# Wind speed data from TexasΒΆ

This is average wind speed and air temperature for data for the state of Texas, USA, on February 26 2018. The original data was downloaded from Iowa State University.

Out:

  station_id  longitude  latitude  air_temperature_c  wind_speed_east_knots  wind_speed_north_knots
0        0F2   -97.7756   33.6017           9.236111               1.032920               -2.357185
1        11R   -96.3742   30.2189          14.214306               1.692155                2.982564
2        2F5  -101.9018   32.7479           7.069444              -1.110056               -0.311412
3        3T5   -96.9500   29.9100          14.496761               1.695097                3.018448
4        5C1   -98.6946   29.7239          12.958333               1.271400                1.090743
/home/leo/src/verde/data/examples/texas-wind.py:42: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all axes decorations.
plt.tight_layout()
/home/leo/src/verde/data/examples/texas-wind.py:43: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure.
plt.show()


import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import verde as vd

# The data are in a pandas.DataFrame
data = vd.datasets.fetch_texas_wind()

# Make a Mercator map of the data using Cartopy
plt.figure(figsize=(8, 6))
ax = plt.axes(projection=ccrs.Mercator())
ax.set_title("Wind speed and air temperature for Texas")
# Plot the air temperature as colored circles and the wind speed as vectors.
plt.scatter(
data.longitude,
data.latitude,
c=data.air_temperature_c,
s=100,
cmap="plasma",
transform=ccrs.PlateCarree(),
)
plt.colorbar().set_label("Air temperature (C)")
ax.quiver(
data.longitude.values,
data.latitude.values,
data.wind_speed_east_knots.values,
data.wind_speed_north_knots.values,
width=0.003,
transform=ccrs.PlateCarree(),
)
# Use an utility function to add tick labels and land and ocean features to the map.
vd.datasets.setup_texas_wind_map(ax)
plt.tight_layout()
plt.show()


Total running time of the script: ( 0 minutes 0.141 seconds)

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