[DEPRECATED] Wind speed data from TexasΒΆ

Warning

All sample datasets in Verde are deprecated and will be removed in Verde v2.0.0. The tutorials/examples will transition to using Ensaio instead.

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  ...  wind_speed_east_knots  wind_speed_north_knots
0        0F2   -97.7756  ...               1.032920               -2.357185
1        11R   -96.3742  ...               1.692155                2.982564
2        2F5  -101.9018  ...              -1.110056               -0.311412
3        3T5   -96.9500  ...               1.695097                3.018448
4        5C1   -98.6946  ...               1.271400                1.090743

[5 rows x 6 columns]
```

```import cartopy.crs as ccrs
import matplotlib.pyplot as plt

import verde as vd

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

# 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.show()
```

Total running time of the script: ( 0 minutes 0.194 seconds)

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