@@ -910,6 +910,9 @@ def chr(arg: Expr) -> Expr:
910910def coalesce (* args : Expr ) -> Expr :
911911 """Returns the value of the first expr in ``args`` which is not NULL.
912912
913+ Args:
914+ *args: Expressions to evaluate in order.
915+
913916 Examples:
914917 >>> ctx = dfn.SessionContext()
915918 >>> df = ctx.from_pydict({"a": [None, 1], "b": [2, 3]})
@@ -1091,6 +1094,10 @@ def greatest(*args: Expr) -> Expr:
10911094def ifnull (x : Expr , y : Expr ) -> Expr :
10921095 """Returns ``x`` if ``x`` is not NULL. Otherwise returns ``y``.
10931096
1097+ Args:
1098+ x: Expression to return when it is not NULL.
1099+ y: Fallback expression to return when ``x`` is NULL.
1100+
10941101 See Also:
10951102 This is an alias for :py:func:`nvl`.
10961103 """
@@ -1325,6 +1332,10 @@ def md5(arg: Expr) -> Expr:
13251332def nanvl (x : Expr , y : Expr ) -> Expr :
13261333 """Returns ``x`` if ``x`` is not ``NaN``. Otherwise returns ``y``.
13271334
1335+ Args:
1336+ x: Expression to return when it is not NaN.
1337+ y: Fallback expression to return when ``x`` is NaN.
1338+
13281339 Examples:
13291340 >>> ctx = dfn.SessionContext()
13301341 >>> df = ctx.from_pydict({"a": [np.nan, 1.0], "b": [0.0, 0.0]})
@@ -1341,6 +1352,10 @@ def nanvl(x: Expr, y: Expr) -> Expr:
13411352def nvl (x : Expr , y : Expr ) -> Expr :
13421353 """Returns ``x`` if ``x`` is not ``NULL``. Otherwise returns ``y``.
13431354
1355+ Args:
1356+ x: Expression to return when it is not NULL.
1357+ y: Fallback expression to return when ``x`` is NULL.
1358+
13441359 Examples:
13451360 >>> ctx = dfn.SessionContext()
13461361 >>> df = ctx.from_pydict({"a": [None, 1], "b": [0, 0]})
@@ -1358,6 +1373,11 @@ def nvl(x: Expr, y: Expr) -> Expr:
13581373def nvl2 (x : Expr , y : Expr , z : Expr ) -> Expr :
13591374 """Returns ``y`` if ``x`` is not NULL. Otherwise returns ``z``.
13601375
1376+ Args:
1377+ x: Expression to check for NULL.
1378+ y: Expression to return when ``x`` is not NULL.
1379+ z: Expression to return when ``x`` is NULL.
1380+
13611381 Examples:
13621382 >>> ctx = dfn.SessionContext()
13631383 >>> df = ctx.from_pydict({"a": [None, 1], "b": [10, 20], "c": [30, 40]})
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