sparktk.frame.ops.drop_rows module
# vim: set encoding=utf-8
# Copyright (c) 2016 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from sparktk.frame.row import Row
def drop_rows(self, predicate):
"""
Erase any row in the current frame which qualifies.
Parameters
----------
:param predicate: (UDF) Function which evaluates a row to a boolean; rows that answer True are dropped from
the frame.
Examples
--------
>>> frame = tc.frame.create([['Fred',39,16,'555-1234'],
... ['Susan',33,3,'555-0202'],
... ['Thurston',65,26,'555-4510'],
... ['Judy',44,14,'555-2183']],
... schema=[('name', str), ('age', int), ('tenure', int), ('phone', str)])
>>> frame.inspect()
[#] name age tenure phone
====================================
[0] Fred 39 16 555-1234
[1] Susan 33 3 555-0202
[2] Thurston 65 26 555-4510
[3] Judy 44 14 555-2183
>>> frame.drop_rows(lambda row: row.name[-1] == 'n') # drop people whose name ends in 'n'
>>> frame.inspect()
[#] name age tenure phone
================================
[0] Fred 39 16 555-1234
[1] Judy 44 14 555-2183
More information on a |UDF| can be found at :doc:`/ds_apir`.
"""
row = Row(self.schema)
def drop_rows_func(r):
row._set_data(r)
return not predicate(row)
self._python.rdd = self._python.rdd.filter(drop_rows_func)
Functions
def drop_rows(
self, predicate)
Erase any row in the current frame which qualifies.
Parameters:
| predicate | (UDF): | Function which evaluates a row to a boolean; rows that answer True are dropped from the frame. |
Examples:
>>> frame = tc.frame.create([['Fred',39,16,'555-1234'],
... ['Susan',33,3,'555-0202'],
... ['Thurston',65,26,'555-4510'],
... ['Judy',44,14,'555-2183']],
... schema=[('name', str), ('age', int), ('tenure', int), ('phone', str)])
>>> frame.inspect()
[#] name age tenure phone
====================================
[0] Fred 39 16 555-1234
[1] Susan 33 3 555-0202
[2] Thurston 65 26 555-4510
[3] Judy 44 14 555-2183
>>> frame.drop_rows(lambda row: row.name[-1] == 'n') # drop people whose name ends in 'n'
>>> frame.inspect()
[#] name age tenure phone
================================
[0] Fred 39 16 555-1234
[1] Judy 44 14 555-2183
More information on a |UDF| can be found at :doc:/ds_apir.
def drop_rows(self, predicate):
"""
Erase any row in the current frame which qualifies.
Parameters
----------
:param predicate: (UDF) Function which evaluates a row to a boolean; rows that answer True are dropped from
the frame.
Examples
--------
>>> frame = tc.frame.create([['Fred',39,16,'555-1234'],
... ['Susan',33,3,'555-0202'],
... ['Thurston',65,26,'555-4510'],
... ['Judy',44,14,'555-2183']],
... schema=[('name', str), ('age', int), ('tenure', int), ('phone', str)])
>>> frame.inspect()
[#] name age tenure phone
====================================
[0] Fred 39 16 555-1234
[1] Susan 33 3 555-0202
[2] Thurston 65 26 555-4510
[3] Judy 44 14 555-2183
>>> frame.drop_rows(lambda row: row.name[-1] == 'n') # drop people whose name ends in 'n'
>>> frame.inspect()
[#] name age tenure phone
================================
[0] Fred 39 16 555-1234
[1] Judy 44 14 555-2183
More information on a |UDF| can be found at :doc:`/ds_apir`.
"""
row = Row(self.schema)
def drop_rows_func(r):
row._set_data(r)
return not predicate(row)
self._python.rdd = self._python.rdd.filter(drop_rows_func)