title: How to load dataframe into BigQuery partitioned table from cloud function with python
body: <p>I'm a bit surprised that I can't find this answer anywhere. </p>
  
  <p>I have the following schema and set-up:</p>
  
  <pre><code>job_config = bigquery.LoadJobConfig(schema = [
  bigquery.SchemaField("foo", "STRING"),
  bigquery.SchemaField("Timestamp", "TIMESTAMP"),
  bigquery.SchemaField("bar", "INT64"),
  bigquery.SchemaField("id", "STRING")
  ])
  
  load_job = bq_client.load_table_from_dataframe(
      df, '.'.join([PROJECT, DATASET, TABLE]), job_config = job_config
  )
  
  load_job.result()
  </code></pre>
  
  <p>As you can see, I'm loading my data frame table (<code>df</code>) to BigQuery. It is working fine. However, I'd like to load with data frame into a partitioned table and using the Timestamp field to define the date of each partitioned table. </p>
  
  <p>How should I do this?</p>