From 3858302ba23d6bfb70614c1228ffca300d4e1f1c Mon Sep 17 00:00:00 2001
From: Julia Signell <jsignell@gmail.com>
Date: Mon, 15 Mar 2021 13:47:40 -0400
Subject: [PATCH] Just use kwargs in aca

---
 dask/dataframe/core.py    | 13 ++++---------
 dask/dataframe/methods.py | 10 ++++++----
 2 files changed, 10 insertions(+), 13 deletions(-)

diff --git a/dask/dataframe/core.py b/dask/dataframe/core.py
index 983d4f0a18c..39aaca5dd2b 100644
--- a/dask/dataframe/core.py
+++ b/dask/dataframe/core.py
@@ -3134,12 +3134,8 @@ def value_counts(
         Note: dropna is only supported in pandas >= 1.1.0, in which case it defaults to
         True.
         """
-        aggregate_kwargs = {
-            "sort": sort,
-            "ascending": ascending,
-            "normalize": normalize,
-        }
-        kwargs = {}
+        kwargs = {"sort": sort, "ascending": ascending, "normalize": normalize}
+
         if dropna is not None:
             if not PANDAS_GT_110:
                 raise NotImplementedError(
@@ -3148,8 +3144,8 @@ def value_counts(
                 )
             kwargs["dropna"] = dropna
 
-        if split_out > 1 and normalize:
-            aggregate_kwargs["length"] = (
+        if split_out > 1:
+            kwargs["total_length"] = (
                 len(self) if dropna is False else len(self.dropna())
             )
 
@@ -3163,7 +3159,6 @@ def value_counts(
             split_every=split_every,
             split_out=split_out,
             split_out_setup=split_out_on_index,
-            aggregate_kwargs=aggregate_kwargs,
             **kwargs,
         )
 
diff --git a/dask/dataframe/methods.py b/dask/dataframe/methods.py
index 9c70e14f670..02a22fec7b2 100644
--- a/dask/dataframe/methods.py
+++ b/dask/dataframe/methods.py
@@ -304,17 +304,19 @@ def unique(x, series_name=None):
     return out
 
 
-def value_counts_combine(x, **groupby_kwargs):
-    # sort, ascending, and normalize don't actually matter until the agg step
+def value_counts_combine(
+    x, sort=True, ascending=False, normalize=False, total_length=None, **groupby_kwargs
+):
+    # sort, ascending, normalize, and total_length don't actually matter until the agg step
     return x.groupby(level=0, **groupby_kwargs).sum()
 
 
 def value_counts_aggregate(
-    x, sort=True, ascending=False, normalize=False, length=None, **groupby_kwargs
+    x, sort=True, ascending=False, normalize=False, total_length=None, **groupby_kwargs
 ):
     out = value_counts_combine(x, **groupby_kwargs)
     if normalize:
-        out /= length if length is not None else out.sum()
+        out /= total_length if total_length is not None else out.sum()
     if sort:
         return out.sort_values(ascending=ascending)
     return out