pandas print all non empty rows <p>I have this data</p> <pre><code>time-stamp ccount A B C D E F G H I 2015-03-03T23:43:33+0000 0 0 0 0 0 0 0 0 0 0 2015-03-04T06:33:28+0000 0 0 0 0 0 0 0 0 0 0 2015-03-04T06:18:38+0000 0 0 0 0 0 0 0 0 0 0 2015-03-04T05:36:43+0000 0 0 0 1 0 0 0 0 0 0 2015-03-04T05:29:09+0000 0 0 0 1 0 0 0 0 1 0 2015-03-04T07:01:11+0000 0 0 1 0 1 0 0 0 0 0 2015-03-03T15:27:06+0000 19 0 1 0 1 0 0 0 0 0 2015-03-03T15:43:38+0000 10 0 1 0 1 1 0 0 0 0 2015-03-03T18:16:26+0000 0 0 0 1 0 0 0 0 0 0 2015-03-03T18:19:48+0000 0 0 0 0 0 0 0 0 0 0 2015-03-03T18:20:02+0000 4 0 0 0 0 1 0 0 0 0 2015-03-03T20:21:55+0000 2 0 0 0 0 0 1 0 0 0 2015-03-03T20:37:36+0000 0 0 0 0 0 0 0 0 0 0 2015-03-04T03:03:51+0000 1 0 0 0 0 0 1 0 0 0 2015-03-03T16:33:04+0000 9 0 0 0 0 0 0 0 0 0 2015-03-03T16:18:13+0000 1 0 0 0 0 0 0 0 0 0 2015-03-03T16:34:18+0000 4 0 0 0 0 0 0 0 0 0 2015-03-03T18:11:36+0000 5 0 0 0 0 0 0 0 0 0 2015-03-03T18:24:35+0000 0 0 0 0 0 0 0 0 0 0 </code></pre> <p>I want to slice all rows which have atleast single one ("1") in their columns A-to-I. i.e. for above data , output will be</p> <pre><code>time-stamp ccount A B C D E F G H I 2015-03-04T05:36:43+0000 0 0 0 1 0 0 0 0 0 0 2015-03-04T05:29:09+0000 0 0 0 1 0 0 0 0 1 0 2015-03-04T07:01:11+0000 0 0 1 0 1 0 0 0 0 0 2015-03-03T15:27:06+0000 19 0 1 0 1 0 0 0 0 0 2015-03-03T15:43:38+0000 10 0 1 0 1 1 0 0 0 0 2015-03-03T18:16:26+0000 0 0 0 1 0 0 0 0 0 0 2015-03-03T18:20:02+0000 4 0 0 0 0 1 0 0 0 0 2015-03-03T20:21:55+0000 2 0 0 0 0 0 1 0 0 0 2015-03-04T03:03:51+0000 1 0 0 0 0 0 1 0 0 0 </code></pre> <p>i.e. we have ignored all the rows which dont have a "1" in any of the columns from [A:I]</p>