import pandas as pd


orders = pd.DataFrame(
    {
        "order_id": [1001, 1002, 1003, 1004],
        "ordered_at": [
            "2026-06-01 09:30",
            "2026-06-02 14:00",
            "not recorded",
            "2026-06-04 08:15",
        ],
        "shipped_at": [
            "2026-06-01T17:45:00+08:00",
            "2026-06-02T07:10:00Z",
            "bad timestamp",
            "2026-06-04T12:00:00+08:00",
        ],
    }
)

orders["ordered_at"] = pd.to_datetime(
    orders["ordered_at"],
    format="%Y-%m-%d %H:%M",
    errors="coerce",
)
orders["shipped_at_utc"] = pd.to_datetime(
    orders["shipped_at"],
    errors="coerce",
    utc=True,
)

print(f"pandas {pd.__version__}")
print()
print(orders.filter(["order_id", "ordered_at", "shipped_at_utc"]).to_string(index=False))
print()
print(orders.filter(["ordered_at", "shipped_at_utc"]).dtypes)
print()
print("parse failures")
print(orders.loc[orders["ordered_at"].isna() | orders["shipped_at_utc"].isna(), ["order_id", "ordered_at", "shipped_at"]].to_string(index=False))