From 149dd167f9daa444a3558c2be4dac84aaebed558 Mon Sep 17 00:00:00 2001 From: Brock Mendel Date: Tue, 23 Jan 2018 08:41:19 -0800 Subject: [PATCH] remove unused convert_sql_column --- pandas/_libs/src/inference.pyx | 4 -- pandas/tests/dtypes/test_io.py | 73 ---------------------------------- 2 files changed, 77 deletions(-) delete mode 100644 pandas/tests/dtypes/test_io.py diff --git a/pandas/_libs/src/inference.pyx b/pandas/_libs/src/inference.pyx index e15f276b39bf8..39656239aae76 100644 --- a/pandas/_libs/src/inference.pyx +++ b/pandas/_libs/src/inference.pyx @@ -1390,10 +1390,6 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0, return objects -def convert_sql_column(x): - return maybe_convert_objects(x, try_float=1) - - def sanitize_objects(ndarray[object] values, set na_values, convert_empty=True): cdef: diff --git a/pandas/tests/dtypes/test_io.py b/pandas/tests/dtypes/test_io.py deleted file mode 100644 index 06b61371c9a0b..0000000000000 --- a/pandas/tests/dtypes/test_io.py +++ /dev/null @@ -1,73 +0,0 @@ -# -*- coding: utf-8 -*- - -import numpy as np -import pandas._libs.lib as lib -import pandas.util.testing as tm - -from pandas.compat import long, u - - -class TestParseSQL(object): - - def test_convert_sql_column_floats(self): - arr = np.array([1.5, None, 3, 4.2], dtype=object) - result = lib.convert_sql_column(arr) - expected = np.array([1.5, np.nan, 3, 4.2], dtype='f8') - tm.assert_numpy_array_equal(result, expected) - - def test_convert_sql_column_strings(self): - arr = np.array(['1.5', None, '3', '4.2'], dtype=object) - result = lib.convert_sql_column(arr) - expected = np.array(['1.5', np.nan, '3', '4.2'], dtype=object) - tm.assert_numpy_array_equal(result, expected) - - def test_convert_sql_column_unicode(self): - arr = np.array([u('1.5'), None, u('3'), u('4.2')], - dtype=object) - result = lib.convert_sql_column(arr) - expected = np.array([u('1.5'), np.nan, u('3'), u('4.2')], - dtype=object) - tm.assert_numpy_array_equal(result, expected) - - def test_convert_sql_column_ints(self): - arr = np.array([1, 2, 3, 4], dtype='O') - arr2 = np.array([1, 2, 3, 4], dtype='i4').astype('O') - result = lib.convert_sql_column(arr) - result2 = lib.convert_sql_column(arr2) - expected = np.array([1, 2, 3, 4], dtype='i8') - tm.assert_numpy_array_equal(result, expected) - tm.assert_numpy_array_equal(result2, expected) - - arr = np.array([1, 2, 3, None, 4], dtype='O') - result = lib.convert_sql_column(arr) - expected = np.array([1, 2, 3, np.nan, 4], dtype='f8') - tm.assert_numpy_array_equal(result, expected) - - def test_convert_sql_column_longs(self): - arr = np.array([long(1), long(2), long(3), long(4)], dtype='O') - result = lib.convert_sql_column(arr) - expected = np.array([1, 2, 3, 4], dtype='i8') - tm.assert_numpy_array_equal(result, expected) - - arr = np.array([long(1), long(2), long(3), None, long(4)], dtype='O') - result = lib.convert_sql_column(arr) - expected = np.array([1, 2, 3, np.nan, 4], dtype='f8') - tm.assert_numpy_array_equal(result, expected) - - def test_convert_sql_column_bools(self): - arr = np.array([True, False, True, False], dtype='O') - result = lib.convert_sql_column(arr) - expected = np.array([True, False, True, False], dtype=bool) - tm.assert_numpy_array_equal(result, expected) - - arr = np.array([True, False, None, False], dtype='O') - result = lib.convert_sql_column(arr) - expected = np.array([True, False, np.nan, False], dtype=object) - tm.assert_numpy_array_equal(result, expected) - - def test_convert_sql_column_decimals(self): - from decimal import Decimal - arr = np.array([Decimal('1.5'), None, Decimal('3'), Decimal('4.2')]) - result = lib.convert_sql_column(arr) - expected = np.array([1.5, np.nan, 3, 4.2], dtype='f8') - tm.assert_numpy_array_equal(result, expected)