docstr: Parameters
  ----------
  df : pd.DataFrame
   contains category_col, and parse_col, were parsed col is entirely spacy docs
  category_col : str
                  name of category column in convention_df
  text_col : str
                  The name of the column which contains each document's raw text.
  feature_col : str
                  name of column in convention_df with a feature dictionary
  metadata_col : str, optional
                  name of column in convention_df with a meatadata dictionary
  parsed_col : str, optional
                  name of column in convention_df with parsed strings
docstr_tok: ["Parameters","--","--","--","--","--","df",":","pd.DataFrame","contains","category_col",",","and","parse_col",",","were","parsed","col","is","entirely","spacy","docs","category_col",":","str","name","of","category","column","in","convention_df","text_col",":","str","The","name","of","the","column","which","contains","each","document","'s","raw","text",".","feature_col",":","str","name","of","column","in","convention_df","with","a","feature","dictionary","metadata_col",":","str",",","optional","name","of","column","in","convention_df","with","a","meatadata","dictionary","parsed_col",":","str",",","optional","name","of","column","in","convention_df","with","parsed","strings"]
code: def __init__(
      self,
      df,
      category_col,
      text_col,
      feature_col,
      metadata_col=None,
      parsed_col=None,
  ):
      """
      Parameters
      ----------
      df : pd.DataFrame
       contains category_col, and parse_col, were parsed col is entirely spacy docs
      category_col : str
                      name of category column in convention_df
      text_col : str
                      The name of the column which contains each document's raw text.
      feature_col : str
                      name of column in convention_df with a feature dictionary
      metadata_col : str, optional
                      name of column in convention_df with a meatadata dictionary
      parsed_col : str, optional
                      name of column in convention_df with parsed strings
      """
      self._df = df.reset_index()
      self._category_col = category_col
      self._text_col = text_col
      self._feature_col = feature_col
      self._parsed_col = parsed_col
      self._metadata_col = metadata_col
      self._category_idx_store = IndexStore()
      self._X_factory = CSRMatrixFactory()
      self._mX_factory = CSRMatrixFactory()
      self._term_idx_store = IndexStore()
      self._metadata_idx_store = IndexStore()
  
file_path: scattertext/scattertext/CorpusFromFeatureDict.py
imports: import numpy
  from scattertext.CorpusDF import CorpusDF
  from scattertext.CSRMatrixTools import CSRMatrixFactory
  from scattertext.ParsedCorpus import ParsedCorpus
  from scattertext.indexstore.IndexStore import IndexStore
label_desc: Use image node_id 1 to create a new CorpusFromFeatureDict object from inherited base classes: object with example: obj = CorpusFromFeatureDict(df, category_col, text_col, feature_col, metadata_col, parsed_col)