code: def test_with_wrong_input(self):
      test_df = pd.DataFrame(
          [{"id": 0, "kind": "a", "value": 3, "sort": np.NaN}]
      )
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", "kind", "value", "sort"
      )
  
      test_df = pd.DataFrame(
          [{"id": 0, "kind": "a", "value": 3, "sort": 1}]
      )
      self.assertRaises(
          ValueError,
          to_tsdata,
          test_df,
          "strange_id",
          "kind",
          "value",
          "sort",
      )
      test_df = dd.from_pandas(test_df, npartitions=1)
      self.assertRaises(
          ValueError,
          to_tsdata,
          test_df,
          "strange_id",
          "kind",
          "value",
          "sort",
      )
  
      test_df = pd.DataFrame(
          [{"id": 0, "kind": "a", "value": 3, "value_2": 1, "sort": 1}]
      )
      self.assertRaises(
          ValueError,
          to_tsdata,
          test_df,
          "strange_id",
          "kind",
          None,
          "sort",
      )
      test_df = dd.from_pandas(test_df, npartitions=1)
      self.assertRaises(
          ValueError,
          to_tsdata,
          test_df,
          "strange_id",
          "kind",
          None,
          "sort",
      )
  
      test_df = pd.DataFrame(
          [{"id": 0, "kind": "a", "value": 3, "sort": 1}]
      )
      self.assertRaises(
          ValueError,
          to_tsdata,
          test_df,
          "id",
          "strange_kind",
          "value",
          "sort",
      )
      test_df = dd.from_pandas(test_df, npartitions=1)
      self.assertRaises(
          ValueError,
          to_tsdata,
          test_df,
          "id",
          "strange_kind",
          "value",
          "sort",
      )
  
      test_df = pd.DataFrame(
          [{"id": np.NaN, "kind": "a", "value": 3, "sort": 1}]
      )
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", "kind", "value", "sort"
      )
  
      test_df = pd.DataFrame(
          [{"id": 0, "kind": np.NaN, "value": 3, "sort": 1}]
      )
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", "kind", "value", "sort"
      )
  
      test_df = pd.DataFrame([{"id": 2}, {"id": 1}])
      test_dd = dd.from_pandas(test_df, npartitions=1)
      test_dict = {"a": test_df, "b": test_df}
  
      # column_id needs to be given
      self.assertRaises(
          ValueError, to_tsdata, test_df, None, "a", "b", None
      )
      self.assertRaises(
          ValueError, to_tsdata, test_dd, None, "a", "b", None
      )
      self.assertRaises(
          ValueError, to_tsdata, test_df, None, "a", "b", "a"
      )
      self.assertRaises(
          ValueError, to_tsdata, test_dd, None, "a", "b", "a"
      )
      self.assertRaises(
          ValueError, to_tsdata, test_dict, None, "a", "b", None
      )
      self.assertRaises(
          ValueError, to_tsdata, test_dict, None, "a", "b", "a"
      )
  
      # If there are more than one column, the algorithm can not choose the correct column
      self.assertRaises(
          ValueError, to_tsdata, test_dict, "id", None, None, None
      )
  
      test_dict = {
          "a": pd.DataFrame(
              [{"id": 2, "value_a": 3}, {"id": 1, "value_a": 4}]
          ),
          "b": pd.DataFrame([{"id": 2}, {"id": 1}]),
      }
  
      # If there are more than one column, the algorithm can not choose the correct column
      self.assertRaises(
          ValueError, to_tsdata, test_dict, "id", None, None, None
      )
  
      test_df = pd.DataFrame([{"id": 0, "value": np.NaN}])
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, "value", None
      )
  
      test_df = pd.DataFrame([{"id": 0, "value": np.NaN}])
      self.assertRaises(
          ValueError, to_tsdata, test_df, None, None, "value", None
      )
  
      test_df = pd.DataFrame([{"id": 0, "a_": 3, "b": 5, "sort": 1}])
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, "sort"
      )
      test_df = dd.from_pandas(test_df, npartitions=1)
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, "sort"
      )
  
      test_df = pd.DataFrame([{"id": 0, "a__c": 3, "b": 5, "sort": 1}])
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, "sort"
      )
      test_df = dd.from_pandas(test_df, npartitions=1)
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, "sort"
      )
  
      test_df = pd.DataFrame([{"id": 0}])
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, None
      )
      test_df = dd.from_pandas(test_df, npartitions=1)
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, None
      )
  
      test_df = pd.DataFrame([{"id": 0, "sort": 0}])
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, "sort"
      )
      test_df = dd.from_pandas(test_df, npartitions=1)
      self.assertRaises(
          ValueError, to_tsdata, test_df, "id", None, None, "sort"
      )
  
      test_df = [1, 2, 3]
      self.assertRaises(
          ValueError, to_tsdata, test_df, "a", "b", "c", "d"
      )
  
imports: import math
  from unittest import TestCase
  from unittest.mock import Mock
  import numpy
  import pandas
  from dask import dataframe
  from tests.fixtures import DataTestCase
  from tsfresh.feature_extraction.data import LongTsFrameAdapter, PartitionedTsData, TsDictAdapter, WideTsFrameAdapter, to_tsdata
  from tsfresh.utilities.distribution import MultiprocessingDistributor
label_desc: Use image node_id 15 for calling the DataAdapterTestCase obj's underlying member method code with example usage: obj.test_with_wrong_input() without return types