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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def create_data(*args):
 """ Produce a single data object from an arbitrary number of different objects. This function returns a single `pandas.DataFrame` object from a collection of `Atoms` and `pandas.DataFrame` objects. The returned object, already indexed by `Atoms.name`, can be promptly used by e.g. `ChemicalSystem`. Parameters *args : `pandas.DataFrame` or `Atoms`-like All positional arguments are assumed to be sources of data. `Atoms`-like objects (i.e. any object accepted by the `Atoms` constructor) become single row records in the final returned data object. `pandas.DataFrame` data table objects, on the other hand, are concatenated together (by using `pandas.DataFrame.concat`). Returns ------- dataframe : `pandas.DataFrame` Resulting tabular data object. The returned object is guaranteed to be indexed by `Atoms.name`; if no column with this name exists at indexing time, a new column (with `None` values) is created for the purpose of indexing. Notes ----- The returned `pandas.DataFrame` will be indexed by `Atoms.name` (see examples below), which might be the same as `Atoms.jobfilename` if no name was given to the constructor of `Atoms` (e.g. mapping). Examples -------- name pyrrole 0 data/pyrrolate/pyrrolate.out -1 Name: charge, dtype: int64 """

    def _prepare_data(data):
        if not isinstance(data, _pd.DataFrame):
            try:
                data = _pd.DataFrame([data.to_series()])
            except AttributeError:
                data = _pd.DataFrame([Atoms(data).to_series()])
        if data.index.name != "name":
            if "name" not in data.columns:
                data["name"] = None
            data = data.set_index("name")
        return data.reset_index()
    args = map(_prepare_data, args)

    dataframe = _pd.concat(args, sort=False)
    return dataframe.set_index("name")