我有一个csv文件，如下所示。我想删除一个行值之前的所有行[Station Mac，第一次看到，最后一次看到，电源，数据包，BSSID，Probed ESSID]进行进一步处理。我在python中使用panadad libarary来读取此csv文件。我可以按索引删除特定的行，但是可以在更改几秒钟后重新加载文件。我应该怎么做。 您的帮助将不胜感激。
BSSID, First time seen, Last time seen, channel, Speed, Privacy, Cipher, Authentication, Power, # beacons, # IV, LAN IP, ID-length, ESSID, Key
52:62:00:00:03:01, 2018-06-22 11:23:45, 2018-06-22 11:23:45, 9, -1, , , , -1, 0, 0, 0. 0. 0. 0, 0, ,
14:30:04:B2:F5:42, 2018-06-22 11:24:04, 2018-06-22 11:24:04, 11, -1, WPA, , , -88, 0, 1, 0. 0. 0. 0, 0, ,
14:30:04:D6C:95:62, 2018-06-22 11:23:50, 2018-06-22 11:24:08, 6, -1, WPA, , , -85, 0, 2, 0. 0. 0. 0, 0, ,
DC:09:4C:BF:6B:13, 2018-06-22 11:23:58, 2018-06-22 11:24:06, 7, 54, WPA2, CCMP, PSK, -75, 2, 0, 0. 0. 0. 0, 12, Death Stroke,
B4:FB:N4:97:F8:03, 2018-06-22 11:23:46, 2018-06-22 11:24:12, 6, 54, WPA2, CCMP, PSK, -74, 6, 6, 0. 0. 0. 0, 3, CSE,
C4:A8:1D:9K:B9:E8, 2018-06-22 11:23:57, 2018-06-22 11:24:12, 11, 22, WPA2 WPA, CCMP TKIP, PSK, -71, 1, 1, 0. 0. 0. 0, 20, SE-IX (Faculty Only),
78:8A:90:81:C1:31, 2018-06-22 11:23:54, 2018-06-22 11:24:06, 6, 54, WPA2, CCMP, PSK, -71, 4, 0, 0. 0. 0. 0, 3, CSE,
78:8A:20:49:^9:D1, 2018-06-22 11:23:44, 2018-06-22 11:24:12, 11, 54, WPA2, CCMP, PSK, -41, 58, 21, 0. 0. 0. 0, 3, CSE,
14:30:04:B3:FD:A2, 2018-06-22 11:23:46, 2018-06-22 11:24:12, 6, -1, , , , -1, 0, 0, 0. 0. 0. 0, 0, ,
14:30:KL:B3:52:22, 2018-06-22 11:23:47, 2018-06-22 11:24:12, 2, -1, WPA, , , -1, 0, 50, 0. 0. 0. 0, 0, ,
14:30:04:LC:9B:E2, 2018-06-22 11:23:48, 2018-06-22 11:24:01, 3, -1, , , , -1, 0, 0, 0. 0. 0. 0, 0, ,
14:U0:04:B3:52:62, 2018-06-22 11:23:49, 2018-06-22 11:24:12, 11, -1, WPA, , , -1, 0, 92, 0. 0. 0. 0, 0, ,
Station MAC, First time seen, Last time seen, Power, # packets, BSSID, Probed ESSIDs
macaddrees, 2018-06-22 11:23:45, 2018-06-22 11:23:45, -78, 8, 52:62:90:00:03:01,
macaddress, 2018-06-22 11:23:46, 2018-06-22 11:24:05, -73, 4, 14:30:04:BB:19:A2,
macaddress, 2018-06-22 11:23:52, 2018-06-22 11:24:12, -73, 5, (not associated) ,
macaddress, 2018-06-22 11:23:43, 2018-06-22 11:24:12, -71, 9, not assocaited,
macadress, 2018-06-22 11:23:52, 2018-06-22 11:23:52, -70, 2, (not associated) ,
macaddress, 2018-06-22 11:23:48, 2018-06-22 11:24:01, -69, 11, NAN,
macaddress, 2018-06-22 11:23:46, 2018-06-22 11:24:12, -65, 15, NAN,
macaddress, 2018-06-22 11:24:12, 2018-06-22 11:24:12, -62, 2, (not associated) ,
macaddress, 2018-06-22 11:24:01, 2018-06-22 11:24:12, -54, 2, NAN,
macaddress, 2018-06-22 11:23:49, 2018-06-22 11:24:12, -48, 97, NAN,
macaddress, 2018-06-22 11:23:43, 2018-06-22 11:24:12, -35, 54, NAN,UET Smart University
macaddress, 2018-06-22 11:23:47, 2018-06-22 11:24:03, -23, 108, NAN,
macaddress, 2018-06-22 11:23:49, 2018-06-22 11:23:49, -1, 9, NAN,
答案 0 :(得分：1)
我们可以读取文件，然后将split放入列表s中，其中包含2个字符串，一个包含空行之前的所有内容（使用\n\n作为分隔符），另一个包含所有内容后。完成后，我们可以将这些字符串作为CSV读取到单独的DataFrame中：
with open('test.csv') as f:
s = f.read().split('\n\n')
df1 = pd.read_csv(pd.compat.StringIO(s[0]))
df2 = pd.read_csv(pd.compat.StringIO(s[1]))
df1：
BSSID First time seen Last time seen channel \
0 52:62:00:00:03:01 2018-06-22 11:23:45 2018-06-22 11:23:45 9
1 14:30:04:B2:F5:42 2018-06-22 11:24:04 2018-06-22 11:24:04 11
2 14:30:04:D6C:95:62 2018-06-22 11:23:50 2018-06-22 11:24:08 6
3 DC:09:4C:BF:6B:13 2018-06-22 11:23:58 2018-06-22 11:24:06 7
4 B4:FB:N4:97:F8:03 2018-06-22 11:23:46 2018-06-22 11:24:12 6
...
df2：
Station MAC First time seen Last time seen Power # packets \
0 macaddrees 2018-06-22 11:23:45 2018-06-22 11:23:45 -78 8
1 macaddress 2018-06-22 11:23:46 2018-06-22 11:24:05 -73 4
2 macaddress 2018-06-22 11:23:52 2018-06-22 11:24:12 -73 5
3 macaddress 2018-06-22 11:23:43 2018-06-22 11:24:12 -71 9
4 macadress 2018-06-22 11:23:52 2018-06-22 11:23:52 -70 2
答案 1 :(得分：0)
如果您使用的文件中Station Mac之前的行数是一致的，并且知道有多少行，则可以使用pandas read_csv跳过这些行
df1 = pd.read_csv（'filename.csv'，skiprows = 14）
其中14（仅计算Station Mac之前的行数）是要跳过的行数。您还可以使用列表而不是整数来指定要跳过的行。