title: Remove row with null value from pandas data frame
body: <p>I'm trying to remove a row from my data frame in which one of the columns has a value of null. Most of the help I can find relates to removing NaN values which hasn't worked for me so far. </p>
  
  <p>Here I've created the data frame:</p>
  
  <pre><code>  # successfully crated data frame
   df1 = ut.get_data(symbols, dates) # column heads are 'SPY', 'BBD'
  
  # can't get rid of row containing null val in column BBD
  # tried each of these with the others commented out but always had an 
  # error or sometimes I was able to get a new column of boolean values
  # but i just want to drop the row
  df1 = pd.notnull(df1['BBD']) # drops rows with null val, not working
  df1 = df1.drop(2010-05-04, axis=0)
  df1 = df1[df1.'BBD' != null]
  df1 = df1.dropna(subset=['BBD'])
  df1 = pd.notnull(df1.BBD)
  
  
  # I know the date to drop but still wasn't able to drop the row
  df1.drop([2015-10-30])
  df1.drop(['2015-10-30'])
  df1.drop([2015-10-30], axis=0)
  df1.drop(['2015-10-30'], axis=0)
  
  
  with pd.option_context('display.max_row', None):
      print(df1)
  </code></pre>
  
  <p>Here is my output:</p>
  
  <p><img src="https://i.stack.imgur.com/BMDm6.png" alt="Output"></p>
  
  <p>Can someone please tell me how I can drop this row, preferably both by identifying the row by the null value and how to drop by date? </p>
  
  <p>I haven't been working with pandas very long and I've been stuck on this for an hour. Any advice would be much appreciated. </p>