Generate additional DynamicMaps from multi-column DataFrame

I use something like the following code (taken from here) to generate data (from external instruments). I had no prior experience with holoviews or pandas, and started simply by plotting the data (of the first instrument) as it came in using a DynamicMap. Now I have many more instruments, and realize to my embarrassment, that I don’t know how to plot any column other than the default first two.
How do I plot the other column versus the first?
I guess I could just duplicate everything (Using a second buffer), but there has to be an easier way.

import numpy as np
import pandas as pd
import holoviews as hv
from holoviews.streams import Buffer
from datetime import datetime

class FakeInstrument(object):
    def __init__(self, offset=0.0):
        self.offset = offset

    def set_offset(self, value):
        self.offset = value

    def read_data(self):
        return np.random.random() + self.offset

instrument = FakeInstrument()

def make_df(data_frequency=0.0, data_phaseshift=0.0, data_magnitude=0.0):
    return pd.DataFrame(data={'Frequency (Hz)': data_frequency, 'Phase shift (deg)': data_phaseshift, 'Magnitude (V)': data_magnitude}, index=[])
empty_reference_df = pd.DataFrame(columns=make_df().columns)
buffer_length = 10
buffer = Buffer(empty_reference_df, length=buffer_length, index=False)
plot1 = hv.DynamicMap(hv.Curve, streams=[buffer])

for f in range(buffer_length):
    value1 = instrument.read_data()
    value2 = instrument.read_data()
    b = make_df(f, value1, value2)  

plot1#Looks okay. By default the first two columns are plotted

plot1.dframe()#looks okay
#plot1.dframe().to_csv('./tmp.csv', index=True, sep='	')#Saving the whole DataFrame to a single file

So this mentions that a solution exists, but doesn’t explicitly state where it can be found.
I guess I’ll keep trying to improve my documentation-reading skills.

I found this. Something like

from functools import partial

plot2 = hv.DynamicMap(partial(hv.Curve, kdims='Frequency (Hz)', vdims='Magnitude (V)'), streams=[buffer])

plot1 + plot2

seems to work.