Filtering Pandas Dataframe By Difference Of Adjacent Rows

I have a dataframe indexed by datetime. I want to filter out rows based on the difference between their index and the index of the previous row. So, if my criteria is 'remove all r

Solution 1:

It seems you need boolean indexing with diff for difference and compare with 1 hour Timedelta:

dates=['2005-07-15 17:00:00','2005-07-17 18:00:00', '2005-07-17 19:00:00',  
      '2005-07-17 23:00:00', '2005-07-18 00:00:00']
df = pd.DataFrame({'a':range(5)}, index=pd.to_datetime(dates))

print (df)
                     a
2005-07-15 17:00:00  0
2005-07-17 18:00:00  1
2005-07-17 19:00:00  2
2005-07-17 23:00:00  3
2005-07-18 00:00:00  4

---

diff = df.index.to_series().diff().fillna(0)
print (diff)
2005-07-15 17:00:00   0 days 00:00:00
2005-07-17 18:00:00   2 days 01:00:00
2005-07-17 19:00:00   0 days 01:00:00
2005-07-17 23:00:00   0 days 04:00:00
2005-07-18 00:00:00   0 days 01:00:00
dtype: timedelta64[ns]

mask = diff <= pd.Timedelta(1, unit='h')
print (mask)
2005-07-15 17:00:00     True
2005-07-17 18:00:00    False
2005-07-17 19:00:00     True
2005-07-17 23:00:00    False
2005-07-18 00:00:00     True
dtype: bool

df = df[mask]
print (df)
                     a
2005-07-15 17:00:00  0
2005-07-17 19:00:00  2
2005-07-18 00:00:00  4