title: Finding if values in multiple columns greater than constant in pandas Dataframe
body: <p>This is how my data frame (df) looks:</p>
  <pre><code>id,activity_date,status01_1,status01_2,status02,status03_01,status03_02, status04
  1,2020-12-09 22:13:16,0,0,3560,0,0,0
  1,2020-12-10 01:02:33,8327,0,0,0,0,0 
  1,2020-12-11 01:02:33,0,0,230,0,0,0 
  </code></pre>
  <p>I would like to find if any of the status 01 and 03 columns are over a constant value of 2000 and set a another column (flag) to say the value was greater than 2000.
  So in the input above rows, 1 and 2 will satisfy the condition but not 3.</p>
  <p>The solution I can think of is to filter the data frame to have only  status 01 and 03 columns in a new dataframe and use a complicated np.where clause to set a flag.</p>
  <pre><code>df1 = df[[status01,status03]]
  df1[more_than_2000] = np.where((df1['status01_01'] &gt;= 2000) | (df1['status01_02'] &gt;= 2000) | ...), 1,0)
  </code></pre>
  <p>What is a much better way of doing this?</p>