Question

我有一个包含许多行和列的大型数据框，我想删除至少有一列是NA / NaN的行。以下是我正在使用的数据框的一个小例子：

  team_id athlete_id GP tm_STL tm_TOV   player_WS
1   13304      75047  1      2      8         NaN
2   13304      75048  1      2      8  0.28563827
3   13304      75049  1      2      8         NaN
4   13304      75050  1      2      8         NaN
5   13304      75053  1      2      8  0.03861989
6   13304      75060  1      2      8 -0.15530707

...虽然是一个糟糕的例子，因为在这种情况下，所有的NaN都显示在最后一列中。我熟悉which(is.na(df$column_name))从单个列获取具有NA值的行的方法，但是对于数据帧的一行中至少有1列具有NA值的行，我再次想要这样做。

谢谢！

Answer 1

尝试使用complete.cases。

> df <- data.frame(col1 = c(1, 2, 3, NA, 5), col2 = c('A', 'B', NA, 'C', 'D'),
             col3 = c(9, NaN, 8, 7, 6))
> df
  col1 col2 col3
1    1    A    9
2    2    B  NaN
3    3 <NA>    8
4   NA    C    7
5    5    D    6
> df[complete.cases(df), ]
  col1 col2 col3
1    1    A    9
5    5    D    6

Answer 2

try { soapMessage.writeTo(System.out); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); }有效：

  ago 12, 2016 12:58:17 PM com.sun.xml.internal.messaging.saaj.client.p2p.HttpSOAPConnection post
    GRAVE: SAAJ0008: respuesta errónea; Not Found
    Exception in thread "main" com.sun.xml.internal.messaging.saaj.SOAPExceptionImpl: com.sun.xml.internal.messaging.saaj.SOAPExceptionImpl: Bad response: (404Not Found
        at com.sun.xml.internal.messaging.saaj.client.p2p.HttpSOAPConnection.call(HttpSOAPConnection.java:149)
        at 
AbstractSoapClient.createRequest(AbstractSoapClient.java:44)
        at SoapClient.main(SoapClient.java:67)
    Caused by: com.sun.xml.internal.messaging.saaj.SOAPExceptionImpl: Bad response: (404Not Found
        at com.sun.xml.internal.messaging.saaj.client.p2p.HttpSOAPConnection.post(HttpSOAPConnection.java:264)
        at com.sun.xml.internal.messaging.saaj.client.p2p.HttpSOAPConnection.call(HttpSOAPConnection.java:145)
        ... 2 more

    CAUSE:

    com.sun.xml.internal.messaging.saaj.SOAPExceptionImpl: Bad response: (404Not Found
        at com.sun.xml.internal.messaging.saaj.client.p2p.HttpSOAPConnection.post(HttpSOAPConnection.java:264)
        at com.sun.xml.internal.messaging.saaj.client.p2p.HttpSOAPConnection.call(HttpSOAPConnection.java:145)
        at AbstractSoapClient.createRequest(AbstractSoapClient.java:44)
        at SoapClient.main(SoapClient.java:67)

如果你正在使用它，它比na.omit更方便，因为它不需要像na.omit(df) ## team_id athlete_id GP tm_STL tm_TOV player_WS ## 2 13304 75048 1 2 8 0.28563827 ## 5 13304 75053 1 2 8 0.03861989 ## 6 13304 75060 1 2 8 -0.15530707，complete.cases或dplyr::filter这样的子集的其他功能。

Answer 3

你可以用它。

df[rowSums(is.na(df))==0,]

#  team_id athlete_id GP tm_STL tm_TOV   player_WS
#2   13304      75048  1      2      8  0.28563827
#5   13304      75053  1      2      8  0.03861989
#6   13304      75060  1      2      8 -0.15530707

这样，您可以计算每行的NA数。你只保留行是非NA的总和为零。

R - 检查r数据帧行的任何列中是否存在NA，如果是，则删除该行

3 个答案: