def test_where_use_if(self):
expr = ibis.where(self.table.f > 0, self.table.e, self.table.a)
assert isinstance(expr, ir.FloatValue)
result = self._translate(expr)
expected = "if(`f` > 0, `e`, `a`)"
assert result == expected
def test_where_use_if(table):
expr = ibis.where(table.f > 0, table.e, table.a)
assert isinstance(expr, ir.FloatingValue)
result = translate(expr)
expected = "if(`f` > 0, `e`, `a`)"
assert result == expected
def test_where_use_if(self):
expr = ibis.where(self.table.f > 0, self.table.e, self.table.a)
assert isinstance(expr, ir.FloatValue)
result = self._translate(expr)
expected = "if(`f` > 0, `e`, `a`)"
assert result == expected
def test_where_use_if(con, alltypes, translate):
expr = ibis.where(alltypes.float_col > 0, alltypes.int_col,
alltypes.bigint_col)
result = translate(expr)
expected = "if(`float_col` > 0, `int_col`, `bigint_col`)"
assert result == expected
con.execute(expr)
def test_where_long(batting, batting_df):
col_expr = batting['AB']
result = ibis.where(col_expr > col_expr.mean(), col_expr, 0.0).execute()
ser = batting_df['AB']
expected = ser.where(ser > ser.mean(), other=0.0)
tm.assert_series_equal(result, expected)
def test_where_series(t, df):
col_expr = t['plain_int64']
result = ibis.where(col_expr > col_expr.mean(), col_expr, 0.0).execute()
ser = df['plain_int64']
expected = ser.where(ser > ser.mean(), other=0.0)
tm.assert_series_equal(result, expected)
def test_where_long(batting, batting_df):
col_expr = batting['AB']
result = ibis.where(col_expr > col_expr.mean(), col_expr, 0.0).execute()
ser = batting_df['AB']
expected = ser.where(ser > ser.mean(), other=0.0)
tm.assert_series_equal(result, expected)
def test_where_series(t, df):
col_expr = t['plain_int64']
result = ibis.where(col_expr > col_expr.mean(), col_expr, 0.0).execute()
ser = df['plain_int64']
expected = ser.where(ser > ser.mean(), other=0.0)
tm.assert_series_equal(result, expected)
def test_where_use_if(con, alltypes, translate):
expr = ibis.where(
alltypes.float_col > 0, alltypes.int_col, alltypes.bigint_col
)
result = translate(expr)
expected = "if(`float_col` > 0, `int_col`, `bigint_col`)"
assert result == expected
con.execute(expr)
def test_where_column(backend, alltypes, df):
expr = (
ibis.where(alltypes["int_col"] == 0, 42, -1)
.cast("int64")
.name("where_col")
)
result = expr.execute()
expected = pd.Series(
np.where(df.int_col == 0, 42, -1),
name="where_col",
dtype="int64",
)
backend.assert_series_equal(result, expected)
def test_where_select(backend, alltypes, df):
table = alltypes
table = table.select(
[
"int_col",
(
ibis.where(table["int_col"] == 0, 42, -1)
.cast("int64")
.name("where_col")
),
]
)
result = table.execute()
expected = df.loc[:, ["int_col"]].copy()
expected['where_col'] = -1
expected.loc[expected['int_col'] == 0, 'where_col'] = 42
backend.assert_frame_equal(result, expected)
def test_where_scalar(t, df, cond, expected_func):
expr = ibis.where(cond, t['plain_int64'], 3.0)
result = expr.execute()
expected = expected_func(df)
tm.assert_series_equal(result, expected)
def test_where_operator(alltypes):
t = alltypes.sort_by('index').limit(10)
expr = ibis.where(t.index > 4, 1, 0)
counts = expr.execute().value_counts()
assert counts[0] == 5
assert counts[1] == 5
def test_where_operator(alltypes):
t = alltypes.sort_by('index').limit(10)
expr = ibis.where(t.index > 4, 1, 0)
counts = expr.execute().value_counts()
assert counts[0] == 5
assert counts[1] == 5
def test_where_scalar(t, df, cond, expected_func):
expr = ibis.where(cond, t['plain_int64'], 3.0)
result = expr.execute()
expected = expected_func(df)
tm.assert_series_equal(result, expected)
