How to keep only the consecutive values in a Pandas dataframe using Python

shift

Get the year diffs as OP first did. Then check if equal to 1 or the previous value is 1

yd = df.Year.groupby(df.group).diff().eq(1)
df[yd | yd.shift(-1)]

   group  Year
0      A  2000
1      A  2001
2      A  2002
3      A  2003
5      A  2007
6      A  2008
7      A  2009
8      A  2010
9      A  2011
10     B  2005
11     B  2006
12     B  2007
15     B  2013
16     B  2014
17     B  2015
18     B  2016
19     B  2017

---

Setup

Thx jez

a = [('A',x) for x in range(2000, 2012) if x not in [2004,2006]]
b = [('B',x) for x in range(2005, 2018) if x not in [2008,2010,2012]]
df = pd.DataFrame(a + b, columns=['group','Year'])

If I understand correctly, using diff and cumsum create the additional group key, then groupby it and your group columns, and drop the count equal to 1.

df[df.g.groupby([df.g,df.Year.diff().ne(1).cumsum()]).transform('count').ne(1)]

Out[317]:
    g  Year
0   A  2000
1   A  2001
2   A  2002
3   A  2003
5   A  2007
6   A  2008
7   A  2009
8   A  2010
9   A  2011
10  B  2005
11  B  2006
12  B  2007
15  B  2013
16  B  2014
17  B  2015
18  B  2016
19  B  2017

---

Data

df=pd.DataFrame({'g':list('AAAAAAAAAABBBBBBBBBB',
                 'Year':[2000,2001,2002,2003,2005,2007,2008,2009,2010,2011,2005,2006,2007,2009,2011,2013,2014,2015,2016,2017])]})