R - check if NA exists in any column of r dataframe row, then if so remove that row
<p>I have a large dataframe that has many rows and columns, and I would like to remove the rows for which at least 1 column is NA / NaN. Below is a small example of the dataframe I am working with:</p>

<pre><code>  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
</code></pre>

<p>...albeit a bad example because all of the NaNs show up in the last column in this case. i am familiar with the approach of <code>which(is.na(df$column_name))</code> for getting the rows with NA values from an individual column, but again want to do something like this for rows where at least 1 column in a row of a dataframe has an NA value.</p>

<p>Thanks!</p>