#To read in
df = pd.read_csv('data.csv', parse_dates=True, index_col='Date)

# Prepare a format string: time_format
time_format = '%Y-%m-%d %H:%M'

# Convert date_list into a datetime object: my_datetimes
my_datetimes = pd.to_datetime(date_list, format=time_format)  

# Construct a pandas Series using temperature_list and my_datetimes: time_series
time_series = pd.Series(temperature_list, index=my_datetimes)

# Extract the hour from 9pm to 10pm on '2010-10-11': ts1
ts1 = ts0.loc['2010-10-11 21:00:00':'2010-10-11 22:00:00']

# Extract '2010-07-04' from ts0: ts2
ts2 = ts0.loc['2010-07-04']

# Extract data from '2010-12-15' to '2010-12-31': ts3
ts3 = ts0.loc['2010-12-15':'2010-12-31']

#Sometimes we may wnat to reindex a df using the timeseries index of another df. 
#python fills in non-matching indices with Nan values
# Reindex without fill method: ts3
ts3 = ts2.reindex(ts1.index)

# Reindex with fill method, using forward fill: ts4
ts4 = ts2.reindex(ts1.index, method='ffill')