Mean Pressure Weighted#

Use `metpy.calc.mean_pressure_weighted` as well as pint’s unit support to perform calculations.

The code below uses example data from our test suite to calculate the pressure-weighted mean temperature over a depth of 500 hPa.

```import pandas as pd

from metpy.calc import mean_pressure_weighted
from metpy.cbook import get_test_data
from metpy.units import units
```

Upper air data can be obtained using the siphon package, but for this example we will use some of MetPy’s sample data.

```# Set column names
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']

# Read in test data using col_names
skiprows=5, usecols=[0, 1, 2, 3, 6, 7], names=col_names)
```

Drop any rows with all NaN values for T, Td, winds

```df = df.dropna(subset=('temperature', 'dewpoint', 'direction', 'speed'),
how='all').reset_index(drop=True)
```

Isolate pressure, temperature, and height and add units

```p = df['pressure'].values * units.hPa
T = df['temperature'].values * units.degC
h = df['height'].values * units.meters
```

Calculate the mean pressure weighted temperature over a depth of 500 hPa

```print(mean_pressure_weighted(p, T, height=h, depth=500 * units.hPa))
```
```[<Quantity(272.583109, 'kelvin')>]
```

Total running time of the script: (0 minutes 0.010 seconds)

Gallery generated by Sphinx-Gallery