BEEP structuring Error "No object to concatenate"

Question

I have a made the csv file as requested by the beep library as folllows:

enter image description here

When I try to validtae the data from the cycler. It says validation has failed.

And I get the error:

  File "C:\Users\concat.py", line 403, in __init__
    raise ValueError("No objects to concatenate")

ValueError: No objects to concatenate

I know it means the data is missing but I dont see any. After doing print I see the data of the csv on print but it does not work.

class VLCyclerDatapath(BEEPDatapath):
    """An example of implementing a custom BEEPDatapath for your own cycler.
    """
    COLUMN_MAPPING = {
        "cycle_index": "cycle_index",
        "step_index": "step_index",
        "step_type":"step_type",
        "step_time": "step_time",
        "test_time": "test_time",
        "current": "current",
        "voltage": "voltage",
        "charge_capacity": "charge_capacity",
        "discharge_capacity": "discharge_capacity",
        "charge_energy": "charge_energy",
        "discharge_energy": "discharge_energy",    
    }

    # Mapping of data types for BEEP columns
    DATA_TYPES = {
        "cycle_index": "int32",
        "step_index": "int32",
        "step_time": "float32",
        "test_time": "float64",
        "current": "float32",
        "voltage": "float32",
        "charge_capacity": "float64",
        "discharge_capacity": "float64",
        "charge_energy": "float64",
        "discharge_energy": "float64",
    }
    @classmethod
    def from_file(cls, filename, metadata_path=None):
        # Load your file from the raw file filename

        df = pd.read_csv(filename)
        # data.rename(columns=cls.COLUMN_MAPPING, inplace=True)
        
        
        for column, dtype in cls.DATA_TYPES.items():
            if column in df:
                if not df[column].isnull().values.any():
                    df[column] = df[column].astype(dtype)
                  
                         
  # Read in metadata from a separate json file, for example
        metadata = dict()
        path = filename
 
        paths = {
           "raw": path,
           "metadata": path + "_metadata"
       }
        print(df)

        return cls(df, metadata, paths)

this_dir = os.path.dirname(os.path.abspath(__file__))
cycler_file = os.path.join(this_dir,("Trial_Writing.csv"))
print (cycler_file )


datapath = VLCyclerDatapath.from_file(cycler_file)
datapath.to_json_file("Trial_neware_data.json")
is_valid, msg = datapath.validate()

print("File is valid: ", is_valid)

datapath.structure()

Any suggestions?