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functions.py
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
"""User functions for operating on :py:class:`~datafusion.expr.Expr`."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any
import pyarrow as pa
from datafusion._internal import functions as f
from datafusion.common import NullTreatment
from datafusion.expr import (
CaseBuilder,
Expr,
SortExpr,
SortKey,
WindowFrame,
expr_list_to_raw_expr_list,
sort_list_to_raw_sort_list,
sort_or_default,
)
try:
from warnings import deprecated # Python 3.13+
except ImportError:
from typing_extensions import deprecated # Python 3.12
if TYPE_CHECKING:
from datafusion.context import SessionContext
__all__ = [
"abs",
"acos",
"acosh",
"alias",
"approx_distinct",
"approx_median",
"approx_percentile_cont",
"approx_percentile_cont_with_weight",
"array",
"array_agg",
"array_append",
"array_cat",
"array_concat",
"array_dims",
"array_distinct",
"array_element",
"array_empty",
"array_except",
"array_extract",
"array_has",
"array_has_all",
"array_has_any",
"array_indexof",
"array_intersect",
"array_join",
"array_length",
"array_ndims",
"array_pop_back",
"array_pop_front",
"array_position",
"array_positions",
"array_prepend",
"array_push_back",
"array_push_front",
"array_remove",
"array_remove_all",
"array_remove_n",
"array_repeat",
"array_replace",
"array_replace_all",
"array_replace_n",
"array_resize",
"array_slice",
"array_sort",
"array_to_string",
"array_union",
"arrow_cast",
"arrow_typeof",
"ascii",
"asin",
"asinh",
"atan",
"atan2",
"atanh",
"avg",
"bit_and",
"bit_length",
"bit_or",
"bit_xor",
"bool_and",
"bool_or",
"btrim",
"cardinality",
"case",
"cbrt",
"ceil",
"char_length",
"character_length",
"chr",
"coalesce",
"col",
"concat",
"concat_ws",
"corr",
"cos",
"cosh",
"cot",
"count",
"count_star",
"covar",
"covar_pop",
"covar_samp",
"cume_dist",
"current_date",
"current_time",
"date_bin",
"date_part",
"date_trunc",
"datepart",
"datetrunc",
"decode",
"degrees",
"dense_rank",
"digest",
"empty",
"encode",
"ends_with",
"exp",
"extract",
"factorial",
"find_in_set",
"first_value",
"flatten",
"floor",
"from_unixtime",
"gcd",
"in_list",
"initcap",
"isnan",
"iszero",
"lag",
"last_value",
"lcm",
"lead",
"left",
"length",
"levenshtein",
"list_append",
"list_cat",
"list_concat",
"list_dims",
"list_distinct",
"list_element",
"list_except",
"list_extract",
"list_indexof",
"list_intersect",
"list_join",
"list_length",
"list_ndims",
"list_position",
"list_positions",
"list_prepend",
"list_push_back",
"list_push_front",
"list_remove",
"list_remove_all",
"list_remove_n",
"list_repeat",
"list_replace",
"list_replace_all",
"list_replace_n",
"list_resize",
"list_slice",
"list_sort",
"list_to_string",
"list_union",
"ln",
"log",
"log2",
"log10",
"lower",
"lpad",
"ltrim",
"make_array",
"make_date",
"make_list",
"max",
"md5",
"mean",
"median",
"min",
"named_struct",
"nanvl",
"now",
"nth_value",
"ntile",
"nullif",
"nvl",
"octet_length",
"order_by",
"overlay",
"percent_rank",
"pi",
"pow",
"power",
"radians",
"random",
"range",
"rank",
"regexp_count",
"regexp_instr",
"regexp_like",
"regexp_match",
"regexp_replace",
"regr_avgx",
"regr_avgy",
"regr_count",
"regr_intercept",
"regr_r2",
"regr_slope",
"regr_sxx",
"regr_sxy",
"regr_syy",
"repeat",
"replace",
"reverse",
"right",
"round",
"row_number",
"rpad",
"rtrim",
"sha224",
"sha256",
"sha384",
"sha512",
"signum",
"sin",
"sinh",
"split_part",
"sqrt",
"starts_with",
"stddev",
"stddev_pop",
"stddev_samp",
"string_agg",
"strpos",
"struct",
"substr",
"substr_index",
"substring",
"sum",
"tan",
"tanh",
"to_char",
"to_date",
"to_hex",
"to_local_time",
"to_time",
"to_timestamp",
"to_timestamp_micros",
"to_timestamp_millis",
"to_timestamp_nanos",
"to_timestamp_seconds",
"to_unixtime",
"today",
"translate",
"trim",
"trunc",
"upper",
"uuid",
"var",
"var_pop",
"var_samp",
"var_sample",
"when",
# Window Functions
"window",
]
def isnan(expr: Expr) -> Expr:
"""Returns true if a given number is +NaN or -NaN otherwise returns false.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1.0, np.nan]})
>>> result = df.select(dfn.functions.isnan(dfn.col("a")).alias("isnan"))
>>> result.collect_column("isnan")[1].as_py()
True
"""
return Expr(f.isnan(expr.expr))
def nullif(expr1: Expr, expr2: Expr) -> Expr:
"""Returns NULL if expr1 equals expr2; otherwise it returns expr1.
This can be used to perform the inverse operation of the COALESCE expression.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2], "b": [1, 3]})
>>> result = df.select(
... dfn.functions.nullif(dfn.col("a"), dfn.col("b")).alias("nullif"))
>>> result.collect_column("nullif").to_pylist()
[None, 2]
"""
return Expr(f.nullif(expr1.expr, expr2.expr))
def encode(expr: Expr, encoding: Expr) -> Expr:
"""Encode the ``input``, using the ``encoding``. encoding can be base64 or hex.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello"]})
>>> result = df.select(
... dfn.functions.encode(dfn.col("a"), dfn.lit("base64")).alias("enc"))
>>> result.collect_column("enc")[0].as_py()
'aGVsbG8'
"""
return Expr(f.encode(expr.expr, encoding.expr))
def decode(expr: Expr, encoding: Expr) -> Expr:
"""Decode the ``input``, using the ``encoding``. encoding can be base64 or hex.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["aGVsbG8="]})
>>> result = df.select(
... dfn.functions.decode(dfn.col("a"), dfn.lit("base64")).alias("dec"))
>>> result.collect_column("dec")[0].as_py()
b'hello'
"""
return Expr(f.decode(expr.expr, encoding.expr))
def array_to_string(expr: Expr, delimiter: Expr) -> Expr:
"""Converts each element to its text representation.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
>>> result = df.select(
... dfn.functions.array_to_string(dfn.col("a"), dfn.lit(",")).alias("s"))
>>> result.collect_column("s")[0].as_py()
'1,2,3'
"""
return Expr(f.array_to_string(expr.expr, delimiter.expr.cast(pa.string())))
def array_join(expr: Expr, delimiter: Expr) -> Expr:
"""Converts each element to its text representation.
See Also:
This is an alias for :py:func:`array_to_string`.
"""
return array_to_string(expr, delimiter)
def list_to_string(expr: Expr, delimiter: Expr) -> Expr:
"""Converts each element to its text representation.
See Also:
This is an alias for :py:func:`array_to_string`.
"""
return array_to_string(expr, delimiter)
def list_join(expr: Expr, delimiter: Expr) -> Expr:
"""Converts each element to its text representation.
See Also:
This is an alias for :py:func:`array_to_string`.
"""
return array_to_string(expr, delimiter)
def in_list(arg: Expr, values: list[Expr], negated: bool = False) -> Expr:
"""Returns whether the argument is contained within the list ``values``.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, 3]})
>>> result = df.select(
... dfn.functions.in_list(
... dfn.col("a"), [dfn.lit(1), dfn.lit(3)]
... ).alias("in")
... )
>>> result.collect_column("in").to_pylist()
[True, False, True]
>>> result = df.select(
... dfn.functions.in_list(
... dfn.col("a"), [dfn.lit(1), dfn.lit(3)],
... negated=True,
... ).alias("not_in")
... )
>>> result.collect_column("not_in").to_pylist()
[False, True, False]
"""
values = [v.expr for v in values]
return Expr(f.in_list(arg.expr, values, negated))
def digest(value: Expr, method: Expr) -> Expr:
"""Computes the binary hash of an expression using the specified algorithm.
Standard algorithms are md5, sha224, sha256, sha384, sha512, blake2s,
blake2b, and blake3.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello"]})
>>> result = df.select(
... dfn.functions.digest(dfn.col("a"), dfn.lit("md5")).alias("d"))
>>> len(result.collect_column("d")[0].as_py()) > 0
True
"""
return Expr(f.digest(value.expr, method.expr))
def concat(*args: Expr) -> Expr:
"""Concatenates the text representations of all the arguments.
NULL arguments are ignored.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello"], "b": [" world"]})
>>> result = df.select(
... dfn.functions.concat(dfn.col("a"), dfn.col("b")).alias("c")
... )
>>> result.collect_column("c")[0].as_py()
'hello world'
"""
args = [arg.expr for arg in args]
return Expr(f.concat(args))
def concat_ws(separator: str, *args: Expr) -> Expr:
"""Concatenates the list ``args`` with the separator.
``NULL`` arguments are ignored. ``separator`` should not be ``NULL``.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello"], "b": ["world"]})
>>> result = df.select(
... dfn.functions.concat_ws("-", dfn.col("a"), dfn.col("b")).alias("c"))
>>> result.collect_column("c")[0].as_py()
'hello-world'
"""
args = [arg.expr for arg in args]
return Expr(f.concat_ws(separator, args))
def order_by(expr: Expr, ascending: bool = True, nulls_first: bool = True) -> SortExpr:
"""Creates a new sort expression.
Examples:
>>> sort_expr = dfn.functions.order_by(
... dfn.col("a"), ascending=False)
>>> sort_expr.ascending()
False
>>> sort_expr = dfn.functions.order_by(
... dfn.col("a"), ascending=True, nulls_first=False)
>>> sort_expr.nulls_first()
False
"""
return SortExpr(expr, ascending=ascending, nulls_first=nulls_first)
def alias(expr: Expr, name: str, metadata: dict[str, str] | None = None) -> Expr:
"""Creates an alias expression with an optional metadata dictionary.
Args:
expr: The expression to alias
name: The alias name
metadata: Optional metadata to attach to the column
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2]})
>>> result = df.select(
... dfn.functions.alias(
... dfn.col("a"), "b"
... )
... )
>>> result.collect_column("b")[0].as_py()
1
>>> result = df.select(
... dfn.functions.alias(
... dfn.col("a"), "b", metadata={"info": "test"}
... )
... )
>>> result.schema()
b: int64
-- field metadata --
info: 'test'
"""
return Expr(f.alias(expr.expr, name, metadata))
def col(name: str) -> Expr:
"""Creates a column reference expression.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, 3]})
>>> df.select(dfn.functions.col("a")).collect_column("a")[0].as_py()
1
"""
return Expr(f.col(name))
def count_star(filter: Expr | None = None) -> Expr:
"""Create a COUNT(1) aggregate expression.
This aggregate function will count all of the rows in the partition.
If using the builder functions described in ref:`_aggregation` this function ignores
the options ``order_by``, ``distinct``, and ``null_treatment``.
Args:
filter: If provided, only count rows for which the filter is True
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, 3]})
>>> result = df.aggregate(
... [], [dfn.functions.count_star(
... ).alias("cnt")])
>>> result.collect_column("cnt")[0].as_py()
3
>>> result = df.aggregate(
... [], [dfn.functions.count_star(
... filter=dfn.col("a") > dfn.lit(1)
... ).alias("cnt")])
>>> result.collect_column("cnt")[0].as_py()
2
"""
return count(Expr.literal(1), filter=filter)
def case(expr: Expr) -> CaseBuilder:
"""Create a case expression.
Create a :py:class:`~datafusion.expr.CaseBuilder` to match cases for the
expression ``expr``. See :py:class:`~datafusion.expr.CaseBuilder` for
detailed usage.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, 3]})
>>> result = df.select(
... dfn.functions.case(dfn.col("a")).when(dfn.lit(1),
... dfn.lit("one")).otherwise(dfn.lit("other")).alias("c"))
>>> result.collect_column("c")[0].as_py()
'one'
"""
return CaseBuilder(f.case(expr.expr))
def when(when: Expr, then: Expr) -> CaseBuilder:
"""Create a case expression that has no base expression.
Create a :py:class:`~datafusion.expr.CaseBuilder` to match cases for the
expression ``expr``. See :py:class:`~datafusion.expr.CaseBuilder` for
detailed usage.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, 3]})
>>> result = df.select(
... dfn.functions.when(dfn.col("a") > dfn.lit(2),
... dfn.lit("big")).otherwise(dfn.lit("small")).alias("c"))
>>> result.collect_column("c")[2].as_py()
'big'
"""
return CaseBuilder(f.when(when.expr, then.expr))
@deprecated("Prefer to call Expr.over() instead")
def window(
name: str,
args: list[Expr],
partition_by: list[Expr] | Expr | None = None,
order_by: list[SortKey] | SortKey | None = None,
window_frame: WindowFrame | None = None,
filter: Expr | None = None,
distinct: bool = False,
ctx: SessionContext | None = None,
) -> Expr:
"""Creates a new Window function expression.
This interface will soon be deprecated. Instead of using this interface,
users should call the window functions directly. For example, to perform a
lag use::
df.select(functions.lag(col("a")).partition_by(col("b")).build())
The ``order_by`` parameter accepts column names or expressions, e.g.::
window("lag", [col("a")], order_by="ts")
"""
args = [a.expr for a in args]
partition_by_raw = expr_list_to_raw_expr_list(partition_by)
order_by_raw = sort_list_to_raw_sort_list(order_by)
window_frame = window_frame.window_frame if window_frame is not None else None
ctx = ctx.ctx if ctx is not None else None
filter_raw = filter.expr if filter is not None else None
return Expr(
f.window(
name,
args,
partition_by=partition_by_raw,
order_by=order_by_raw,
window_frame=window_frame,
ctx=ctx,
filter=filter_raw,
distinct=distinct,
)
)
# scalar functions
def abs(arg: Expr) -> Expr:
"""Return the absolute value of a given number.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [-1, 0, 1]})
>>> result = df.select(dfn.functions.abs(dfn.col("a")).alias("abs"))
>>> result.collect_column("abs")[0].as_py()
1
"""
return Expr(f.abs(arg.expr))
def acos(arg: Expr) -> Expr:
"""Returns the arc cosine or inverse cosine of a number.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1.0]})
>>> result = df.select(dfn.functions.acos(dfn.col("a")).alias("acos"))
>>> result.collect_column("acos")[0].as_py()
0.0
"""
return Expr(f.acos(arg.expr))
def acosh(arg: Expr) -> Expr:
"""Returns inverse hyperbolic cosine.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1.0]})
>>> result = df.select(dfn.functions.acosh(dfn.col("a")).alias("acosh"))
>>> result.collect_column("acosh")[0].as_py()
0.0
"""
return Expr(f.acosh(arg.expr))
def ascii(arg: Expr) -> Expr:
"""Returns the numeric code of the first character of the argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["a","b","c"]})
>>> ascii_df = df.select(dfn.functions.ascii(dfn.col("a")).alias("ascii"))
>>> ascii_df.collect_column("ascii")[0].as_py()
97
"""
return Expr(f.ascii(arg.expr))
def asin(arg: Expr) -> Expr:
"""Returns the arc sine or inverse sine of a number.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0.0]})
>>> result = df.select(dfn.functions.asin(dfn.col("a")).alias("asin"))
>>> result.collect_column("asin")[0].as_py()
0.0
"""
return Expr(f.asin(arg.expr))
def asinh(arg: Expr) -> Expr:
"""Returns inverse hyperbolic sine.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0.0]})
>>> result = df.select(dfn.functions.asinh(dfn.col("a")).alias("asinh"))
>>> result.collect_column("asinh")[0].as_py()
0.0
"""
return Expr(f.asinh(arg.expr))
def atan(arg: Expr) -> Expr:
"""Returns inverse tangent of a number.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0.0]})
>>> result = df.select(dfn.functions.atan(dfn.col("a")).alias("atan"))
>>> result.collect_column("atan")[0].as_py()
0.0
"""
return Expr(f.atan(arg.expr))
def atanh(arg: Expr) -> Expr:
"""Returns inverse hyperbolic tangent.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0.0]})
>>> result = df.select(dfn.functions.atanh(dfn.col("a")).alias("atanh"))
>>> result.collect_column("atanh")[0].as_py()
0.0
"""
return Expr(f.atanh(arg.expr))
def atan2(y: Expr, x: Expr) -> Expr:
"""Returns inverse tangent of a division given in the argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"y": [0.0], "x": [1.0]})
>>> result = df.select(
... dfn.functions.atan2(dfn.col("y"), dfn.col("x")).alias("atan2"))
>>> result.collect_column("atan2")[0].as_py()
0.0
"""
return Expr(f.atan2(y.expr, x.expr))
def bit_length(arg: Expr) -> Expr:
"""Returns the number of bits in the string argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["a","b","c"]})
>>> bit_df = df.select(dfn.functions.bit_length(dfn.col("a")).alias("bit_len"))
>>> bit_df.collect_column("bit_len")[0].as_py()
8
"""
return Expr(f.bit_length(arg.expr))
def btrim(arg: Expr) -> Expr:
"""Removes all characters, spaces by default, from both sides of a string.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [" a "]})
>>> trim_df = df.select(dfn.functions.btrim(dfn.col("a")).alias("trimmed"))
>>> trim_df.collect_column("trimmed")[0].as_py()
'a'
"""
return Expr(f.btrim(arg.expr))
def cbrt(arg: Expr) -> Expr:
"""Returns the cube root of a number.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [27]})
>>> cbrt_df = df.select(dfn.functions.cbrt(dfn.col("a")).alias("cbrt"))
>>> cbrt_df.collect_column("cbrt")[0].as_py()
3.0
"""
return Expr(f.cbrt(arg.expr))
def ceil(arg: Expr) -> Expr:
"""Returns the nearest integer greater than or equal to argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1.9]})
>>> ceil_df = df.select(dfn.functions.ceil(dfn.col("a")).alias("ceil"))
>>> ceil_df.collect_column("ceil")[0].as_py()
2.0
"""
return Expr(f.ceil(arg.expr))
def character_length(arg: Expr) -> Expr:
"""Returns the number of characters in the argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["abc","b","c"]})
>>> char_len_df = df.select(
... dfn.functions.character_length(dfn.col("a")).alias("char_len"))
>>> char_len_df.collect_column("char_len")[0].as_py()
3
"""
return Expr(f.character_length(arg.expr))
def length(string: Expr) -> Expr:
"""The number of characters in the ``string``.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello"]})
>>> result = df.select(dfn.functions.length(dfn.col("a")).alias("len"))
>>> result.collect_column("len")[0].as_py()
5
"""
return Expr(f.length(string.expr))
def char_length(string: Expr) -> Expr:
"""The number of characters in the ``string``.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello"]})
>>> result = df.select(dfn.functions.char_length(dfn.col("a")).alias("len"))
>>> result.collect_column("len")[0].as_py()
5
"""
return Expr(f.char_length(string.expr))
def chr(arg: Expr) -> Expr:
"""Converts the Unicode code point to a UTF8 character.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [65]})
>>> result = df.select(dfn.functions.chr(dfn.col("a")).alias("chr"))
>>> result.collect_column("chr")[0].as_py()
'A'
"""
return Expr(f.chr(arg.expr))
def coalesce(*args: Expr) -> Expr:
"""Returns the value of the first expr in ``args`` which is not NULL.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [None, 1], "b": [2, 3]})
>>> result = df.select(
... dfn.functions.coalesce(dfn.col("a"), dfn.col("b")).alias("c"))
>>> result.collect_column("c")[0].as_py()
2
"""
args = [arg.expr for arg in args]
return Expr(f.coalesce(*args))
def cos(arg: Expr) -> Expr:
"""Returns the cosine of the argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0,-1,1]})
>>> cos_df = df.select(dfn.functions.cos(dfn.col("a")).alias("cos"))
>>> cos_df.collect_column("cos")[0].as_py()
1.0
"""
return Expr(f.cos(arg.expr))
def cosh(arg: Expr) -> Expr:
"""Returns the hyperbolic cosine of the argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0,-1,1]})
>>> cosh_df = df.select(dfn.functions.cosh(dfn.col("a")).alias("cosh"))
>>> cosh_df.collect_column("cosh")[0].as_py()
1.0
"""
return Expr(f.cosh(arg.expr))
def cot(arg: Expr) -> Expr:
"""Returns the cotangent of the argument.
Examples:
>>> from math import pi
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [pi / 4]})
>>> result = df.select(
... dfn.functions.cot(dfn.col("a")).alias("cot")
... )
>>> result.collect_column("cot")[0].as_py()
1.0...
"""
return Expr(f.cot(arg.expr))
def degrees(arg: Expr) -> Expr:
"""Converts the argument from radians to degrees.
Examples:
>>> from math import pi
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0,pi,2*pi]})
>>> deg_df = df.select(dfn.functions.degrees(dfn.col("a")).alias("deg"))
>>> deg_df.collect_column("deg")[2].as_py()
360.0
"""
return Expr(f.degrees(arg.expr))
def ends_with(arg: Expr, suffix: Expr) -> Expr:
"""Returns true if the ``string`` ends with the ``suffix``, false otherwise.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["abc","b","c"]})
>>> ends_with_df = df.select(
... dfn.functions.ends_with(dfn.col("a"), dfn.lit("c")).alias("ends_with"))
>>> ends_with_df.collect_column("ends_with")[0].as_py()
True
"""
return Expr(f.ends_with(arg.expr, suffix.expr))
def exp(arg: Expr) -> Expr:
"""Returns the exponential of the argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [0.0]})
>>> result = df.select(dfn.functions.exp(dfn.col("a")).alias("exp"))
>>> result.collect_column("exp")[0].as_py()
1.0
"""
return Expr(f.exp(arg.expr))
def factorial(arg: Expr) -> Expr:
"""Returns the factorial of the argument.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [3]})
>>> result = df.select(
... dfn.functions.factorial(dfn.col("a")).alias("factorial")
... )
>>> result.collect_column("factorial")[0].as_py()
6
"""
return Expr(f.factorial(arg.expr))
def find_in_set(string: Expr, string_list: Expr) -> Expr:
"""Find a string in a list of strings.
Returns a value in the range of 1 to N if the string is in the string list
``string_list`` consisting of N substrings.
The string list is a string composed of substrings separated by ``,`` characters.
Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["b"]})
>>> result = df.select(
... dfn.functions.find_in_set(dfn.col("a"), dfn.lit("a,b,c")).alias("pos"))
>>> result.collect_column("pos")[0].as_py()
2
"""
return Expr(f.find_in_set(string.expr, string_list.expr))