How to use the siphon.simplewebservice.ndbc.NDBC.realtime_observations function in siphon

"""
NDBC Buoy Meteorological Data Request
=====================================

The NDBC keeps a 45-day recent rolling file for each buoy. This examples shows how to access
the basic meteorological data from a buoy and make a simple plot.
"""

import matplotlib.pyplot as plt

from siphon.simplewebservice.ndbc import NDBC

####################################################
# Get a pandas data frame of all of the observations, meteorological data is the default
# observation set to query.
df = NDBC.realtime_observations('46006')
df.head()

####################################################
# Let's make a simple time series plot to checkout what the data look like.
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(12, 10))
ax2b = ax2.twinx()

# Pressure
ax1.plot(df['time'], df['pressure'], color='black')
ax1.set_ylabel('Pressure [hPa]')

# Wind speed, gust, direction
ax2.plot(df['time'], df['wind_speed'], color='tab:orange')
ax2.plot(df['time'], df['wind_gust'], color='tab:olive', linestyle='--')
ax2b.plot(df['time'], df['wind_direction'], color='tab:blue', linestyle='-')
ax2.set_ylabel('Wind Speed [m/s]')

The NDBC keeps a 40-day recent rolling file for each buoy. This examples shows how to access
the other types of data available for a buoy.
"""

from siphon.simplewebservice.ndbc import NDBC

####################################################
# Request the types of data available from a given buoy.
data_aval = NDBC.buoy_data_types('41002')
print(data_aval)

####################################################
# Get a pandas data frame of all of the observations, meteorological data is the default
# observation set to query.
df = NDBC.realtime_observations('41002', data_type='supl')
df.head()

"""
NDBC Buoy Meteorological Data Request
=====================================

The NDBC keeps a 45-day recent rolling file for each buoy. This examples shows how to access
the basic meteorological data from a buoy and make a simple plot.
"""

import matplotlib.pyplot as plt

from siphon.simplewebservice.ndbc import NDBC

####################################################
# Get a pandas data frame of all of the observations, meteorological data is the default
# observation set to query.
df = NDBC.realtime_observations('46006')
df.head()

####################################################
# Let's make a simple time series plot to checkout what the data look like.
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(12, 10))
ax2b = ax2.twinx()

# Pressure
ax1.plot(df['time'], df['pressure'], color='black')
ax1.set_ylabel('Pressure [hPa]')

# Wind speed, gust, direction
ax2.plot(df['time'], df['wind_speed'], color='tab:orange')
ax2.plot(df['time'], df['wind_gust'], color='tab:olive', linestyle='--')
ax2b.plot(df['time'], df['wind_direction'], color='tab:blue', linestyle='-')
ax2.set_ylabel('Wind Speed [m/s]')