human
I am working on the file "Day_2/solutions/17-Pandas-Intro-Solution.ipynb".
The first task is:
Cleaning data
<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">The truth about data science: cleaning your data is 90% of the work. Fitting the model is easy. Interpreting the results is the other 90%.</p>&mdash.
Jake VanderPlas (@jakevdp) <a href="https://twitter.com/jakevdp/status/742406386525446144">June 13, 2016</a></blockquote>
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Dealing with dates and times
Can you write Python code for it?

Write me a the Python code you requested?
assistant
#Here is the Python code you requested.

# def dateparse(date_str, time_str):
#     diff = pd.to_timedelta((df['End Date'] == '24:00:00').astype(int), unit='d')
#     pd.datetime.strptime(x+y, '%Y-%m-%d%H:%M:%S') 

air_quality = pd.read_csv(fname, header=4, skipfooter=4, na_values='No data', engine='python',
                          parse_dates={'Time': [0, 1]})