pandas - read CSV, convert columns, calculate average, plot bar chart

I had speedtest-cli running on a regular basis to figure out which provider mobile provider works best in a given location. For this, I gathered all speedtest results in a CSV and just wanted to get the average download and upload speed over all entries.

This is how the CSV looks like:

server name	server id	idle latency	idle jitter	packet loss	download	upload	download bytes	upload bytes	share url	download server count	download latency	download latency jitter	download latency low	download latency high	upload latency	upload latency jitter	upload latency low	upload latency high	idle latency low	idle latency high
foobar	1337	33.1252	8.44775	0	1067331	436851	12296456	4025128		1	737.564	85.5956	39.424	1710.7	323.56	69.9196	35.317	1023	26.975	44.814

and here's the python script how to convert all the things and display them:

import pandas as pd
import matplotlib.pyplot as plt

"""read csv"""

df = pd.read_csv('results.csv')

"""convert bytes to mbps"""

def bytes_to_mbits(num_bytes):
    return num_bytes * 8 / 1e6

"""take just the download and upload columns from the csv file, convert each entries using the function above, round to two decimal points"""

dl_ul = df[['download', 'upload']]
dl_ul.reset_index(drop=True)

download = round(df['download'].apply(bytes_to_mbits), 2)
upload = round(df['upload'].apply(bytes_to_mbits), 2)

"""take the download and upload results, calculate average, put on bar chart"""

plt.bar(['download', 'upload'], [download.mean(), upload.mean()], color=['green', 'red'])
plt.ylabel('speed in mbit/s')
plt.title('speedtest')
plt.show()