Fixes issue where value_counts was not returning LuxSeries (#210)

* add series equality and value counts test

* black formatting

* fix old value counts test instead

* minor fix

Co-authored-by: Doris Lee <dorisjunglinlee@gmail.com>

lux/action/default.py

@@ -7,7 +7,6 @@ def register_default_actions():
     from lux.action.filter import add_filter
     from lux.action.generalize import generalize
 
-    print("Register default actions")
     # display conditions for default actions
     no_vis = lambda ldf: (ldf.current_vis is None) or (
         ldf.current_vis is not None and len(ldf.current_vis) == 0

lux/core/__init__.py

@@ -57,7 +57,7 @@ def setOption(overridePandas=True):
         ) = (
             pd.io.spss.DataFrame
         ) = pd.io.stata.DataFrame = pd.io.api.DataFrame = pd.core.frame.DataFrame = LuxDataFrame
-        pd.Series = LuxSeries
+        pd.Series = pd.core.series.Series = LuxSeries
     else:
         pd.DataFrame = pd.io.parsers.DataFrame = pd.core.frame.DataFrame = originalDF
         pd.Series = originalSeries

lux/core/series.py

@@ -88,7 +88,8 @@ def __repr__(self):
             # 1) Values of the series are of dtype objects (df.dtypes)
             is_dtype_series = all(isinstance(val, np.dtype) for val in self.values)
             # 2) Mixed type, often a result of a "row" acting as a series (df.iterrows, df.iloc[0])
-            mixed_dtype = len(set([type(val) for val in self.values])) > 1
+            # Tolerant for NaNs + 1 type
+            mixed_dtype = len(set([type(val) for val in self.values])) > 2
             if ldf._pandas_only or is_dtype_series or mixed_dtype:
                 print(series_repr)
                 ldf._pandas_only = False

tests/test_pandas_coverage.py

@@ -607,7 +607,7 @@ def test_value_counts(global_var):
     assert df.cardinality is not None
     series = df["Weight"]
     series.value_counts()
-    assert isinstance(series, lux.core.series.LuxSeries), "Derived series is type LuxSeries."
+    assert type(df["Brand"].value_counts()) == lux.core.series.LuxSeries
     assert df["Weight"]._metadata == [
         "_intent",
         "data_type",