# Buggy code
def _from_arraylike(cls, data, freq):
    if not isinstance(data, np.ndarray):
        if np.isscalar(data) or isinstance(data, Period):
            raise ValueError(
                "PeriodIndex() must be called with a "
                "collection of some kind, %s was passed" % repr(data)
            )

        # other iterable of some kind
        if not isinstance(data, (list, tuple)):
            data = list(data)

        try:
            data = np.array(data, dtype="i8")
        except (TypeError, ValueError):
            data = np.array(data, dtype="O")

        if freq is None and len(data) > 0:
            freq = getattr(data[0], "freq", None)

        if freq is None:
            raise ValueError(
                ("freq not specified and cannot be inferred from first element")
            )

        data = _period_unbox_array(data, check=freq)
    else:
        if isinstance(data, PeriodIndex):
            if freq is None or freq == data.freq:
                freq = data.freq
                data = data.values
            else:
                base1, _ = _gfc(data.freq)
                base2, _ = _gfc(freq)
                data = plib.period_asfreq_arr(data.values, base1, base2, 1)
        else:
            if freq is None and len(data) > 0:
                freq = getattr(data[0], "freq", None)

            if freq is None:
                raise ValueError(
                    ("freq not specified and cannot be inferred from first element")
                )

            if np.issubdtype(data.dtype, np.datetime64):
                data = dt64arr_to_periodarr(data, freq)
            elif data.dtype == np.int64:
                pass
            else:
                try:
                    data = data.astype("i8")
                except (TypeError, ValueError):
                    data = data.astype("O")
                    data = _period_unbox_array(data, check=freq)

    return data, freq


# Traceback (IndexError)
In [1]: from pandas import *

In [2]: a = DataFrame(columns=['column1'], data=[1])

In [3]: b = DataFrame(columns=['column1'])

In [4]: a.merge(b, on=['column1'], how='left')


IndexError                                Traceback (most recent call last)
IndexError: index out of range for array

# Fixed code
def _from_arraylike(cls, data, freq):
    if not isinstance(data, np.ndarray):
        if np.isscalar(data) or isinstance(data, Period):
            raise ValueError(
                "PeriodIndex() must be called with a "
                "collection of some kind, %s was passed" % repr(data)
            )

        # other iterable of some kind
        if not isinstance(data, (list, tuple)):
            data = list(data)

        try:
            data = com._ensure_int64(data)
            if freq is None:
                raise ValueError("freq not specified")
            data = np.array(
                [Period(x, freq=freq).ordinal for x in data], dtype=np.int64
            )
        except (TypeError, ValueError):
            data = com._ensure_object(data)

            if freq is None and len(data) > 0:
                freq = getattr(data[0], "freq", None)

            if freq is None:
                raise ValueError(
                    "freq not specified and cannot be inferred from first element"
                )

            data = _get_ordinals(data, freq)
    else:
        if isinstance(data, PeriodIndex):
            if freq is None or freq == data.freq:
                freq = data.freq
                data = data.values
            else:
                base1, _ = _gfc(data.freq)
                base2, _ = _gfc(freq)
                data = plib.period_asfreq_arr(data.values, base1, base2, 1)
        else:
            if freq is None and len(data) > 0:
                freq = getattr(data[0], "freq", None)

            if freq is None:
                raise ValueError(
                    ("freq not specified and cannot be inferred from first element")
                )

            if np.issubdtype(data.dtype, np.datetime64):
                data = dt64arr_to_periodarr(data, freq)
            elif data.dtype == np.int64:
                pass
            else:
                try:
                    data = com._ensure_int64(data)
                except (TypeError, ValueError):
                    data = com._ensure_object(data)
                    data = _get_ordinals(data, freq)

    return data, freq