<jupyter_start><jupyter_text>ERDAP with erddapy example for PMEL TELOS platform data ***requires python 3.6*** for passing time information (pandas datetime to timestamp doesn't appear to work in 2.7)  connecting and basic information<jupyter_code>from erddapy import ERDDAP
import pandas as pd
import numpy as np

import datetime

server_url = 'http://dunkel.pmel.noaa.gov:9290/erddap'

e = ERDDAP(server=server_url)
#df = pd.read_csv(e.get_search_url(response='csv', search_for='all'))
df = pd.read_csv(e.get_search_url(response='csv', search_for='TELOS'))
print('We have {} tabledap, {} griddap, and {} wms endpoints.\n'.format(
    len(set(df['tabledap'].dropna())),
    len(set(df['griddap'].dropna())),
    len(set(df['wms'].dropna()))
))
print('Datasets:\n{}'.format('\n'.join(df['Title'])))
df.groupby(['Institution']).groups
gb = df.groupby(['Institution'])

gb.get_group('PMEL RUDICS')
info_url = e.get_info_url(dataset_id=df['Dataset ID'][0], response='csv')

info = pd.read_csv(info_url)

info.head()<jupyter_output><empty_output><jupyter_text>retrieving and plotting data - variables<jupyter_code>print('\n'.join(info.loc[info['Row Type'] == 'variable', 'Variable Name']))

constraints = {
    'time>=': '2017-07-10T00:00:00Z',
    'time<=': str(datetime.datetime.today()),
}

variables = [
 'AT',
 'AS',
 'RH',
 'RS',
 'latitude',
 'longitude',
 'time',
]

d = ERDDAP(server=server_url,
           protocol='tabledap',
           response='csv',
           dataset_id=df['Dataset ID'][0],
           variables=variables,
           constraints=constraints
          )
d.get_download_url()
df = d.to_pandas(
    index_col='time',
    parse_dates=True,
    skiprows=(1,)  # units information can be dropped.
).dropna()

df.head()
print('{} \n {}'.format(df.max(),df.min()))
df.hist(figsize=(9, 9))
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

fig, ax = plt.subplots(figsize=(17, 2))
cs = ax.scatter(df.index, df['AT'], s=15, c=df['AT'], marker='o', edgecolor='none')
fig, ax = plt.subplots(figsize=(17, 2))
cs = ax.scatter(df.index, df['AS'], s=15, c=df['AS'], marker='o', edgecolor='none')
fig, ax = plt.subplots(figsize=(17, 2))
cs = ax.scatter(df.index, df['RH'], s=15, c=df['RH'], marker='o', edgecolor='none')
fig, ax = plt.subplots(figsize=(17, 2))
cs = ax.scatter(df.index, df['RS'], s=15, c=df['RS'], marker='o', edgecolor='none')

import metpy<jupyter_output><empty_output>
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