From aaeb39b1ef2aabfd47707459eca3fbee057aca5c Mon Sep 17 00:00:00 2001
From: Alexey Prutskov <alexey.prutskov@intel.com>
Date: Tue, 25 Aug 2020 15:17:41 +0300
Subject: [PATCH] FIX-#1646: Fix representation of `Series` with datetimelike
 index

Signed-off-by: Alexey Prutskov <alexey.prutskov@intel.com>
---
 modin/pandas/series.py           | 11 ++++++++---
 modin/pandas/test/test_series.py | 26 ++++++++++++++++++--------
 2 files changed, 26 insertions(+), 11 deletions(-)

diff --git a/modin/pandas/series.py b/modin/pandas/series.py
index 939806c3bda..ce8c1459d88 100644
--- a/modin/pandas/series.py
+++ b/modin/pandas/series.py
@@ -308,6 +308,11 @@ def __repr__(self):
         if isinstance(temp_df, pandas.DataFrame) and not temp_df.empty:
             temp_df = temp_df.iloc[:, 0]
         temp_str = repr(temp_df)
+        freq_str = (
+            "Freq: {}, ".format(self.index.freqstr)
+            if isinstance(self.index, pandas.DatetimeIndex)
+            else ""
+        )
         if self.name is not None:
             name_str = "Name: {}, ".format(str(self.name))
         else:
@@ -322,9 +327,9 @@ def __repr__(self):
             else temp_str.rsplit("dtype: ", 1)[-1]
         )
         if len(self) == 0:
-            return "Series([], {}{}".format(name_str, dtype_str)
-        return temp_str.rsplit("\nName:", 1)[0] + "\n{}{}{}".format(
-            name_str, len_str, dtype_str
+            return "Series([], {}{}{}".format(freq_str, name_str, dtype_str)
+        return temp_str.rsplit("\n", 1)[0] + "\n{}{}{}{}".format(
+            freq_str, name_str, len_str, dtype_str
         )
 
     def __round__(self, decimals=0):
diff --git a/modin/pandas/test/test_series.py b/modin/pandas/test/test_series.py
index b866e585ef3..57dc0c8a3de 100644
--- a/modin/pandas/test/test_series.py
+++ b/modin/pandas/test/test_series.py
@@ -474,14 +474,24 @@ def test___pow__(data):
     inter_df_math_helper(modin_series, pandas_series, "__pow__")
 
 
-def test___repr___empty():
-    modin_series, pandas_series = pd.Series(), pandas.Series()
-    assert repr(modin_series) == repr(pandas_series)
-
-
-@pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
-def test___repr__(data):
-    modin_series, pandas_series = create_test_series(data)
+@pytest.mark.parametrize("name", ["Dates", None])
+@pytest.mark.parametrize(
+    "dt_index", [True, False], ids=["dt_index_true", "dt_index_false"]
+)
+@pytest.mark.parametrize(
+    "data", [*test_data_values, "empty"], ids=[*test_data_keys, "empty"]
+)
+def test___repr__(name, dt_index, data):
+    if data == "empty":
+        modin_series, pandas_series = pd.Series(), pandas.Series()
+    else:
+        modin_series, pandas_series = create_test_series(data)
+    pandas_series.name = modin_series.name = name
+    if dt_index:
+        index = pandas.date_range(
+            "1/1/2000", periods=len(pandas_series.index), freq="T"
+        )
+        pandas_series.index = modin_series.index = index
     assert repr(modin_series) == repr(pandas_series)