu:8080/thredds/dodsC/las/id-a1d60eba44/data_usr_local_tomcat_content_cbiomes_20190510_20_darwin_v0.2_cs510_darwin_v0.2_cs510_nutrients.nc.jnl')

Fields/Dimensions

fields = list(database.keys())
dims = list(database.dims)

fields = pd.Series([fields], index = ['Fields'])
fields = pd.DataFrame({'Database Fields' : fields})
dims = pd.Series([dims], index = ['Dimensions'])
dims = pd.DataFrame({'Database Dimensions' : dims})

display(fields)
display(dims)

	Database Fields
Fields	[FeT, PO4, DIN, SiO2, O2]

	Database Dimensions
Dimensions	[DEP_C, LAT_C, LON_C, TIME]

Fields: Generally, the variables being measured
Dimensions: What the variable is being measured over

Example: Susie measured the amount of mayflies ( field ) over time ( dimension )

Dimension Descriptions

#---_Time
timeStart = datetime.fromisoformat(database.TIME.attrs['start'])
timeEnd = datetime.fromisoformat(database.TIME.attrs['end'])
yearRange = timeEnd.year - timeStart.year
timeLogged = round( (yearRange * 365) / int(database.TIME.attrs['length']) )
#----Depth
depths = database.DEP_C.values
#----Lats/Lons
lats = database.LAT_C.values
lons = database.LON_C.values

#TIME
timeSeries = pd.Series([timeStart, timeEnd, database.TIME.attrs['length'], 'every ' + str(timeLogged) + ' days'], index = ['Start', 'End', 'Length', 'Data Logged'])
majorTable = pd.DataFrame({'TIME Values' : timeSeries})

#DEPTH
depthSeries = pd.Series([database.DEP_C.attrs['start'], database.DEP_C.attrs['end'], database.DEP_C.attrs['length'], database.DEP_C.values], index = ['Start', 'End', 'Length', 'Depth List'])
majorTable['DEPTH(m) Values'] = depthSeries

#LATITUDE
latSeries = pd.Series([database.LAT_C.attrs['start'], database.LAT_C.attrs['end'], database.LAT_C.attrs['length']], index = ['Start', 'End', 'Length'])
majorTable['LATITUDE Values'] = latSeries

#LONGITUDE
lonSeries = pd.Series([database.LON_C.attrs['start'], database.LON_C.attrs['end'], database.LON_C.attrs['length']], index = ['Start', 'End', 'Length'])
majorTable['LONGITUDE Values'] = lonSeries

display(majorTable)
pd.set_option('display.max_colwidth', abs(int(database.DEP_C.attrs['end'])))

depths = pd.Series([depths], index = ['Depths List'])
depths = pd.DataFrame({'Depth List' : depths})
display(depths)
pd.set_option('display.max_colwidth', 100)

	TIME Values	DEPTH(m) Values	LATITUDE Values	LONGITUDE Values
Start	1992-01-02 12:00:00	5	-89.75	-179.75
End	2016-08-20 12:00:00	5906.25	89.75	179.75
Length	3000	50	360.00	720.00
Data Logged	every 3 days	NaN	NaN	NaN

Depth List

Depths List

[5.0, 15.0, 25.0, 35.0, 45.0, 55.0, 65.0, 75.004997253418, 85.0250015258789, 95.0950012207031, 105.309997558594, 115.870002746582, 127.150001525879, 139.740005493164, 154.470001220703, 172.399993896484, 194.735000610352, 222.710006713867, 257.470001220703, 299.929992675781, 350.679992675781, 409.929992675781, 477.470001220703, 552.710021972656, 634.734985351563, 722.400024414063, 814.469970703125, 909.739990234375, 1007.15502929688, 1105.90502929688, 1205.53503417969, 1306.20495605469, 1409.15002441406, 1517.09497070313, 1634.17504882813, 1765.13500976563, 1914.15002441406, 2084.03491210938, 2276.22509765625, 2491.25, 2729.25, 2990.25, 3274.25, 3581.25, 3911.25, 4264.25, 4640.25, 5039.25, 5461.25, 5906.25]

Definitions
Start: value the dimension begins at EX: (1, 2, 3…)
End: values the dimension ends with EX: (…4, 5, 6)
Length: amount of items in dimensions EX: (the length of the alphabet is 26)
Data Logged: amount of time between each data log EX: (time data is logged every x days)
Depth List: list of all logged depths in the database EX: (30 meters, 40 meters, etc)

Field Descriptions

field = database.variables['O2'] #field to describe

#Attributes 
fieldTable = pd.Series([field.dims, field.attrs['units'], field.attrs['infile_datatype'], field.attrs['direction'], field.attrs['dataset_index']], index = ['Dimensions', 'Units', 'Datatype', 'Direction', 'Dataset Index'])
fieldTable = pd.DataFrame({str(field.attrs['long_name']) : fieldTable})
display(fieldTable)

	O2 concentration
Dimensions	(TIME, DEP_C, LAT_C, LON_C)
Units	mmol O/m^3
Datatype	FLOAT
Direction	IJKL
Dataset Index	1

A description of the variable’s attributes. To describe a variable of your choosing, enter the field name in the “database.variables[’< YOUR FIELD HERE >’]” space