def test_can_select_columns():
df = tibble(x=1, y=2)
out = df >> rename_with(str.upper) >> names()
assert_iterable_equal(out, ["X", "Y"])
out = df >> rename_with(str.upper, 0) >> names()
assert_iterable_equal(out, ["X", "y"])
out = df >> rename_with(str.upper, f.x) >> names()
assert_iterable_equal(out, ["X", "y"])
def test_0_vars(df):
gdata = group_data(group_by(iris))
assert names(gdata) == ["_rows"]
out = gdata
assert_iterable_equal(out._rows[0], range(nrow(iris)))
gdata = group_data(group_by(iris, **{}))
assert names(gdata) == ["_rows"]
out = gdata
assert_iterable_equal(out._rows[0], range(nrow(iris)))
def test_can_be_before_group_by():
df = tibble(id=c(1, 1, 2, 2, 2, 3, 3, 4, 4, 5),
year=c(2013, 2013, 2012, 2013, 2013, 2013, 2012, 2012, 2013,
2013),
var1=rnorm(10))
dfagg = df >> group_by(f.id, f.year) >> select(
f.id, f.year, f.var1) >> summarise(var1=mean(f.var1))
assert_iterable_equal(names(dfagg), ["id", "year", "var1"])
def test_passes_args_kwargs_along():
df = tibble(x=1, y=2)
out = df >> rename_with(str.replace, f.x, "x", "X") >> names()
assert_iterable_equal(out, ["X", "y"])
def test_can_rename_with_duplicate_columns():
df = tibble(tibble(x=1), x=2, y=1, _name_repair="minimal")
out = df >> rename(x2=1) >> names()
assert_iterable_equal(out, ["x", "x2", "y"])
def test_slice_handles_empty_df():
df = tibble(x=[])
res = df >> slice(f[:3])
assert nrow(res) == 0
assert names(res) == ["x"]