PMeinshausen

from selenium import webdriver

browser = webdriver.Firefox()

# The list of book titles is in a pandas dataframe 
# named 'data', in the column 'title'

for row in range(len(data)):
    browser.get("http://www.amazon.com")
    time.sleep(1)

PMeinshausen

--Syntax

SELECT * FROM TF_IDF(
  ON TF
  (
    ON {table|view|(query)} PARTITION BY docid
        [FORMULA('bool'|'log'|'augment'|'normal')]
    ) AS TF PARTITION BY term
    [ON (SELECT term, COUNT(distinct docid) FROM input_table
        GROUP BY term) AS docperterm PARTITION BY term] 

PMeinshausen

--Syntax (version 1.0)

select * from Sentenizer(
  on input_table
  TEXTCOLUMN('text_column_name')
  [ACCUMULATE('accumulate_column_names')]);

PMeinshausen

--Syntax (version 1.0)

SELECT * from PosTagger(
  ON input_table
  TEXTCOLUMN('text_column_name')]
  [ACCUMULATE('accumulate_column_names')]
);

PMeinshausen

--Syntax (version 1.3)
SELECT *
  FROM nGram
    (
     ON {table_name | view_name | (query)}
     TEXT_COLUMN('column_name')
    [DELIMITER('delimiter_regular_expression')]
     GRAMS(gram_number)
    [OVERLAPPING({'true'|'false'})]
    [CASE_INSENSITIVE({'true'|'false'})]

PMeinshausen

--Syntax (version 1.0)

CREATE TABLE model_table_name ( PARTITION KEY(token) ) AS
SELECT token, SUM( category_1 ) AS category_1, ... ,
SUM( category_n ) AS category_n FROM
NaiveBayesText(
  ON input_table
  TEXT_COLUMN( text_column )
  CATEGORY_COLUMN( category_column )
  CATEGORIES( category_1, ... , category_n )

PMeinshausen

--Syntax (version 1.1)
--Use a SELECT statement to call the Levenshtein distance function:

SELECT *
  FROM ldist
    (
      ON table_name
      SOURCE (column1 [, column2,...])
      TARGET(column1)
    [THRESHOLD(value)]

PMeinshausen

--Syntax (version 1.1)

SELECT * FROM WMAVG(
  ON {table_name|view_name|(query)}
  PARTITION BY partition_column
  ORDER BY order_by_column 
  COLUMNS('column_names')
  RETURN_ALL('true'|'false')
  WINDOW_SIZE('window_size')
);

PMeinshausen

--Syntax (version 1.1)
SELECT * FROM VWAP(
  ON {table_name | view_name | (query)}
  PARTITION BY expression [, ...]
  ORDER BY date_column
  [PRICE('price_column')]
  [VOLUME ('volume_column')]
  [TIMEINTERVAL('number_of_seconds')]
  [DT('date_column')]
);

PMeinshausen

--Syntax (version 1.0)

--Unconditional sampling, single sample rate
select * from sample(
   ON ...
  SAMPLEFRACTION('fraction')
  [Seed('seed')]
  
--Unconditional sampling, total approximate sample size
select * from sample (