title: can we load the data from pandas dataframe to databricks table without spark.sql
body: <p>I have a requirement, to write the data from csv/pandas dataframe to databricks table.
  My python code may not be running on databricks cluster. I may be running on an isolated standalone node. I am using databricks python connector to select the data from databricks table. selects are working. But I am unable to load the data from csv or pandas dataframe to databricks.</p>
  <p>Can I use databricks python connector to load the bulk data in csv/pandas dataframe into databricks table?</p>
  <p>Below is the code snippet for getting the databricks connection and performing selects on standalone node using databricks-python connector.</p>
  <pre><code>from databricks import sql
  conn = sql.connect(server_hostname=self.server_name,
                             http_path=self.http_path,
                             access_token=self.access_token
                             )
  try:
      with conn.cursor() as cursor:
          cursor.execute(qry)
          return cursor.fetchall_arrow().to_pandas()
  except Exception as e:
      print(&quot;Exception Occurred:&quot; + str(e))
  </code></pre>
  <p>Note: My csv file is on Azure ADLS Gen2 storage. I am reading this file to create a pandas dataframe. All I need is to either load the data from pandas to Databricks delta table or read csv file and load the data to delta table. Can this be achieved using databricks-python connector instead of using spark?</p>