code: def test_dirty_float_single_warning():
      with warnings.catch_warnings(record=True) as w:
          warnings.simplefilter("always")
  
          rng = np.random.RandomState(0)
          cont_clean = [
              "{:2.2f}".format(x) for x in rng.uniform(size=100)
          ]
  
          dirty3 = pd.Series(cont_clean)
          dirty3[::20] = [("missing", "but weird")] * 5
  
          X = pd.DataFrame({"dirty3": dirty3})
          clean(X)
  
          mixed_type_errors = sum(("Mixed type" in str(w2) for w2 in w))
          assert mixed_type_errors == 1
  
imports: import os
  import pytest
  import random
  import string
  import warnings
  import numpy
  import pandas
  from sklearn.datasets import load_iris, load_digits
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import make_pipeline
  from sklearn.linear_model import LogisticRegression
  from dabl.preprocessing import USELESS_TYPES, detect_types, EasyPreprocessor, DirtyFloatCleaner, clean, _FLOAT_REGEX, _float_matching, detect_type_series
  from dabl.utils import data_df_from_bunch
  from dabl.datasets import load_titanic
  from dabl import plot
label_desc: Use image node_id 10 for calling a global function with example usage: test_dirty_float_single_warning() without return types