ValueError: cannot convert NA to integer on some CS2 demos

[billfreeman44]

Describe the bug
Demo is from dathost. parsing it throws a ValueError: cannot convert NA to integer error.

Include Information to Reproduce
Just the basic example

Screenshots
error dump:

ValueError                                Traceback (most recent call last)
Cell In[1], line 3
      1 from awpy import parse_demo
----> 3 parsed = parse_demo(file="combine-challenger-mid1900-0_.dem")

File ~\OneDrive\Documents\GitHub\awpy\awpy\parser\demoparser.py:589, in parse_demo(file)
    587 damage = parser.parse_events([GameEvent.PLAYER_HURT.value], other=["game_phase"])
    588 damage_df = parse_damages(damage)
--> 589 damage_df = apply_round_num_to_df(damage_df, round_df)
    591 # Blockers (smokes, molotovs, etc.)
    592 effect = parser.parse_events(
    593     [
    594         GameEvent.INFERNO_STARTBURN.value,
   (...)
    598     ]
    599 )

File ~\OneDrive\Documents\GitHub\awpy\awpy\parser\demoparser.py:43, in apply_round_num_to_df(df, round_df)
     33 """Assigns a round num to each row in the DataFrame.
     34 
     35 Args:
   (...)
     40     pd.DataFrame: A dataframe with the round num assigned to column `round_num`.
     41 """
     42 print(round_df)
---> 43 interval_index = pd.IntervalIndex.from_arrays(
     44     round_df["round_start"], round_df["round_end_official"], closed="left"
     45 )
     46 intervals = pd.cut(df["tick"], interval_index)
     47 round_num_map = dict(zip(interval_index, round_df["round_num"], strict=True))

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\interval.py:300, in IntervalIndex.from_arrays(cls, left, right, closed, name, copy, dtype)
    269 @classmethod
    270 @Appender(
    271     _interval_shared_docs["from_arrays"]
   (...)
    297     dtype: Dtype | None = None,
    298 ) -> IntervalIndex:
    299     with rewrite_exception("IntervalArray", cls.__name__):
--> 300         array = IntervalArray.from_arrays(
    301             left, right, closed, copy=copy, dtype=dtype
    302         )
    303     return cls._simple_new(array, name=name)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\arrays\interval.py:539, in IntervalArray.from_arrays(cls, left, right, closed, copy, dtype)
    536 left = _maybe_convert_platform_interval(left)
    537 right = _maybe_convert_platform_interval(right)
--> 539 left, right, dtype = cls._ensure_simple_new_inputs(
    540     left,
    541     right,
    542     closed=closed,
    543     copy=copy,
    544     dtype=dtype,
    545 )
    546 cls._validate(left, right, dtype=dtype)
    548 return cls._simple_new(left, right, dtype=dtype)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\arrays\interval.py:311, in IntervalArray._ensure_simple_new_inputs(cls, left, right, closed, copy, dtype)
    308 left = maybe_upcast_numeric_to_64bit(left)
    310 right = ensure_index(right, copy=copy)
--> 311 right = maybe_upcast_numeric_to_64bit(right)
    313 if closed is None and isinstance(dtype, IntervalDtype):
    314     closed = dtype.closed

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\dtypes\cast.py:439, in maybe_upcast_numeric_to_64bit(arr)
    437 dtype = arr.dtype
    438 if is_signed_integer_dtype(dtype) and dtype != np.int64:
--> 439     return arr.astype(np.int64)
    440 elif is_unsigned_integer_dtype(dtype) and dtype != np.uint64:
    441     return arr.astype(np.uint64)

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexes\base.py:1017, in Index.astype(self, dtype, copy)
   1015 if isinstance(values, ExtensionArray):
   1016     with rewrite_exception(type(values).__name__, type(self).__name__):
-> 1017         new_values = values.astype(dtype, copy=copy)
   1019 elif isinstance(dtype, ExtensionDtype):
   1020     cls = dtype.construct_array_type()

File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\arrays\masked.py:498, in BaseMaskedArray.astype(self, dtype, copy)
    496 # to_numpy will also raise, but we get somewhat nicer exception messages here
    497 if is_integer_dtype(dtype) and self._hasna:
--> 498     raise ValueError("cannot convert NA to integer")
    499 if is_bool_dtype(dtype) and self._hasna:
    500     # careful: astype_nansafe converts np.nan to True
    501     raise ValueError("cannot convert float NaN to bool")

ValueError: cannot convert NA to integer

Additional context
n/a

[billfreeman44]

#306 should fix this