/
relations.py
3602 lines (3192 loc) · 190 KB
/
relations.py
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from __future__ import annotations
import collections
import contextlib
import functools
import itertools
import operator
import re
from keyword import iskeyword
from typing import TYPE_CHECKING, Callable, Iterable, Literal, Mapping, Sequence
import toolz
from public import public
import ibis
import ibis.common.exceptions as com
import ibis.expr.datatypes as dt
import ibis.expr.operations as ops
import ibis.expr.schema as sch
from ibis import util
from ibis.expr.deferred import Deferred
from ibis.expr.types.core import Expr, _FixedTextJupyterMixin
if TYPE_CHECKING:
import pandas as pd
import ibis.selectors as s
import ibis.expr.types as ir
from ibis.common.typing import SupportsSchema
from ibis.selectors import IfAnyAll, Selector
from ibis.expr.types.groupby import GroupedTable
_ALIASES = (f"_ibis_view_{n:d}" for n in itertools.count())
def _ensure_expr(table, expr):
import ibis.expr.rules as rlz
from ibis.selectors import Selector
# This is different than self._ensure_expr, since we don't want to
# treat `str` or `int` values as column indices
if util.is_function(expr):
return expr(table)
elif isinstance(expr, Deferred):
return expr.resolve(table)
elif isinstance(expr, Selector):
return expr.expand(table)
else:
return rlz.any(expr).to_expr()
def _regular_join_method(
name: str,
how: Literal[
"inner",
"left",
"outer",
"right",
"semi",
"anti",
"any_inner",
"any_left",
],
):
def f( # noqa: D417
self: Table,
right: Table,
predicates: str
| Sequence[
str | tuple[str | ir.Column, str | ir.Column] | ir.BooleanValue
] = (),
*,
lname: str = "",
rname: str = "{name}_right",
) -> Table:
"""Perform a join between two tables.
Parameters
----------
right
Right table to join
predicates
Boolean or column names to join on
lname
A format string to use to rename overlapping columns in the left
table (e.g. ``"left_{name}"``).
rname
A format string to use to rename overlapping columns in the right
table (e.g. ``"right_{name}"``).
Returns
-------
Table
Joined table
"""
return self.join(right, predicates, how=how, lname=lname, rname=rname)
f.__name__ = name
return f
@public
class Table(Expr, _FixedTextJupyterMixin):
# Higher than numpy & dask objects
__array_priority__ = 20
__array_ufunc__ = None
def __array__(self, dtype=None):
return self.execute().__array__(dtype)
def as_table(self) -> Table:
"""Promote the expression to a table.
This method is a no-op for table expressions.
Returns
-------
Table
A table expression
Examples
--------
>>> t = ibis.table(dict(a="int"), name="t")
>>> s = t.as_table()
>>> t is s
True
"""
return self
def __contains__(self, name: str) -> bool:
"""Return whether `name` is a column in the table.
Parameters
----------
name
Possible column name
Returns
-------
bool
Whether `name` is a column in `self`
Examples
--------
>>> t = ibis.table(dict(a="string", b="float"), name="t")
>>> "a" in t
True
>>> "c" in t
False
"""
return name in self.schema()
def cast(self, schema: SupportsSchema) -> Table:
"""Cast the columns of a table.
!!! note "If you need to cast columns to a single type, use [selectors](https://ibis-project.org/blog/selectors/)."
Parameters
----------
schema
Mapping, schema or iterable of pairs to use for casting
Returns
-------
Table
Casted table
Examples
--------
>>> import ibis
>>> import ibis.selectors as s
>>> ibis.options.interactive = True
>>> t = ibis.examples.penguins.fetch()
>>> t.schema()
ibis.Schema {
species string
island string
bill_length_mm float64
bill_depth_mm float64
flipper_length_mm int64
body_mass_g int64
sex string
year int64
}
>>> cols = ["body_mass_g", "bill_length_mm"]
>>> t[cols].head()
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓
┃ body_mass_g ┃ bill_length_mm ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩
│ int64 │ float64 │
├─────────────┼────────────────┤
│ 3750 │ 39.1 │
│ 3800 │ 39.5 │
│ 3250 │ 40.3 │
│ NULL │ nan │
│ 3450 │ 36.7 │
└─────────────┴────────────────┘
Columns not present in the input schema will be passed through unchanged
>>> t.columns
['species', 'island', 'bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g', 'sex', 'year']
>>> expr = t.cast({"body_mass_g": "float64", "bill_length_mm": "int"})
>>> expr.select(*cols).head()
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓
┃ body_mass_g ┃ bill_length_mm ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩
│ float64 │ int64 │
├─────────────┼────────────────┤
│ 3750.0 │ 39 │
│ 3800.0 │ 40 │
│ 3250.0 │ 40 │
│ nan │ NULL │
│ 3450.0 │ 37 │
└─────────────┴────────────────┘
Columns that are in the input `schema` but not in the table raise an error
>>> t.cast({"foo": "string"})
Traceback (most recent call last):
...
ibis.common.exceptions.IbisError: Cast schema has fields that are not in the table: ['foo']
"""
schema = sch.schema(schema)
cols = []
columns = self.columns
if missing_fields := frozenset(schema.names).difference(columns):
raise com.IbisError(
f"Cast schema has fields that are not in the table: {sorted(missing_fields)}"
)
for col in columns:
if (new_type := schema.get(col)) is not None:
new_col = self[col].cast(new_type).name(col)
else:
new_col = col
cols.append(new_col)
return self.select(*cols)
def __rich_console__(self, console, options):
from rich.text import Text
from ibis.expr.types.pretty import to_rich_table
if not ibis.options.interactive:
return console.render(Text(self._repr()), options=options)
if console.is_jupyter:
# Rich infers a console width in jupyter notebooks, but since
# notebooks can use horizontal scroll bars we don't want to apply a
# limit here. Since rich requires an integer for max_width, we
# choose an arbitrarily large integer bound. Note that we need to
# handle this here rather than in `to_rich_table`, as this setting
# also needs to be forwarded to `console.render`.
options = options.update(max_width=1_000_000)
width = None
else:
width = options.max_width
table = to_rich_table(self, width)
return console.render(table, options=options)
def __getitem__(self, what):
"""Select items from a table expression.
This method implements square bracket syntax for table expressions,
including various forms of projection and filtering.
Parameters
----------
what
Selection object. This can be a variety of types including strings, ints, lists.
Returns
-------
Table | Column
The return type depends on the input. For a single string or int
input a column is returned, otherwise a table is returned.
Examples
--------
>>> import ibis
>>> import ibis.selectors as s
>>> from ibis import _
>>> ibis.options.interactive = True
>>> t = ibis.examples.penguins.fetch()
>>> t
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ … ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━┩
│ string │ string │ float64 │ float64 │ int64 │ … │
├─────────┼───────────┼────────────────┼───────────────┼───────────────────┼───┤
│ Adelie │ Torgersen │ 39.1 │ 18.7 │ 181 │ … │
│ Adelie │ Torgersen │ 39.5 │ 17.4 │ 186 │ … │
│ Adelie │ Torgersen │ 40.3 │ 18.0 │ 195 │ … │
│ Adelie │ Torgersen │ nan │ nan │ NULL │ … │
│ Adelie │ Torgersen │ 36.7 │ 19.3 │ 193 │ … │
│ Adelie │ Torgersen │ 39.3 │ 20.6 │ 190 │ … │
│ Adelie │ Torgersen │ 38.9 │ 17.8 │ 181 │ … │
│ Adelie │ Torgersen │ 39.2 │ 19.6 │ 195 │ … │
│ Adelie │ Torgersen │ 34.1 │ 18.1 │ 193 │ … │
│ Adelie │ Torgersen │ 42.0 │ 20.2 │ 190 │ … │
│ … │ … │ … │ … │ … │ … │
└─────────┴───────────┴────────────────┴───────────────┴───────────────────┴───┘
Return a column by name
>>> t["island"]
┏━━━━━━━━━━━┓
┃ island ┃
┡━━━━━━━━━━━┩
│ string │
├───────────┤
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ … │
└───────────┘
Return the second column, starting from index 0
>>> t.columns[1]
'island'
>>> t[1]
┏━━━━━━━━━━━┓
┃ island ┃
┡━━━━━━━━━━━┩
│ string │
├───────────┤
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ … │
└───────────┘
Extract a range of rows
>>> t[:2]
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ … ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━┩
│ string │ string │ float64 │ float64 │ int64 │ … │
├─────────┼───────────┼────────────────┼───────────────┼───────────────────┼───┤
│ Adelie │ Torgersen │ 39.1 │ 18.7 │ 181 │ … │
│ Adelie │ Torgersen │ 39.5 │ 17.4 │ 186 │ … │
└─────────┴───────────┴────────────────┴───────────────┴───────────────────┴───┘
>>> t[:5]
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ … ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━┩
│ string │ string │ float64 │ float64 │ int64 │ … │
├─────────┼───────────┼────────────────┼───────────────┼───────────────────┼───┤
│ Adelie │ Torgersen │ 39.1 │ 18.7 │ 181 │ … │
│ Adelie │ Torgersen │ 39.5 │ 17.4 │ 186 │ … │
│ Adelie │ Torgersen │ 40.3 │ 18.0 │ 195 │ … │
│ Adelie │ Torgersen │ nan │ nan │ NULL │ … │
│ Adelie │ Torgersen │ 36.7 │ 19.3 │ 193 │ … │
└─────────┴───────────┴────────────────┴───────────────┴───────────────────┴───┘
>>> t[2:5]
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ … ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━┩
│ string │ string │ float64 │ float64 │ int64 │ … │
├─────────┼───────────┼────────────────┼───────────────┼───────────────────┼───┤
│ Adelie │ Torgersen │ 40.3 │ 18.0 │ 195 │ … │
│ Adelie │ Torgersen │ nan │ nan │ NULL │ … │
│ Adelie │ Torgersen │ 36.7 │ 19.3 │ 193 │ … │
└─────────┴───────────┴────────────────┴───────────────┴───────────────────┴───┘
Select columns
>>> t[["island", "bill_length_mm"]].head()
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓
┃ island ┃ bill_length_mm ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩
│ string │ float64 │
├───────────┼────────────────┤
│ Torgersen │ 39.1 │
│ Torgersen │ 39.5 │
│ Torgersen │ 40.3 │
│ Torgersen │ nan │
│ Torgersen │ 36.7 │
└───────────┴────────────────┘
>>> t["island", "bill_length_mm"].head()
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓
┃ island ┃ bill_length_mm ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩
│ string │ float64 │
├───────────┼────────────────┤
│ Torgersen │ 39.1 │
│ Torgersen │ 39.5 │
│ Torgersen │ 40.3 │
│ Torgersen │ nan │
│ Torgersen │ 36.7 │
└───────────┴────────────────┘
>>> t[_.island, _.bill_length_mm].head()
┏━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓
┃ island ┃ bill_length_mm ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩
│ string │ float64 │
├───────────┼────────────────┤
│ Torgersen │ 39.1 │
│ Torgersen │ 39.5 │
│ Torgersen │ 40.3 │
│ Torgersen │ nan │
│ Torgersen │ 36.7 │
└───────────┴────────────────┘
Filtering
>>> t[t.island.lower() != "torgersen"].head()
┏━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ … ┃
┡━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━┩
│ string │ string │ float64 │ float64 │ int64 │ … │
├─────────┼────────┼────────────────┼───────────────┼───────────────────┼───┤
│ Adelie │ Biscoe │ 37.8 │ 18.3 │ 174 │ … │
│ Adelie │ Biscoe │ 37.7 │ 18.7 │ 180 │ … │
│ Adelie │ Biscoe │ 35.9 │ 19.2 │ 189 │ … │
│ Adelie │ Biscoe │ 38.2 │ 18.1 │ 185 │ … │
│ Adelie │ Biscoe │ 38.8 │ 17.2 │ 180 │ … │
└─────────┴────────┴────────────────┴───────────────┴───────────────────┴───┘
Selectors
>>> t[~s.numeric() | (s.numeric() & ~s.c("year"))].head()
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ … ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━┩
│ string │ string │ float64 │ float64 │ int64 │ … │
├─────────┼───────────┼────────────────┼───────────────┼───────────────────┼───┤
│ Adelie │ Torgersen │ 39.1 │ 18.7 │ 181 │ … │
│ Adelie │ Torgersen │ 39.5 │ 17.4 │ 186 │ … │
│ Adelie │ Torgersen │ 40.3 │ 18.0 │ 195 │ … │
│ Adelie │ Torgersen │ nan │ nan │ NULL │ … │
│ Adelie │ Torgersen │ 36.7 │ 19.3 │ 193 │ … │
└─────────┴───────────┴────────────────┴───────────────┴───────────────────┴───┘
>>> t[s.r["bill_length_mm":"body_mass_g"]].head()
┏━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ body_mass_g ┃
┡━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ float64 │ float64 │ int64 │ int64 │
├────────────────┼───────────────┼───────────────────┼─────────────┤
│ 39.1 │ 18.7 │ 181 │ 3750 │
│ 39.5 │ 17.4 │ 186 │ 3800 │
│ 40.3 │ 18.0 │ 195 │ 3250 │
│ nan │ nan │ NULL │ NULL │
│ 36.7 │ 19.3 │ 193 │ 3450 │
└────────────────┴───────────────┴───────────────────┴─────────────┘
"""
from ibis.expr.types.generic import Column
from ibis.expr.types.logical import BooleanValue
if isinstance(what, (str, int)):
return ops.TableColumn(self, what).to_expr()
if isinstance(what, slice):
step = what.step
if step is not None and step != 1:
raise ValueError('Slice step can only be 1')
start = what.start or 0
stop = what.stop
if stop is None or stop < 0:
raise ValueError('End index must be a positive number')
if start < 0:
raise ValueError('Start index must be a positive number')
return self.limit(stop - start, offset=start)
what = bind_expr(self, what)
if isinstance(what, (list, tuple, Table)):
# Projection case
return self.select(what)
elif isinstance(what, BooleanValue):
# Boolean predicate
return self.filter([what])
elif isinstance(what, Column):
# Projection convenience
return self.select(what)
else:
raise NotImplementedError(
'Selection rows or columns with {} objects is not '
'supported'.format(type(what).__name__)
)
def __len__(self):
raise com.ExpressionError('Use .count() instead')
def __getattr__(self, key: str) -> ir.Column:
"""Return the column name of a table.
Parameters
----------
key
Column name
Returns
-------
Column
Column expression with name `key`
Examples
--------
>>> import ibis
>>> ibis.options.interactive = True
>>> t = ibis.examples.penguins.fetch()
>>> t.island
┏━━━━━━━━━━━┓
┃ island ┃
┡━━━━━━━━━━━┩
│ string │
├───────────┤
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ Torgersen │
│ … │
└───────────┘
"""
with contextlib.suppress(com.IbisTypeError):
return ops.TableColumn(self, key).to_expr()
# A mapping of common attribute typos, mapping them to the proper name
common_typos = {
"sort": "order_by",
"sort_by": "order_by",
"sortby": "order_by",
"orderby": "order_by",
"groupby": "group_by",
}
if key in common_typos:
hint = common_typos[key]
raise AttributeError(
f"{type(self).__name__} object has no attribute {key!r}, did you mean {hint!r}"
)
raise AttributeError(f"'Table' object has no attribute {key!r}")
def __dir__(self) -> list[str]:
out = set(dir(type(self)))
out.update(c for c in self.columns if c.isidentifier() and not iskeyword(c))
return sorted(out)
def _ipython_key_completions_(self) -> list[str]:
return self.columns
def _ensure_expr(self, expr):
import numpy as np
from ibis.selectors import Selector
if isinstance(expr, str):
# treat strings as column names
return self[expr]
elif isinstance(expr, (int, np.integer)):
# treat Python integers as a column index
return self[self.schema().name_at_position(expr)]
elif isinstance(expr, Deferred):
# resolve deferred expressions
return expr.resolve(self)
elif isinstance(expr, Selector):
return expr.expand(self)
elif callable(expr):
return expr(self)
else:
return expr
@property
def columns(self) -> list[str]:
"""The list of columns in this table.
Examples
--------
>>> import ibis
>>> ibis.options.interactive = True
>>> t = ibis.examples.penguins.fetch()
>>> t.columns
['species',
'island',
'bill_length_mm',
'bill_depth_mm',
'flipper_length_mm',
'body_mass_g',
'sex',
'year']
"""
return list(self.schema().names)
def schema(self) -> sch.Schema:
"""Return the schema for this table.
Returns
-------
Schema
The table's schema.
Examples
--------
>>> import ibis
>>> ibis.options.interactive = True
>>> t = ibis.examples.penguins.fetch()
>>> t.schema()
ibis.Schema {
species string
island string
bill_length_mm float64
bill_depth_mm float64
flipper_length_mm int64
body_mass_g int64
sex string
year int64
}
"""
return self.op().schema
def group_by(
self,
by: str | ir.Value | Iterable[str] | Iterable[ir.Value] | None = None,
**key_exprs: str | ir.Value | Iterable[str] | Iterable[ir.Value],
) -> GroupedTable:
"""Create a grouped table expression.
Parameters
----------
by
Grouping expressions
key_exprs
Named grouping expressions
Returns
-------
GroupedTable
A grouped table expression
Examples
--------
>>> import ibis
>>> from ibis import _
>>> ibis.options.interactive = True
>>> t = ibis.memtable({"fruit": ["apple", "apple", "banana", "orange"], "price": [0.5, 0.5, 0.25, 0.33]})
>>> t
┏━━━━━━━━┳━━━━━━━━━┓
┃ fruit ┃ price ┃
┡━━━━━━━━╇━━━━━━━━━┩
│ string │ float64 │
├────────┼─────────┤
│ apple │ 0.50 │
│ apple │ 0.50 │
│ banana │ 0.25 │
│ orange │ 0.33 │
└────────┴─────────┘
>>> t.group_by("fruit").agg(total_cost=_.price.sum(), avg_cost=_.price.mean())
┏━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━┓
┃ fruit ┃ total_cost ┃ avg_cost ┃
┡━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━┩
│ string │ float64 │ float64 │
├────────┼────────────┼──────────┤
│ apple │ 1.00 │ 0.50 │
│ banana │ 0.25 │ 0.25 │
│ orange │ 0.33 │ 0.33 │
└────────┴────────────┴──────────┘
"""
from ibis.expr.types.groupby import GroupedTable
return GroupedTable(self, by, **key_exprs)
def rowid(self) -> ir.IntegerValue:
"""A unique integer per row.
!!! note "This operation is only valid on physical tables"
Any further meaning behind this expression is backend dependent.
Generally this corresponds to some index into the database storage
(for example, sqlite or duckdb's `rowid`).
For a monotonically increasing row number, see `ibis.row_number`.
Returns
-------
IntegerColumn
An integer column
"""
if not isinstance(self.op(), ops.PhysicalTable):
raise com.IbisTypeError(
"rowid() is only valid for physical tables, not for generic "
"table expressions"
)
return ops.RowID(self).to_expr()
def view(self) -> Table:
"""Create a new table expression distinct from the current one.
Use this API for any self-referencing operations like a self-join.
Returns
-------
Table
Table expression
"""
return ops.SelfReference(self).to_expr()
def difference(self, *tables: Table, distinct: bool = True) -> Table:
"""Compute the set difference of multiple table expressions.
The input tables must have identical schemas.
Parameters
----------
tables
One or more table expressions
distinct
Only diff distinct rows not occurring in the calling table
See Also
--------
[`ibis.difference`][ibis.difference]
Returns
-------
Table
The rows present in `self` that are not present in `tables`.
Examples
--------
>>> import ibis
>>> ibis.options.interactive = True
>>> t1 = ibis.memtable({"a": [1, 2]})
>>> t1
┏━━━━━━━┓
┃ a ┃
┡━━━━━━━┩
│ int64 │
├───────┤
│ 1 │
│ 2 │
└───────┘
>>> t2 = ibis.memtable({"a": [2, 3]})
>>> t2
┏━━━━━━━┓
┃ a ┃
┡━━━━━━━┩
│ int64 │
├───────┤
│ 2 │
│ 3 │
└───────┘
>>> t1.difference(t2)
┏━━━━━━━┓
┃ a ┃
┡━━━━━━━┩
│ int64 │
├───────┤
│ 1 │
└───────┘
Passing no arguments to `difference` returns the table expression
This can be useful when you have a sequence of tables to process, and
you don't know the length prior to running your program (for example, user input).
>>> t1
┏━━━━━━━┓
┃ a ┃
┡━━━━━━━┩
│ int64 │
├───────┤
│ 1 │
│ 2 │
└───────┘
>>> t1.difference()
┏━━━━━━━┓
┃ a ┃
┡━━━━━━━┩
│ int64 │
├───────┤
│ 1 │
│ 2 │
└───────┘
>>> t1.difference().equals(t1)
True
"""
t = functools.reduce(
functools.partial(ops.Difference, distinct=distinct), tables, self.op()
).to_expr()
if t.equals(self):
return t
return t.select(self.columns)
def aggregate(
self,
metrics: Sequence[ir.Scalar] | None = None,
by: Sequence[ir.Value] | None = None,
having: Sequence[ir.BooleanValue] | None = None,
**kwargs: ir.Value,
) -> Table:
"""Aggregate a table with a given set of reductions grouping by `by`.
Parameters
----------
metrics
Aggregate expressions. These can be any scalar-producing
expression, including aggregation functions like `sum` or literal
values like `ibis.literal(1)`.
by
Grouping expressions.
having
Post-aggregation filters. The shape requirements are the same
`metrics`, but the output type for `having` is `boolean`.
!!! warning "Expressions like `x is None` return `bool` and **will not** generate a SQL comparison to `NULL`"
kwargs
Named aggregate expressions
Returns
-------
Table
An aggregate table expression
Examples
--------
>>> import ibis
>>> from ibis import _
>>> ibis.options.interactive = True
>>> t = ibis.memtable({"fruit": ["apple", "apple", "banana", "orange"], "price": [0.5, 0.5, 0.25, 0.33]})
>>> t
┏━━━━━━━━┳━━━━━━━━━┓
┃ fruit ┃ price ┃
┡━━━━━━━━╇━━━━━━━━━┩
│ string │ float64 │
├────────┼─────────┤
│ apple │ 0.50 │
│ apple │ 0.50 │
│ banana │ 0.25 │
│ orange │ 0.33 │
└────────┴─────────┘
>>> t.aggregate(by=["fruit"], total_cost=_.price.sum(), avg_cost=_.price.mean(), having=_.price.sum() < 0.5)
┏━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━┓
┃ fruit ┃ total_cost ┃ avg_cost ┃
┡━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━┩
│ string │ float64 │ float64 │
├────────┼────────────┼──────────┤
│ banana │ 0.25 │ 0.25 │
│ orange │ 0.33 │ 0.33 │
└────────┴────────────┴──────────┘
"""
import ibis.expr.analysis as an
metrics = itertools.chain(
itertools.chain.from_iterable(
(
(_ensure_expr(self, m) for m in metric)
if isinstance(metric, (list, tuple))
else util.promote_list(_ensure_expr(self, metric))
)
for metric in util.promote_list(metrics)
),
(
e.name(name)
for name, expr in kwargs.items()
for e in util.promote_list(_ensure_expr(self, expr))
),
)
agg = ops.Aggregation(
self,
metrics=list(metrics),
by=bind_expr(self, util.promote_list(by)),
having=bind_expr(self, util.promote_list(having)),
)
agg = an.simplify_aggregation(agg)
return agg.to_expr()
agg = aggregate
def distinct(
self,
*,
on: str | Iterable[str] | s.Selector | None = None,
keep: Literal["first", "last"] | None = "first",
) -> Table:
"""Return a Table with duplicate rows removed.
Similar to `pandas.DataFrame.drop_duplicates()`.
!!! note "Some backends do not support `keep='last'`"
Parameters
----------
on
Only consider certain columns for identifying duplicates.
By default deduplicate all of the columns.
keep
Determines which duplicates to keep.
- `"first"`: Drop duplicates except for the first occurrence.
- `"last"`: Drop duplicates except for the last occurrence.
- `None`: Drop all duplicates
Examples
--------
>>> import ibis
>>> import ibis.examples as ex
>>> import ibis.selectors as s
>>> ibis.options.interactive = True
>>> t = ex.penguins.fetch()
>>> t
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_mm ┃ flipper_length_mm ┃ … ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━┩
│ string │ string │ float64 │ float64 │ int64 │ … │
├─────────┼───────────┼────────────────┼───────────────┼───────────────────┼───┤
│ Adelie │ Torgersen │ 39.1 │ 18.7 │ 181 │ … │
│ Adelie │ Torgersen │ 39.5 │ 17.4 │ 186 │ … │
│ Adelie │ Torgersen │ 40.3 │ 18.0 │ 195 │ … │
│ Adelie │ Torgersen │ nan │ nan │ NULL │ … │
│ Adelie │ Torgersen │ 36.7 │ 19.3 │ 193 │ … │
│ Adelie │ Torgersen │ 39.3 │ 20.6 │ 190 │ … │
│ Adelie │ Torgersen │ 38.9 │ 17.8 │ 181 │ … │
│ Adelie │ Torgersen │ 39.2 │ 19.6 │ 195 │ … │
│ Adelie │ Torgersen │ 34.1 │ 18.1 │ 193 │ … │
│ Adelie │ Torgersen │ 42.0 │ 20.2 │ 190 │ … │
│ … │ … │ … │ … │ … │ … │
└─────────┴───────────┴────────────────┴───────────────┴───────────────────┴───┘
Compute the distinct rows of a subset of columns
>>> t[["species", "island"]].distinct()
┏━━━━━━━━━━━┳━━━━━━━━━━━┓
┃ species ┃ island ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━┩
│ string │ string │
├───────────┼───────────┤
│ Adelie │ Torgersen │
│ Adelie │ Biscoe │
│ Adelie │ Dream │
│ Gentoo │ Biscoe │
│ Chinstrap │ Dream │
└───────────┴───────────┘
Drop all duplicate rows except the first
>>> t.distinct(on=["species", "island"], keep="first")
┏━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_… ┃ flipper_length_mm ┃ ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━┩
│ string │ string │ float64 │ float64 │ int64 │ │
├───────────┼───────────┼────────────────┼──────────────┼───────────────────┼──┤
│ Adelie │ Torgersen │ 39.1 │ 18.7 │ 181 │ │
│ Adelie │ Biscoe │ 37.8 │ 18.3 │ 174 │ │
│ Adelie │ Dream │ 39.5 │ 16.7 │ 178 │ │
│ Gentoo │ Biscoe │ 46.1 │ 13.2 │ 211 │ │
│ Chinstrap │ Dream │ 46.5 │ 17.9 │ 192 │ │
└───────────┴───────────┴────────────────┴──────────────┴───────────────────┴──┘
Drop all duplicate rows except the last
>>> t.distinct(on=["species", "island"], keep="last")
┏━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━┓
┃ species ┃ island ┃ bill_length_mm ┃ bill_depth_… ┃ flipper_length_mm ┃ ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━┩
│ string │ string │ float64 │ float64 │ int64 │ │
├───────────┼───────────┼────────────────┼──────────────┼───────────────────┼──┤
│ Adelie │ Torgersen │ 43.1 │ 19.2 │ 197 │ │
│ Adelie │ Biscoe │ 42.7 │ 18.3 │ 196 │ │
│ Adelie │ Dream │ 41.5 │ 18.5 │ 201 │ │
│ Gentoo │ Biscoe │ 49.9 │ 16.1 │ 213 │ │
│ Chinstrap │ Dream │ 50.2 │ 18.7 │ 198 │ │
└───────────┴───────────┴────────────────┴──────────────┴───────────────────┴──┘
Drop all duplicated rows
>>> expr = t.distinct(on=["species", "island", "year", "bill_length_mm"], keep=None)
>>> expr.count()
273