How do you mix 1d and 2d variables in a pandas dataframe?

I am working with a bucketload of data that has the form:

import pandas as pd
import numpy as np

lat = np.array([80.589, 80.592, 80.595])
lon = np.array([50.268, 50.264, 50.260])
wav = np.array([[486, 605, 666, 821, 777,  719],
                [ 65,  60,  68,  67,  72,   64],
                [866, 946, 882, 855, 999, 1195]])
print("lat shape:",lat.shape)
print("lon shape:",lon.shape)
print("wav shape:",wav.shape)

# lat shape: (3,)
# lon shape: (3,)
# wav shape: (3, 6)

df = pd.DataFrame({
    'Lon': lon,
    'Lat': lat,
    'Wav': wav})

which gives the error "ValueError: Per-column arrays must each be 1-dimensional"

I can work around this by converting the guts of wav to a string and back again when I need it, but that is Ugly Gross, and I would like to find the proper way to handle mix dimension arrays in a pandas dataframe.

Desired result:

print(df.head(1))

      Lon     Lat    Wav
0  50.268  80.589    [486, 605, 666, 821, 777,  719]

>Solution :

How about using a list of lists ?

df = pd.DataFrame({
    'Lon': lon,
    'Lat': lat,
    'Wav': [list(wav_row) for wav_row in wav]
})