def store_and_parse(document):
"""
INPUT: dataframe with event id and description
OUTPUT: sql inserts into database
This function takes in the dataframe, parses the text data, and stores the
dependencies, associated words and their parts of speech into a Postgres
database.
'"""
result = []
# while loop necessary because of the parse server timing out occasionally and
# needing to be hit again
while type(result) == list:
result = loads(server.parse(document))
sentences = result['sentences']
print "Length of sentences :: ", len(sentences)
dependencies_list = ps.parse_document(sentences)
new_frame = cd.store_the_dependencies(dependencies_list)
return new_frame
def store_and_parse(document):
"""
INPUT: dataframe with event id and description
OUTPUT: sql inserts into database
This function takes in the dataframe, parses the text data, and stores the
dependencies, associated words and their parts of speech into a Postgres
database.
'"""
result = []
# while loop necessary because of the parse server timing out occasionally and
# needing to be hit again
while type(result) == list:
result = loads(server.parse(document))
sentences = result["sentences"]
print "Length of sentences :: ", len(sentences)
dependencies_list = ps.parse_document(sentences)
new_frame = cd.store_the_dependencies(dependencies_list)
return new_frame
def store_and_parse(dataframe): """ INPUT: dataframe with event id and description OUTPUT: sql inserts into database This function takes in the dataframe, parses the text data, and stores the dependencies, associated words and their parts of speech into a Postgres database. '""" for i in dataframe.index: this_acct_type = dataframe.acct_type.ix[i] this_event_id = dataframe.event_id.ix[i] document = dataframe.description.ix[i] result = [] # while loop necessary because of the parse server timing out occasionally and needing to be hti again while type(result) == list: result = loads(server.parse(document)) sentences = result['sentences'] dependency_list = ps.parse_document(sentences, this_event_id, this_acct_type) sq.write_to_sql(dependency_list)
def store_and_parse(dataframe):
"""
INPUT: dataframe with event id and description
OUTPUT: sql inserts into database
This function takes in the dataframe, parses the text data, and stores the
dependencies, associated words and their parts of speech into a Postgres
database.
'"""
for i in dataframe.index:
this_acct_type = dataframe.acct_type.ix[i]
this_event_id = dataframe.event_id.ix[i]
document = dataframe.description.ix[i]
result = []
# while loop necessary because of the parse server timing out occasionally and needing to be hti again
while type(result) == list:
result = loads(server.parse(document))
sentences = result['sentences']
dependency_list = ps.parse_document(sentences, this_event_id,
this_acct_type)
sq.write_to_sql(dependency_list)
