code: def ingest_from_dataframe(self, df, ingestion_properties):
          
  
          from pandas import DataFrame
  
          if not isinstance(df, DataFrame):
              raise ValueError("Expected DataFrame instance, found {}".format(type(df)))
  
          file_name = "df_{timestamp}_{pid}.csv.gz".format(timestamp=int(time.time()), pid=os.getpid())
          temp_file_path = os.path.join(tempfile.gettempdir(), file_name)
  
          df.to_csv(temp_file_path, index=False, encoding="utf-8", header=False, compression="gzip")
  
          fd = FileDescriptor(temp_file_path)
  
          blob_name = "{db}__{table}__{guid}__{file}".format(
              db=ingestion_properties.database, table=ingestion_properties.table, guid=uuid.uuid4(), file=file_name
          )
  
          containers = self._resource_manager.get_containers()
          container_details = random.choice(containers)
          storage_client = CloudStorageAccount(container_details.storage_account_name, sas_token=container_details.sas)
          blob_service = storage_client.create_block_blob_service()
  
          blob_service.create_blob_from_path(
              container_name=container_details.object_name, blob_name=blob_name, file_path=temp_file_path
          )
  
          url = blob_service.make_blob_url(container_details.object_name, blob_name, sas_token=container_details.sas)
  
          self.ingest_from_blob(BlobDescriptor(url, fd.size), ingestion_properties=ingestion_properties)
  
          fd.delete_files()
          os.unlink(temp_file_path)
docs: Enqueuing an ingest command from local files.
          :param pandas.DataFrame df: input dataframe to ingest.
          :param azure.kusto.ingest.IngestionProperties ingestion_properties: Ingestion properties.