code: def get_valid_datatypes_from_meta(meta: dict):
      """
      Parse the meta data into valid input for data analyzers
  
      Args:
          meta: dict, data meta data
  
      Returns:
          feature: dict, which maps to data type for feature names
          valid_feature_names: list, which contains all valid feature names
          valid_feature_types: list, which contains all valid feature types
          sequence_features: list, which contains all sequence features
          label: str, label column name
      """
      label = None
      sequence_features = []
      valid_feature_names = []
      valid_feature_types = []
      feature = dict()
      feature[DATATYPE.CATEGORY] = []
      feature[DATATYPE.NUMBER] = []
      feature[DATATYPE.FREETEXT] = []
      feature[DATATYPE.DATETIME] = []
  
      for feature_name, feature_config in meta.items():
          feature_type = feature_config[DATATYPE.TYPE]
          structured = feature_config[DATATYPE.STRUCTURED]
  
          if structured == DATATYPE.SEQUENCE:
              sequence_features.append(feature_name)
  
          if feature_type == DATATYPE.LABEL:
              label = feature_name
          if feature_type == DATATYPE.CATEGORY:
              valid_feature_types.append(DATATYPE.CATEGORY)
              valid_feature_names.append(feature_name)
              feature[DATATYPE.CATEGORY].append(feature_name)
          elif feature_type == DATATYPE.NUMBER:
              valid_feature_types.append(DATATYPE.NUMBER)
              valid_feature_names.append(feature_name)
              feature[DATATYPE.NUMBER].append(feature_name)
          elif feature_type == DATATYPE.FREETEXT:
              valid_feature_types.append(DATATYPE.FREETEXT)
              valid_feature_names.append(feature_name)
              feature[DATATYPE.FREETEXT].append(feature_name)
          elif feature_type == DATATYPE.DATETIME:
              valid_feature_types.append(DATATYPE.DATETIME)
              valid_feature_names.append(feature_name)
              feature[DATATYPE.DATETIME].append(feature_name)
  
      return (
          feature,
          valid_feature_names,
          valid_feature_types,
          sequence_features,
          label,
      )
  
file_path: contextual-ai/xai/data/helper.py
imports: import json
  import warnings
  from collections import Counter
  from statistics import median
  import dateutil
  import numpy
  import math
  from xai.data.constants import DATATYPE, THRESHOLD
  from xai.data.explorer import CategoricalDataAnalyzer, DataAnalyzerSuite
  from xai.data.validator import MissingValidator
label_desc: Use image node_id 2 for calling a global function with example usage: get_valid_datatypes_from_meta(meta) and returns: feature,  valid_feature_names,  valid_feature_types,  sequence_features,  label