code: def compute_features_import(dataframe):
      """
      Compute a relative features importance, sum of absolute values
       ​​of the contributions for each
       features importance compute in base 100
      Parameters
      ----------
      dataframe: pd.DataFrame
          Matrix containing all contributions
  
      Returns
      -------
      pd.Series
          feature importance One row by feature,
          index of the serie = dataframe.columns
      """
      feat_imp = dataframe.abs().sum().sort_values(ascending=True)
      tot = feat_imp.sum()
      return feat_imp / tot
  
file_path: shapash/shapash/manipulation/summarize.py
imports: import warnings
  import numpy
  import pandas
  from pandas.core.common import flatten
  from sklearn.manifold import TSNE
  from shapash.utils.transform import get_features_transform_mapping
label_desc: Use image node_id 2 for calling a global function with example usage: compute_features_import(dataframe) and returns: unknown