title: Working with dataframe / matrix to create an input for sklearn & Tensorflow
body: <p>I am working with pandas / python /numpy / datalab/bigQuery to generate an input table for machine learning processing. The data is genomic - and right now, I am working with small subset of
  174 rows
  12430 columns</p>
  
  <p>The column names are extracted from bigQuery <code>(df_pik3ca_features = bq.Query(std_sql_features).to_dataframe(dialect='standard',use_cache=True))</code> 
  at the same way, the row names are extracted: <code>samples_rows = bq.Query('SELECT sample_id FROM</code>speedy-emissary-167213.pgp_orielresearch.pgp_PIK3CA_all_features_values_step_3<code>GROUP BY sample_id')</code></p>
  
  <p>what would be the easiest way to create a dataframe / matrix with named rows and columns that were extracted.</p>
  
  <p>I explored the dataframes in pandas and could not find the way to pass the names as parameter.</p>
  
  <p>for empty array, I was able to find the following (numpy) with no names:</p>
  
  <pre><code>a = np.full([num_of_rows, num_of_columns], np.nan)
  a.columns
  </code></pre>
  
  <p>I know R very well (if there is no other way - I hope that I can use it with datalab)</p>
  
  <p>any idea?</p>
  
  <p>Many thanks!</p>