class_docstr: This class extracts a number of basic text descriptives from FeedbackDataset
  records using the TextDescriptives library and adds them as record metadata.
class_docstr_tok: ["This","class","extracts","a","number","of","basic","text","descriptives","from","FeedbackDataset","records","using","the","TextDescriptives","library","and","adds","them","as","record","metadata","."]
docstr: Convert integer, boolean and floats columns in a dataframe
  to Python native types.
  
  Args:
      df (pd.DataFrame): The text descriptives dataframe.
  
  Returns:
      pd.DataFrame: The text descriptives dataframe with integer and boolean columns cast to Python native types.
docstr_tok: ["Convert","integer",",","boolean","and","floats","columns","in","a","dataframe","to","Python","native","types",".","Args",":","df","(","pd.DataFrame",")",":","The","text","descriptives","dataframe",".","Returns",":","pd.DataFrame",":","The","text","descriptives","dataframe","with","integer","and","boolean","columns","cast","to","Python","native","types","."]
code: def _cast_to_python_types(self, df: pd.DataFrame) -> pd.DataFrame:
      """
      Convert integer, boolean and floats columns in a dataframe
      to Python native types.
  
      Args:
          df (pd.DataFrame): The text descriptives dataframe.
  
      Returns:
          pd.DataFrame: The text descriptives dataframe with integer and boolean columns cast to Python native types.
      """
      # Select columns by data type
      int_cols = df.select_dtypes(include=["int64"]).columns
      bool_cols = df.select_dtypes(include=["boolean"]).columns
      float_cols = df.select_dtypes(include=["float64"]).columns
      # Cast integer columns to Python's native int type
      df[int_cols] = df[int_cols].astype(int)
      # Cast boolean columns to Python's native str type
      df[bool_cols] = df[bool_cols].astype(str)
      # Cast float columns to Python's native float type and round to 2 decimal places
      df[float_cols] = df[float_cols].astype(float).round(2)
      return df
  
imports: import logging
  import re
  import warnings
  from typing import Any, List, Optional, Union
  import numpy
  import pandas
  from rich.progress import Progress
  from argilla.client.feedback.dataset.local.dataset import FeedbackDataset
  from argilla.client.feedback.dataset.remote.dataset import RemoteFeedbackDataset
  from argilla.client.feedback.schemas.metadata import FloatMetadataProperty, IntegerMetadataProperty, TermsMetadataProperty
  from argilla.client.feedback.schemas.records import FeedbackRecord
  from argilla.client.feedback.schemas.remote.records import RemoteFeedbackRecord
  from argilla.utils.dependency import require_dependencies
label_desc: Use image node_id 4 for calling the TextDescriptivesExtractor obj's underlying member method code with example usage: obj._cast_to_python_types(df) and returns: df