code: def make_dirty_float():
      rng = np.random.RandomState(0)
      cont_clean = ["{:2.2f}".format(x) for x in rng.uniform(size=100)]
      dirty = pd.DataFrame(cont_clean, columns=["a_column"])
      dirty[::12] = "missing"
      dirty.iloc[3, 0] = "garbage"
      return dirty
  
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 1 for calling a global function with example usage: make_dirty_float() and returns: dirty