HML*_*ude 2 python numpy machine-learning python-3.x pandas
我有以下格式的CSV数据:
+-------------+-------------+-------+
| Location | Num of Reps | Sales |
+-------------+-------------+-------+
| 75894 | 3 | 12 |
| Burkbank | 2 | 19 |
| 75286 | 7 | 24 |
| Carson City | 4 | 13 |
| 27659 | 3 | 17 |
+-------------+-------------+-------+
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该Location列是object数据类型.我想要做的是删除所有具有非数字位置标签的行.所以我想要的输出,如上表所示:
+----------+-------------+-------+
| Location | Num of Reps | Sales |
+----------+-------------+-------+
| 75894 | 3 | 12 |
| 75286 | 7 | 24 |
| 27659 | 3 | 17 |
+----------+-------------+-------+
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现在,我可以通过以下方式对解决方案进行硬编码:
list1 = ['Carson City ', 'Burbank'];
df = df[~df['Location'].isin(['list1'])]
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其灵感来自以下帖子:
但是,我正在寻找的是一般解决方案,适用于上述类型的任何表.
或者你可以做到
df[df['Location'].str.isnumeric()]
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Location Num of Reps Sales 0 75894 3 12 2 75286 7 24 4 27659 3 17
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