Pandas: remove observations from a data frame based on mulitple columns

Question

I have a data frame and I need to delete certain observations from it based upon the values of other columns.

  cid      date     unemployment    billsum     id.thomas   loansum     feccanid    amtsum
N00003147   2005.0      5.6           1.0          1336        2.0      S4TN00153   4.500
N00009082   2007.0      3.7           1.0            11        2.0      S6CO00168   13.000
N00013870   2007.0      4.6           3.0          1697        17.5     S2MN00126   1636.709
N00002091   2007.0      3.1           1.0           246        11.5     S0ID00057   238.795
N00006515   2007.0      3.8           2.0          1319        49.5     S8NM00010   966.286

I would like, eg to remove values for id.thomas == 1763 only when date == 2008 through 2012 (my date range is 2005-14). I have tried:

bill_amtmerge = bill_amtmerge[bill_amtmerge['id.thomas']!= 1763 & (bill_amtmerge['date'] > 2007)]

Does someone have an idea on this?

Answer 1

try this:

mask = (df['id.thomas'] == 1763) & (df['date'] >= 2008) & (df['date'] <= 2012)
df = df[~mask]

alternatively you can negate your condition :

df = df[(df['id.thomas'] != 1763) | (df['date'] < 2008) | (df['date'] > 2012)]