Path srt correction

[mfardm]

The function does not work on every system. I updated the path variables to str and the issue is solved.
Please refer updated main function in below

`import os
import re
import math
import pandas as pd
from functools import reduce
from pathlib import PurePath

def PSCADVar(path, file_name, del_out = False):
''' Function which will compile all the .out files exported by PSCAD in a .csv file '''

# create the extensions that will be used on the code
inf_ex = '.inf'   
out_ex = '.out'
csv_ex = '.csv'
path= r"C:\Projects\Python\PSCAD_Channel"
file_name= 'Why_680RC2_IVF_RAPC227_52511_1'

INF_path = str(PurePath(path, file_name + inf_ex)) # create path for the .inf file, which has the header

with open(INF_path) as myfile:             # Open all the lines in the inf path
    lines = myfile.readlines()
    n_col = 11                                 # Number of columns that the txt has
    n_var = len(lines)                         # Number of PSCAD Variables
    n_files = int(math.ceil(n_var / 10.0))     # Number of .out Files exported (the floating is important)
    n_var_tot = n_var + n_files                # Number of variables INCLUDING additional time column FOR EACH .OUT
    n_var_last = n_var_tot -(n_files-1)*n_col  # Number of variables in the last file

# Create list to store the number of columns of each file
    last_col = [0]*n_files

    for file_ in range(0,n_files):     

        numb_columns = n_col if file_ != n_files-1 else n_var_last
    
        last_col[file_] = numb_columns

    pattern = "Desc=\"(.*?)\""  # Patter that holds the variable name
    header  = [0]*(n_var_tot)  

    b = 0  # to "freeze" the time when storing the "TIME"
    c = 1  # used in the index: from 1 to 11

    # "For" Logic: each file can take 11 variables, and the first one is TIME
    # so this "for" writes time if it is the time column, or takes the header from
    # the array "header"
for var in range(0, n_var_tot):
    
        if  ((var == 0) | (var % 11 == 0)): # if it is the first value of all files, store the time name
            header[var] = 'time'            # to the object outside
            b = b - 1
            if var != 0:
                c = 1
        else:
            header[var] = re.search(pattern, lines[b]).group(1)  
            header[var] = header[var].replace(" ", "_")  
        
        b = b + 1
        c = c + 1

############################################################################
    # Take all the paths of the .out files
    ############################################################################

OUT_name  = [0] * n_files
OUT_path  = [0] * n_files

for ii in range(0, n_files):
    if (ii < 9):
        OUT_name[ii] = "_0" + str(ii + 1) + out_ex               # Create ending "_0ii".out
    else:
        OUT_name[ii] = "_" + str(ii + 1) + out_ex                # Create ending "_ii".out

    OUT_path[ii] = PurePath(path, file_name + OUT_name[ii])  # replace in INF_path the.inf for the new end

    # Creates the path of the .CSV that's gonna be writen
CSV_path = PurePath(path, file_name + csv_ex) # Replaces the ending .inf with .csv

########################################################
### Treat the data
########################################################

# Create an empty list to store all of the pandas dataframes
dff = []

# Read all of the .out files and append them to the empty list
for path in OUT_path:
    dff.append(pd.read_csv(str(path), delim_whitespace = True, header = None))

    if del_out:
        os.remove(path)

# Create auxiliar variables
ii = 0
jj = 0

# Rename the header of each file (which is now 0,1,2,3,4...) for the names that are storage at the variable header
for file_ in range(0, n_files):
    for ii in range(0, last_col[file_]):
        dff[file_].rename(columns = {ii:header[ii + jj]}, inplace = True)
    jj = jj + 11

# Now that the headers are done, merge all of them (2 by 2) using the column 'time' as reference
df_merged = reduce(lambda  left, right: pd.merge(left, right, on = 'time'), dff)

# Storage all the dataframe into one csv file with header
df_merged.to_csv(str(CSV_path), index = False)    

`

[LuisArthurNH]

Hey mfardm, I can see the change you have made. Which operating system are you using?

[mfardm]

Hey mfardm, I can see the change you have made. Which operating system are you using?

Hey Luis,

It is Windows 64bit with Python2.7. Most likely you are using Python 3 and above. Those modification is going to make it compatible with both.

Regards,
Majid