In [1]:

    

import numpy as np, pandas as pd


    

In [2]:

    

path = '/media/mike/tera/data/erplab/Test_Data/S1/'


    

In [9]:

    

eventfile = path + 'event_mapping_1.txt'
# event_mapping = pd.read_csv(path + 'event_mapping_1.txt', sep=r'\s*', header=None) # wrong!
event_mapping = pd.read_fwf(eventfile, header=None) # correct!
event_mapping


    

    
Out[9]:






  

    

      

      
0
      
1
      
2
      
3
    
  
  

    

      
0
      
22
      
"Frequent_Digit"
      
1
      
"Frequent Category (Digit)"
    
    

      
1
      
12
      
"Rare_Letter"
      
2
      
"Rare Category (Letter)"
    
    

      
2
      
9
      
"Corr_Resp"
      
[]
      
""
    
    

      
3
      
8
      
"Err_Resp"
      
[]
      
""
    
  

In [10]:

    

with open(eventfile, 'r') as infile:
    data = infile.read()


    

In [12]:

    

print(data)


    

    




   22 "Frequent_Digit"     1 "Frequent Category (Digit)"
   12    "Rare_Letter"     2 "Rare Category (Letter)"
    9      "Corr_Resp"    []                   ""
    8      "Err_Resp"    []                   ""

In [23]:

    

print(data.replace(' ', chr(0x2610)))


    

    




☐☐☐22☐"Frequent_Digit"☐☐☐☐☐1☐"Frequent☐Category☐(Digit)"
☐☐☐12☐☐☐☐"Rare_Letter"☐☐☐☐☐2☐"Rare☐Category☐(Letter)"
☐☐☐☐9☐☐☐☐☐☐"Corr_Resp"☐☐☐☐[]☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐""
☐☐☐☐8☐☐☐☐☐☐"Err_Resp"☐☐☐☐[]☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐☐""

In [22]:

    

chr(0x25a1)


    

    
Out[22]:





'□'

In [24]:

    

from tabulate import tabulate

def to_fwf(df, fname):
    content = tabulate(df.values.tolist(), list(df.columns), tablefmt="plain")
    open(fname, "w").write(content)


    

In [26]:

    

to_fwf(event_mapping, path +'test_event.txt')


    

In [ ]: