Update example to use pandas

Author: jrleeman

tutorials/upperair_soundings.py

@@ -14,15 +14,15 @@
 air weather service guide.
 """
 
-from datetime import datetime
 
 import matplotlib.pyplot as plt
 from mpl_toolkits.axes_grid1.inset_locator import inset_axes
-
+import numpy as np
+import pandas as pd
 import metpy.calc as mpcalc
-from metpy.io import get_upper_air_data
-from metpy.io.upperair import UseSampleData
+from metpy.cbook import get_test_data
 from metpy.plots import Hodograph, SkewT
+from metpy.units import units
 
 #########################################################################
 # Getting Data
@@ -31,19 +31,29 @@
 # Upper air data can be obtained using the siphon package, but for this tutorial we will use
 # some of MetPy's sample data. This event is the Veterans Day tornado outbreak in 2002.
 
-with UseSampleData():  # Only needed to use our local sample data
-    dataset = get_upper_air_data(datetime(2002, 11, 11, 0), 'BNA')
+col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
+
+df = pd.read_fwf(get_test_data('nov11_sounding.txt', as_file_obj=False),
+                 skiprows=5, usecols=[0, 1, 2, 3, 6, 7], names=col_names)
+
+df['u_wind'], df['v_wind'] = mpcalc.get_wind_components(df['speed'],
+                                                        np.deg2rad(df['direction']))
+
+# Drop any rows with all NaN values for T, Td, winds
+df = df.dropna(subset=('temperature', 'dewpoint', 'direction', 'speed',
+                       'u_wind', 'v_wind'), how='all').reset_index(drop=True)
 
 ##########################################################################
 
-# We will pull the data out of the example dataset into individual variables.
+# We will pull the data out of the example dataset into individual variables and
+# assign units.
 
-p = dataset.variables['pressure'][:]
-T = dataset.variables['temperature'][:]
-Td = dataset.variables['dewpoint'][:]
-u = dataset.variables['u_wind'][:]
-v = dataset.variables['v_wind'][:]
-wind_speed = dataset.variables['speed'][:]
+p = df['pressure'].values * units.hPa
+T = df['temperature'].values * units.degC
+Td = df['dewpoint'].values * units.degC
+wind_speed = df['speed'].values * units.knots
+wind_dir = df['direction'].values * units.degrees
+u, v = mpcalc.get_wind_components(wind_speed, wind_dir)
 
 ##########################################################################
 # Thermodynamic Calculations