additional timezone selector example

pola-rs · Jul 1, 2023 · 8a4b8f8 · 8a4b8f8
1 parent 71792bc
commit 8a4b8f8
Showing 1 changed file with 24 additions and 19 deletions.
diff --git a/py-polars/polars/selectors.py b/py-polars/polars/selectors.py
@@ -498,6 +498,10 @@ def datetime(
     >>> import polars.selectors as cs
     >>> df = pl.DataFrame(
     ...     {
+    ...         "tstamp_tokyo": [
+    ...             datetime(1999, 7, 20, 20, 20, 16, 987654),
+    ...             datetime(2000, 5, 15, 21, 21, 21, 123465),
+    ...         ],
     ...         "tstamp_utc": [
     ...             datetime(2023, 4, 10, 12, 14, 16, 999666),
     ...             datetime(2025, 8, 25, 14, 18, 22, 666333),
@@ -513,6 +517,7 @@ def datetime(
     ...         "dt": [date(1999, 12, 31), date(2010, 7, 5)],
     ...     },
     ...     schema_overrides={
+    ...         "tstamp_tokyo": pl.Datetime("us", "Asia/Tokyo"),
     ...         "tstamp_utc": pl.Datetime("ns", "UTC"),
     ...         "tstamp": pl.Datetime("ns"),
     ...     },
@@ -521,15 +526,15 @@ def datetime(
     Select all datetime columns:
 
     >>> df.select(cs.datetime())
-    shape: (2, 3)
-    ┌────────────────────────────────┬─────────────────────────┬────────────────────────────┐
-    │ tstamp_utc                     ┆ tstamp                  ┆ dtime                      │
-    │ ---                            ┆ ---                     ┆ ---                        │
-    │ datetime[ns, UTC]              ┆ datetime[ns]            ┆ datetime[μs]               │
-    ╞════════════════════════════════╪═════════════════════════╪════════════════════════════╡
-    │ 2023-04-10 12:14:16.999666 UTC ┆ 2000-11-20 18:12:16.600 ┆ 2010-10-10 10:25:30.987    │
-    │ 2025-08-25 14:18:22.666333 UTC ┆ 2020-10-30 10:20:25.123 ┆ 2024-12-31 20:30:45.400500 │
-    └────────────────────────────────┴─────────────────────────┴────────────────────────────┘
+    shape: (2, 4)
+    ┌────────────────────────────────┬────────────────────────────────┬─────────────────────────┬────────────────────────────┐
+    │ tstamp_tokyo                   ┆ tstamp_utc                     ┆ tstamp                  ┆ dtime                      │
+    │ ---                            ┆ ---                            ┆ ---                     ┆ ---                        │
+    │ datetime[μs, Asia/Tokyo]       ┆ datetime[ns, UTC]              ┆ datetime[ns]            ┆ datetime[μs]               │
+    ╞════════════════════════════════╪════════════════════════════════╪═════════════════════════╪════════════════════════════╡
+    │ 1999-07-21 05:20:16.987654 JST ┆ 2023-04-10 12:14:16.999666 UTC ┆ 2000-11-20 18:12:16.600 ┆ 2010-10-10 10:25:30.987    │
+    │ 2000-05-16 06:21:21.123465 JST ┆ 2025-08-25 14:18:22.666333 UTC ┆ 2020-10-30 10:20:25.123 ┆ 2024-12-31 20:30:45.400500 │
+    └────────────────────────────────┴────────────────────────────────┴─────────────────────────┴────────────────────────────┘
 
     Select all datetime columns that have 'ns' precision:
 
@@ -547,15 +552,15 @@ def datetime(
     Select all datetime columns that have *any* timezone:
 
     >>> df.select(cs.datetime(time_zone="*"))
-    shape: (2, 1)
-    ┌────────────────────────────────┐
-    │ tstamp_utc                     │
-    │ ---                            │
-    │ datetime[ns, UTC]              │
-    ╞════════════════════════════════╡
-    │ 2023-04-10 12:14:16.999666 UTC │
-    │ 2025-08-25 14:18:22.666333 UTC │
-    └────────────────────────────────┘
+    shape: (2, 2)
+    ┌────────────────────────────────┬────────────────────────────────┐
+    │ tstamp_tokyo                   ┆ tstamp_utc                     │
+    │ ---                            ┆ ---                            │
+    │ datetime[μs, Asia/Tokyo]       ┆ datetime[ns, UTC]              │
+    ╞════════════════════════════════╪════════════════════════════════╡
+    │ 1999-07-21 05:20:16.987654 JST ┆ 2023-04-10 12:14:16.999666 UTC │
+    │ 2000-05-16 06:21:21.123465 JST ┆ 2025-08-25 14:18:22.666333 UTC │
+    └────────────────────────────────┴────────────────────────────────┘
 
     Select all datetime columns that have a *specific* timezone:
 
@@ -570,7 +575,7 @@ def datetime(
     │ 2025-08-25 14:18:22.666333 UTC │
     └────────────────────────────────┘
 
-    Select all datetime columns that do NOT have a timezone:
+    Select all datetime columns that have NO timezone:
 
     >>> df.select(cs.datetime(time_zone=None))
     shape: (2, 2)