kosiew commented on code in PR #1418:
URL:
https://github.com/apache/datafusion-python/pull/1418#discussion_r2929595651
##########
python/datafusion/functions.py:
##########
@@ -2516,6 +2516,14 @@ def first_value(
For example::
df.aggregate([], first_value(col("a"), order_by="ts"))
+
+ Examples:
+ ---------
+ >>> ctx = dfn.SessionContext()
+ >>> df = ctx.from_pydict({"a": [10, 20, 30]})
+ >>> result = df.aggregate([],
[dfn.functions.first_value(dfn.col("a")).alias("v")])
Review Comment:
2518: df.aggregate([], expr)
2524: ...df.aggregate([], [expr])
Mixing both forms inside the same docstring makes the API shape feel less
crisp than it could be.
Same observation for `first_value`, `last_value`, and `nth_value`
##########
python/datafusion/functions.py:
##########
@@ -2995,6 +3074,22 @@ def cume_dist(
For example::
cume_dist(order_by="points")
+
+ Examples:
+ ---------
+ >>> ctx = dfn.SessionContext()
+ >>> df = ctx.from_pydict({"a": [10, 10, 20]})
+ >>> import builtins
+ >>> result = df.select(
+ ... dfn.col("a"),
+ ... dfn.functions.cume_dist(
+ ... order_by="a"
+ ... ).alias("cd")
+ ... )
+ >>> [builtins.round(x, 4) for x in
+ ... result.sort(dfn.col("a")
+ ... ).collect_column("cd").to_pylist()]
+ [0.6667, 0.6667, 1.0]
Review Comment:
I think this would be a simpler example without builtin:
```
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, 2, 3]})
>>> result = df.select(cume_dist(col("a"))).collect()[0]
>>> rounded = [round(x, 2) for x in result.column(0)]
>>> rounded
[0.25, 0.75, 0.75, 1.0]
```
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