title: drop columns in pandas dataframe based on mask
body: <p>I have a  dataframe with various number of values in each columns.  I created a mask that tells me how many values in each column with the following code from another post > I get the following results</p>
  
  <pre><code>count_year_mask = df_mth_return.notnull().sum()
  results in series like this
  AAPL US Equity     312
  GOOGL US Equity    161
  GOOG US Equity      45
  MSFT US Equity     312
  AMZN US Equity     248
  FB US Equity        68
  </code></pre>
  
  <p>I then want to delete all the columns in df_mth_return that are LESS THAN 180 from the above series.  I want the DF to only have columns with > 180 numbers.  So GOOGL, GOOG and FB would be eliminated. I tried this code and got the following error</p>
  
  <pre><code>df_mth_return.drop(np.where(count_year_mask&lt;180))
  ValueError: Buffer has wrong number of dimensions (expected 1, got 3)
  </code></pre>
  
  <p>This seems like a simple mask so not sure what I am doing wrong.  Please help if you can</p>