Problem set 2-9 - Get Hourly Exits

import pandas

def get_hourly_exits(df):
    '''
    The data in the MTA Subway Turnstile data reports on the cumulative
    number of entries and exits per row.  Assume that you have a dataframe
    called df that contains only the rows for a particular turnstile machine
    (i.e., unique SCP, C/A, and UNIT).  This function should change
    these cumulative exit numbers to a count of exits since the last reading
    (i.e., exits since the last row in the dataframe).
    
    More specifically, you want to do two things:
       1) Create a new column called EXITSn_hourly
       2) Assign to the column the difference between EXITSn of the current row 
          and the previous row. If there is any NaN, fill/replace it with 0.
    
    You may find the pandas functions shift() and fillna() to be helpful in this exercise.
    
    Example dataframe below:

          Unnamed: 0   C/A  UNIT       SCP     DATEn     TIMEn    DESCn  ENTRIESn    EXITSn  ENTRIESn_hourly  EXITSn_hourly
    0              0  A002  R051  02-00-00  05-01-11  00:00:00  REGULAR   3144312   1088151                0              0
    1              1  A002  R051  02-00-00  05-01-11  04:00:00  REGULAR   3144335   1088159               23              8
    2              2  A002  R051  02-00-00  05-01-11  08:00:00  REGULAR   3144353   1088177               18             18
    3              3  A002  R051  02-00-00  05-01-11  12:00:00  REGULAR   3144424   1088231               71             54
    4              4  A002  R051  02-00-00  05-01-11  16:00:00  REGULAR   3144594   1088275              170             44
    5              5  A002  R051  02-00-00  05-01-11  20:00:00  REGULAR   3144808   1088317              214             42
    6              6  A002  R051  02-00-00  05-02-11  00:00:00  REGULAR   3144895   1088328               87             11
    7              7  A002  R051  02-00-00  05-02-11  04:00:00  REGULAR   3144905   1088331               10              3
    8              8  A002  R051  02-00-00  05-02-11  08:00:00  REGULAR   3144941   1088420               36             89
    9              9  A002  R051  02-00-00  05-02-11  12:00:00  REGULAR   3145094   1088753              153            333
    '''
    
    #your code here
    df['EXITSn_hourly'] = df['EXITSn']-df['EXITSn'].shift(1)
    
    return df.fillna(0)