last dict fixings

Author: UrielMaD

pandas/tests/io/generate_legacy_storage_files.py

@@ -142,16 +142,16 @@ def create_data():
         "E": [0.0, 1, Timestamp("20100101"), "foo", 2.0],
     }
 
-    scalars = dict(timestamp=Timestamp("20130101"), period=Period("2012", "M"))
-
-    index = dict(
-        int=Index(np.arange(10)),
-        date=date_range("20130101", periods=10),
-        period=period_range("2013-01-01", freq="M", periods=10),
-        float=Index(np.arange(10, dtype=np.float64)),
-        uint=Index(np.arange(10, dtype=np.uint64)),
-        timedelta=timedelta_range("00:00:00", freq="30T", periods=10),
-    )
+    scalars = {"timestamp": Timestamp("20130101"), "period": Period("2012", "M")}
+
+    index = {
+        "int": Index(np.arange(10)),
+        "date": date_range("20130101", periods=10),
+        "period": period_range("2013-01-01", freq="M", periods=10),
+        "float": Index(np.arange(10, dtype=np.float64)),
+        "uint": Index(np.arange(10, dtype=np.uint64)),
+        "timedelta": timedelta_range("00:00:00", freq="30T", periods=10),
+    }
 
     index["range"] = RangeIndex(10)
 
@@ -160,8 +160,8 @@ def create_data():
 
         index["interval"] = interval_range(0, periods=10)
 
-    mi = dict(
-        reg2=MultiIndex.from_tuples(
+    mi = {
+        "reg2": MultiIndex.from_tuples(
             tuple(
                 zip(
                     *[
@@ -172,35 +172,35 @@ def create_data():
             ),
             names=["first", "second"],
         )
-    )
+    }
 
-    series = dict(
-        float=Series(data["A"]),
-        int=Series(data["B"]),
-        mixed=Series(data["E"]),
-        ts=Series(
+    series = {
+        "float": Series(data["A"]),
+        "int": Series(data["B"]),
+        "mixed": Series(data["E"]),
+        "ts": Series(
             np.arange(10).astype(np.int64), index=date_range("20130101", periods=10)
         ),
-        mi=Series(
+        "mi": Series(
             np.arange(5).astype(np.float64),
             index=MultiIndex.from_tuples(
                 tuple(zip(*[[1, 1, 2, 2, 2], [3, 4, 3, 4, 5]])), names=["one", "two"]
             ),
         ),
-        dup=Series(np.arange(5).astype(np.float64), index=["A", "B", "C", "D", "A"]),
-        cat=Series(Categorical(["foo", "bar", "baz"])),
-        dt=Series(date_range("20130101", periods=5)),
-        dt_tz=Series(date_range("20130101", periods=5, tz="US/Eastern")),
-        period=Series([Period("2000Q1")] * 5),
-    )
+        "dup": Series(np.arange(5).astype(np.float64), index=["A", "B", "C", "D", "A"]),
+        "cat": Series(Categorical(["foo", "bar", "baz"])),
+        "dt": Series(date_range("20130101", periods=5)),
+        "dt_tz": Series(date_range("20130101", periods=5, tz="US/Eastern")),
+        "period": Series([Period("2000Q1")] * 5),
+    }
 
     mixed_dup_df = DataFrame(data)
     mixed_dup_df.columns = list("ABCDA")
-    frame = dict(
-        float=DataFrame({"A": series["float"], "B": series["float"] + 1}),
-        int=DataFrame({"A": series["int"], "B": series["int"] + 1}),
-        mixed=DataFrame({k: data[k] for k in ["A", "B", "C", "D"]}),
-        mi=DataFrame(
+    frame = {
+        "float": DataFrame({"A": series["float"], "B": series["float"] + 1}),
+        "int": DataFrame({"A": series["int"], "B": series["int"] + 1}),
+        "mixed": DataFrame({k: data[k] for k in ["A", "B", "C", "D"]}),
+        "mi": DataFrame(
             {"A": np.arange(5).astype(np.float64), "B": np.arange(5).astype(np.int64)},
             index=MultiIndex.from_tuples(
                 tuple(
@@ -214,45 +214,45 @@ def create_data():
                 names=["first", "second"],
             ),
         ),
-        dup=DataFrame(
+        "dup": DataFrame(
             np.arange(15).reshape(5, 3).astype(np.float64), columns=["A", "B", "A"]
         ),
-        cat_onecol=DataFrame({"A": Categorical(["foo", "bar"])}),
-        cat_and_float=DataFrame(
+        "cat_onecol": DataFrame({"A": Categorical(["foo", "bar"])}),
+        "cat_and_float": DataFrame(
             {
                 "A": Categorical(["foo", "bar", "baz"]),
                 "B": np.arange(3).astype(np.int64),
             }
         ),
-        mixed_dup=mixed_dup_df,
-        dt_mixed_tzs=DataFrame(
+        "mixed_dup": mixed_dup_df,
+        "dt_mixed_tzs": DataFrame(
             {
                 "A": Timestamp("20130102", tz="US/Eastern"),
                 "B": Timestamp("20130603", tz="CET"),
             },
             index=range(5),
         ),
-        dt_mixed2_tzs=DataFrame(
+        "dt_mixed2_tzs": DataFrame(
             {
                 "A": Timestamp("20130102", tz="US/Eastern"),
                 "B": Timestamp("20130603", tz="CET"),
                 "C": Timestamp("20130603", tz="UTC"),
             },
             index=range(5),
         ),
-    )
+    }
 
-    cat = dict(
-        int8=Categorical(list("abcdefg")),
-        int16=Categorical(np.arange(1000)),
-        int32=Categorical(np.arange(10000)),
-    )
+    cat = {
+        "int8": Categorical(list("abcdefg")),
+        "int16": Categorical(np.arange(1000)),
+        "int32": Categorical(np.arange(10000)),
+    }
 
-    timestamp = dict(
-        normal=Timestamp("2011-01-01"),
-        nat=NaT,
-        tz=Timestamp("2011-01-01", tz="US/Eastern"),
-    )
+    timestamp = {
+        "normal": Timestamp("2011-01-01"),
+        "nat": NaT,
+        "tz": Timestamp("2011-01-01", tz="US/Eastern"),
+    }
 
     timestamp["freq"] = Timestamp("2011-01-01", freq="D")
     timestamp["both"] = Timestamp("2011-01-01", tz="Asia/Tokyo", freq="M")
@@ -282,18 +282,18 @@ def create_data():
         "Minute": Minute(1),
     }
 
-    return dict(
-        series=series,
-        frame=frame,
-        index=index,
-        scalars=scalars,
-        mi=mi,
-        sp_series=dict(float=_create_sp_series(), ts=_create_sp_tsseries()),
-        sp_frame=dict(float=_create_sp_frame()),
-        cat=cat,
-        timestamp=timestamp,
-        offsets=off,
-    )
+    return {
+        "series": series,
+        "frame": frame,
+        "index": index,
+        "scalars": scalars,
+        "mi": mi,
+        "sp_series": {"float": _create_sp_series(), "ts": _create_sp_tsseries()},
+        "sp_frame": {"float": _create_sp_frame()},
+        "cat": cat,
+        "timestamp": timestamp,
+        "offsets": off,
+    }
 
 
 def create_pickle_data():