Load data from DataFrame

  import 
  
 datetime 
 from 
  
 google.cloud 
  
 import 
  bigquery 
 
 import 
  
 pandas 
 import 
  
 pytz 
 # Construct a BigQuery client object. 
 client 
 = 
  bigquery 
 
 . 
  Client 
 
 () 
 # TODO(developer): Set table_id to the ID of the table to create. 
 # table_id = "your-project.your_dataset.your_table_name" 
 records 
 = 
 [ 
 { 
 "title" 
 : 
 "The Meaning of Life" 
 , 
 "release_year" 
 : 
 1983 
 , 
 "length_minutes" 
 : 
 112.5 
 , 
 "release_date" 
 : 
 pytz 
 . 
 timezone 
 ( 
 "Europe/Paris" 
 ) 
 . 
 localize 
 ( 
 datetime 
 . 
 datetime 
 ( 
 1983 
 , 
 5 
 , 
 9 
 , 
 13 
 , 
 0 
 , 
 0 
 )) 
 . 
 astimezone 
 ( 
 pytz 
 . 
 utc 
 ), 
 # Assume UTC timezone when a datetime object contains no timezone. 
 "dvd_release" 
 : 
 datetime 
 . 
 datetime 
 ( 
 2002 
 , 
 1 
 , 
 22 
 , 
 7 
 , 
 0 
 , 
 0 
 ), 
 }, 
 { 
 "title" 
 : 
 "Monty Python and the Holy Grail" 
 , 
 "release_year" 
 : 
 1975 
 , 
 "length_minutes" 
 : 
 91.5 
 , 
 "release_date" 
 : 
 pytz 
 . 
 timezone 
 ( 
 "Europe/London" 
 ) 
 . 
 localize 
 ( 
 datetime 
 . 
 datetime 
 ( 
 1975 
 , 
 4 
 , 
 9 
 , 
 23 
 , 
 59 
 , 
 2 
 )) 
 . 
 astimezone 
 ( 
 pytz 
 . 
 utc 
 ), 
 "dvd_release" 
 : 
 datetime 
 . 
 datetime 
 ( 
 2002 
 , 
 7 
 , 
 16 
 , 
 9 
 , 
 0 
 , 
 0 
 ), 
 }, 
 { 
 "title" 
 : 
 "Life of Brian" 
 , 
 "release_year" 
 : 
 1979 
 , 
 "length_minutes" 
 : 
 94.25 
 , 
 "release_date" 
 : 
 pytz 
 . 
 timezone 
 ( 
 "America/New_York" 
 ) 
 . 
 localize 
 ( 
 datetime 
 . 
 datetime 
 ( 
 1979 
 , 
 8 
 , 
 17 
 , 
 23 
 , 
 59 
 , 
 5 
 )) 
 . 
 astimezone 
 ( 
 pytz 
 . 
 utc 
 ), 
 "dvd_release" 
 : 
 datetime 
 . 
 datetime 
 ( 
 2008 
 , 
 1 
 , 
 14 
 , 
 8 
 , 
 0 
 , 
 0 
 ), 
 }, 
 { 
 "title" 
 : 
 "And Now for Something Completely Different" 
 , 
 "release_year" 
 : 
 1971 
 , 
 "length_minutes" 
 : 
 88.0 
 , 
 "release_date" 
 : 
 pytz 
 . 
 timezone 
 ( 
 "Europe/London" 
 ) 
 . 
 localize 
 ( 
 datetime 
 . 
 datetime 
 ( 
 1971 
 , 
 9 
 , 
 28 
 , 
 23 
 , 
 59 
 , 
 7 
 )) 
 . 
 astimezone 
 ( 
 pytz 
 . 
 utc 
 ), 
 "dvd_release" 
 : 
 datetime 
 . 
 datetime 
 ( 
 2003 
 , 
 10 
 , 
 22 
 , 
 10 
 , 
 0 
 , 
 0 
 ), 
 }, 
 ] 
 dataframe 
 = 
 pandas 
 . 
 DataFrame 
 ( 
 records 
 , 
 # In the loaded table, the column order reflects the order of the 
 # columns in the DataFrame. 
 columns 
 = 
 [ 
 "title" 
 , 
 "release_year" 
 , 
 "length_minutes" 
 , 
 "release_date" 
 , 
 "dvd_release" 
 , 
 ], 
 # Optionally, set a named index, which can also be written to the 
 # BigQuery table. 
 index 
 = 
 pandas 
 . 
 Index 
 ( 
 [ 
 "Q24980" 
 , 
 "Q25043" 
 , 
 "Q24953" 
 , 
 "Q16403" 
 ], 
 name 
 = 
 "wikidata_id" 
 ), 
 ) 
 job_config 
 = 
  bigquery 
 
 . 
  LoadJobConfig 
 
 ( 
 # Specify a (partial) schema. All columns are always written to the 
 # table. The schema is used to assist in data type definitions. 
 schema 
 = 
 [ 
 # Specify the type of columns whose type cannot be auto-detected. For 
 # example the "title" column uses pandas dtype "object", so its 
 # data type is ambiguous. 
  bigquery 
 
 . 
  SchemaField 
 
 ( 
 "title" 
 , 
  bigquery 
 
 . 
  enums 
 
 . 
  SqlTypeNames 
 
 . 
  STRING 
 
 ), 
 # Indexes are written if included in the schema by name. 
  bigquery 
 
 . 
  SchemaField 
 
 ( 
 "wikidata_id" 
 , 
  bigquery 
 
 . 
  enums 
 
 . 
  SqlTypeNames 
 
 . 
  STRING 
 
 ), 
 ], 
 # Optionally, set the write disposition. BigQuery appends loaded rows 
 # to an existing table by default, but with WRITE_TRUNCATE write 
 # disposition it replaces the table with the loaded data. 
 write_disposition 
 = 
 "WRITE_TRUNCATE" 
 , 
 ) 
 job 
 = 
 client 
 . 
  load_table_from_dataframe 
 
 ( 
 dataframe 
 , 
 table_id 
 , 
 job_config 
 = 
 job_config 
 ) 
 # Make an API request. 
  job 
 
 . 
 result 
 () 
 # Wait for the job to complete. 
 table 
 = 
 client 
 . 
  get_table 
 
 ( 
 table_id 
 ) 
 # Make an API request. 
 print 
 ( 
 "Loaded 
 {} 
 rows and 
 {} 
 columns to 
 {} 
 " 
 . 
 format 
 ( 
 table 
 . 
  num_rows 
 
 , 
 len 
 ( 
 table 
 . 
 schema 
 ), 
 table_id 
 ) 
 )