基于列值删除Pandas中的DataFrame行

daysago line_race rating rw wrating line_date 2007-03-31 62 11 56 1.000000 56.000000 2007-03-10 83 11 67 1.000000 67.000000 2007-02-10 111 9 66 1.000000 66.000000 2007-01-13 139 10 83 0.880678 73.096278 2006-12-23 160 10 88 0.793033 69.786942 2006-11-09 204 9 52 0.636655 33.106077 2006-10-22 222 8 66 0.581946 38.408408 2006-09-29 245 9 70 0.518825 36.317752 2006-09-16 258 11 68 0.486226 33.063381 2006-08-30 275 8 72 0.446667 32.160051 2006-02-11 475 5 65 0.164591 10.698423 2006-01-13 504 0 70 0.142409 9.968634 2006-01-02 515 0 64 0.134800 8.627219 2005-12-06 542 0 70 0.117803 8.246238 2005-11-29 549 0 70 0.113758 7.963072 2005-11-22 556 0 -1 0.109852 -0.109852 2005-11-01 577 0 -1 0.098919 -0.098919 2005-10-20 589 0 -1 0.093168 -0.093168 2005-09-27 612 0 -1 0.083063 -0.083063 2005-09-07 632 0 -1 0.075171 -0.075171 2005-06-12 719 0 69 0.048690 3.359623 2005-05-29 733 0 -1 0.045404 -0.045404 2005-05-02 760 0 -1 0.039679 -0.039679 2005-04-02 790 0 -1 0.034160 -0.034160 2005-03-13 810 0 -1 0.030915 -0.030915 2004-11-09 934 0 -1 0.016647 -0.016647

3条回答

网友

1楼 · 编辑于 2024-04-20 08:55:23

但是对于任何未来的绕过者，您可以提到df = df[df.line_race != 0]在尝试筛选None/缺少的值时不会做任何事情。

是否有效：

df = df[df.line_race != 0]

什么都不做：

df = df[df.line_race != None]

是否有效：

df = df[df.line_race.notnull()]

网友

2楼 · 编辑于 2024-04-20 08:55:23

最好的方法是使用布尔掩蔽：

In [56]: df
Out[56]:
     line_date  daysago  line_race  rating    raw  wrating
0   2007-03-31       62         11      56  1.000   56.000
1   2007-03-10       83         11      67  1.000   67.000
2   2007-02-10      111          9      66  1.000   66.000
3   2007-01-13      139         10      83  0.881   73.096
4   2006-12-23      160         10      88  0.793   69.787
5   2006-11-09      204          9      52  0.637   33.106
6   2006-10-22      222          8      66  0.582   38.408
7   2006-09-29      245          9      70  0.519   36.318
8   2006-09-16      258         11      68  0.486   33.063
9   2006-08-30      275          8      72  0.447   32.160
10  2006-02-11      475          5      65  0.165   10.698
11  2006-01-13      504          0      70  0.142    9.969
12  2006-01-02      515          0      64  0.135    8.627
13  2005-12-06      542          0      70  0.118    8.246
14  2005-11-29      549          0      70  0.114    7.963
15  2005-11-22      556          0      -1  0.110   -0.110
16  2005-11-01      577          0      -1  0.099   -0.099
17  2005-10-20      589          0      -1  0.093   -0.093
18  2005-09-27      612          0      -1  0.083   -0.083
19  2005-09-07      632          0      -1  0.075   -0.075
20  2005-06-12      719          0      69  0.049    3.360
21  2005-05-29      733          0      -1  0.045   -0.045
22  2005-05-02      760          0      -1  0.040   -0.040
23  2005-04-02      790          0      -1  0.034   -0.034
24  2005-03-13      810          0      -1  0.031   -0.031
25  2004-11-09      934          0      -1  0.017   -0.017

In [57]: df[df.line_race != 0]
Out[57]:
     line_date  daysago  line_race  rating    raw  wrating
0   2007-03-31       62         11      56  1.000   56.000
1   2007-03-10       83         11      67  1.000   67.000
2   2007-02-10      111          9      66  1.000   66.000
3   2007-01-13      139         10      83  0.881   73.096
4   2006-12-23      160         10      88  0.793   69.787
5   2006-11-09      204          9      52  0.637   33.106
6   2006-10-22      222          8      66  0.582   38.408
7   2006-09-29      245          9      70  0.519   36.318
8   2006-09-16      258         11      68  0.486   33.063
9   2006-08-30      275          8      72  0.447   32.160
10  2006-02-11      475          5      65  0.165   10.698

更新：现在pandas 0.13已经发布，另一种方法是df.query('line_race != 0')。

网友

3楼 · 编辑于 2024-04-20 08:55:23

如果我理解正确，应该简单到：

df = df[df.line_race != 0]

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