old_contents: import pandas as pd
  import numpy as np
  
  data = pd.read_csv('../../data/raw/orbf_benin.csv' , delimiter = ';')
  
  ## Keep only data with claimed and verified values
  
  print('Length Complete Data :' + str(len(data)))
  data = data[(np.isnan(data.indicator_claimed_value) == False) & (np.isnan(data.indicator_verified_value) == False) ]
  print('Length Data with claimed and verified complete :' + str(len(data)))
  
  
  
  ## Formatting facilities names for simplicity
  data.entity_name[data.entity_name == 'CNHU-PPC (Centre National Hospitalier Universitaire Pneumo Phtysiologique de Cot CSC'] = "CNHU-PPC"
  
  
  data.entity_name = data.entity_name.str.title()
  ## Format Date Variables
  u = data['datafile_year'].astype(str) + '-' +  data['datafile_month'].astype(str)
  data['date'] = pd.to_datetime(u)
  data['period'] = data['date'].dt.to_period('M')
  
new_contents: import pandas as pd
  import numpy as np
  
  data = pd.read_csv('../../data/raw/orbf_benin.csv' , delimiter = ';')
  
  ## Keep only data with claimed and verified values
  
  print('Length Complete Data :' + str(len(data)))
  data = data[(np.isnan(data.indicator_claimed_value) == False) & (np.isnan(data.indicator_verified_value) == False) ]
  print('Length Data with claimed and verified complete :' + str(len(data)))
  
  ## Formatting facilities names for simplicity
  data.entity_name[data.entity_name == 'CNHU-PPC (Centre National Hospitalier Universitaire Pneumo Phtysiologique de Cot CSC'] = "CNHU-PPC"
  data.entity_name = data.entity_name.str.title()
  
  ## Format Date Variables
  u = data['datafile_year'].astype(str) + '-' +  data['datafile_month'].astype(str)
  data['date'] = pd.to_datetime(u)
  data['period'] = data['date'].dt.to_period('M')
  
  to_export = ['entity_id' , 'entity_name' , 'entity_type' , 'parent_geozone_name' , 'geozone_name' , 'entity_fosa_id' ,  'content' , 'entity_status' , 'entity_active' , 'filetype_name' , 'filetype_id' , 'datafile_total' , 'datafile_author_id' , 'indicator_id' , 'indicator_title' , 'indicator_claimed_value' , 'indicator_verified_value' ,   'indicator_tarif' , 'indicator_montant' , 'entity_pop' , 'entity_pop_year' , 'geozone_pop' , 'geozone_pop_year' , 'parent_geozone_pop' , 'parent_geozone_pop_year']
  
  ## Qu'est-ce que entity group ?
  ## Datafile status
  
  len(to_export)
  len(data.columns)
  
  
  data['datafile_status'].value_counts()
  
  out = data[]
  
  data.columns
  
subject: Select columns of interest