Datasets:

aflah
/

autotrain-data-Engage

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Dataset Viewer

The dataset viewer is not available for this dataset.

Cannot get the config names for the dataset.

Error code:   ConfigNamesError
Exception:    ValueError
Message:      Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('json', {}), NamedSplit('validation'): ('json', {}), NamedSplit('test'): ('csv', {})}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response
                  for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1512, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1489, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1054, in get_module
                  module_name, default_builder_kwargs = infer_module_for_data_files(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 513, in infer_module_for_data_files
                  raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}")
              ValueError: Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('json', {}), NamedSplit('validation'): ('json', {}), NamedSplit('test'): ('csv', {})}

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AutoTrain Dataset for project: Engage

Dataset Descritpion

This dataset has been automatically processed by AutoTrain for project Engage.

Languages

The BCP-47 code for the dataset's language is unk.

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "feat_km_driven": 0.0296548632976001,
    "feat_seats": 0.4166666666666666,
    "feat_how_old": 0.1923076923076923,
    "feat_EngineCC": 0.5218120805369127,
    "feat_mileage_conv": 0.3666666666666666,
    "feat_torque_conv": 0.3509308849783218,
    "feat_max_power_conv": 0.2374727668845316,
    "feat_Automatic": 0.0,
    "feat_Manual": 1.0,
    "feat_First Owner": 1.0,
    "feat_Fourth & Above Owner": 0.0,
    "feat_Second Owner": 0.0,
    "feat_Test Drive Car": 0.0,
    "feat_Third Owner": 0.0,
    "feat_Dealer": 0.0,
    "feat_Individual": 1.0,
    "feat_Trustmark Dealer": 0.0,
    "feat_CNG": 0.0,
    "feat_Diesel": 1.0,
    "feat_LPG": 0.0,
    "feat_Petrol": 0.0,
    "target": 715000.0
  },
  {
    "feat_km_driven": 0.0338913328611081,
    "feat_seats": 0.2499999999999999,
    "feat_how_old": 0.4615384615384616,
    "feat_EngineCC": 0.0577181208053691,
    "feat_mileage_conv": 0.469047619047619,
    "feat_torque_conv": 0.0729405763835756,
    "feat_max_power_conv": 0.0367647058823529,
    "feat_Automatic": 0.0,
    "feat_Manual": 1.0,
    "feat_First Owner": 0.0,
    "feat_Fourth & Above Owner": 0.0,
    "feat_Second Owner": 1.0,
    "feat_Test Drive Car": 0.0,
    "feat_Third Owner": 0.0,
    "feat_Dealer": 0.0,
    "feat_Individual": 1.0,
    "feat_Trustmark Dealer": 0.0,
    "feat_CNG": 0.0,
    "feat_Diesel": 0.0,
    "feat_LPG": 0.0,
    "feat_Petrol": 1.0,
    "target": 110000.0
  }
]

Dataset Fields

The dataset has the following fields (also called "features"):

{
  "feat_km_driven": "Value(dtype='float64', id=None)",
  "feat_seats": "Value(dtype='float64', id=None)",
  "feat_how_old": "Value(dtype='float64', id=None)",
  "feat_EngineCC": "Value(dtype='float64', id=None)",
  "feat_mileage_conv": "Value(dtype='float64', id=None)",
  "feat_torque_conv": "Value(dtype='float64', id=None)",
  "feat_max_power_conv": "Value(dtype='float64', id=None)",
  "feat_Automatic": "Value(dtype='float64', id=None)",
  "feat_Manual": "Value(dtype='float64', id=None)",
  "feat_First Owner": "Value(dtype='float64', id=None)",
  "feat_Fourth & Above Owner": "Value(dtype='float64', id=None)",
  "feat_Second Owner": "Value(dtype='float64', id=None)",
  "feat_Test Drive Car": "Value(dtype='float64', id=None)",
  "feat_Third Owner": "Value(dtype='float64', id=None)",
  "feat_Dealer": "Value(dtype='float64', id=None)",
  "feat_Individual": "Value(dtype='float64', id=None)",
  "feat_Trustmark Dealer": "Value(dtype='float64', id=None)",
  "feat_CNG": "Value(dtype='float64', id=None)",
  "feat_Diesel": "Value(dtype='float64', id=None)",
  "feat_LPG": "Value(dtype='float64', id=None)",
  "feat_Petrol": "Value(dtype='float64', id=None)",
  "target": "Value(dtype='float32', id=None)"
}

Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

Split name	Num samples
train	7115
valid	791

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