code: import numpy as np
  import pandas as pd
  import gzip
  
  input_file = 'predictions/2nd-place-233-seq.csv'
  nickname='kazuki2'
  
  df = pd.read_csv('../233x_sequences_degdata_081120.csv')
  df1 = pd.read_csv(input_file)
  
  df1['ID'] = [int(x.split('_')[0]) for x in df1['id_seqpos']]
  df1['seqpos'] = [int(x.split('_')[1]) for x in df1['id_seqpos']]
  
  df1['startpos'] = df['startpos']
  df1['endpos'] = df['endpos']
  
  for data_type in ['reactivity', 'deg_Mg_pH10', 'deg_pH10', 'deg_Mg_50C','deg_50C']:
      output_array = np.ones([233,1588])*np.NaN
  
      for _, row in df1.iterrows():
          output_array[row['ID'],row['seqpos']] = row[data_type]
  
      np.savetxt('formatted_predictions/%s_%s_flat_FULL_233x.csv' % (nickname, data_type),output_array, delimiter=',')
  
      for i, row in df1.iterrows():
          if not np.isnan(row['startpos']):
              output_array[i, :int(row['startpos'])] = np.NaN
              output_array[i, int(row['endpos']):] = np.NaN
              
      np.savetxt('formatted_predictions/%s_%s_flat_PCR_233x.csv' % (nickname, data_type),output_array, delimiter=',')
  
apis: pandas.read_csv numpy.savetxt numpy.ones numpy.isnan