我有一个pandas表,其中包含一个具有String数据类型的列。我需要的是从数据框中排除任何“未找到”作为字符串的行。我正在尝试:
df [df.some_column!=“未找到”],但这不起作用
期待回复。
示例数据:
card_number effective_date expiry_date grouping_name Ac. Year code
0 1206090 28 Sep 2012 21 Aug 2013 Dummy no.1 201213
1 1206090 21 Feb 2013 21 Aug 2013 Dummy no.2 201213
2 1206090 28 Sep 2012 30 Nov 2012 Dummy no.3 201213
3 1206090 03 Dec 2012 21 Aug 2013 Dummy no.3 201213
4 1206090 23 Apr 2013 31 Aug 2013 Dummy no.4 201213
5 1206090 28 Sep 2012 21 Aug 2013 Dummy no.5 201213
6 1206090 28 Sep 2012 21 Aug 2013 Dummy no.6 201213
7 1206090 24 Oct 2012 07 Aug 2013 Not found 201213
8 1206090 08 Jan 2013 08 Jan 2013 Not found 201213
9 1206090 08 Jan 2013 31 Aug 2013 Not found 201213
10 Not found 03 Jul 2013 21 Aug 2013 Dummy no.1 201213
11 Not found 03 Jul 2013 21 Aug 2013 Dummy no.2 201213
额外注意:我的字符串匹配必须非常奇怪...当运行df [grouping_name]!=“未找到”时,我认为7,8,9是真的...有谁知道为什么?
答案 0 :(得分:1)
尝试:
df[df['some_column'] != "Not found"]
解决方案使用样本数据:
df = pd.read_csv("data.csv")
df
card_number effective_date expiry_date grouping_name Ac. Year code
0 1206090 28 Sep 2012 21 Aug 2013 Dummy no.1 201213
1 1206090 21 Feb 2013 21 Aug 2013 Dummy no.2 201213
2 1206090 28 Sep 2012 30 Nov 2012 Dummy no.3 201213
3 1206090 03 Dec 2012 21 Aug 2013 Dummy no.3 201213
4 1206090 23 Apr 2013 31 Aug 2013 Dummy no.4 201213
5 1206090 28 Sep 2012 21 Aug 2013 Dummy no.5 201213
6 1206090 28 Sep 2012 21 Aug 2013 Dummy no.6 201213
7 1206090 24 Oct 2012 07 Aug 2013 Not found 201213
8 1206090 08 Jan 2013 08 Jan 2013 Not found 201213
9 1206090 08 Jan 2013 31 Aug 2013 Not found 201213
10 Not found 03 Jul 2013 21 Aug 2013 Dummy no.1 201213
11 Not found 03 Jul 2013 21 Aug 2013 Dummy no.2 201213
df[df['grouping_name'] != 'Not found']
card_number effective_date expiry_date grouping_name Ac. Year code
0 1206090 28 Sep 2012 21 Aug 2013 Dummy no.1 201213
1 1206090 21 Feb 2013 21 Aug 2013 Dummy no.2 201213
2 1206090 28 Sep 2012 30 Nov 2012 Dummy no.3 201213
3 1206090 03 Dec 2012 21 Aug 2013 Dummy no.3 201213
4 1206090 23 Apr 2013 31 Aug 2013 Dummy no.4 201213
5 1206090 28 Sep 2012 21 Aug 2013 Dummy no.5 201213
6 1206090 28 Sep 2012 21 Aug 2013 Dummy no.6 201213
10 Not found 03 Jul 2013 21 Aug 2013 Dummy no.1 201213
11 Not found 03 Jul 2013 21 Aug 2013 Dummy no.2 201213