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Need a push to start with a function about text files, I can't figure this out on my own

I don't need the entire code but I want a push to help me on the way, I've been searching on the internet for clues on how to start to write a function like this but I haven't gotten any further then just the name of the function.
So I haven't got the slightest clue on how to start with this, I don't know how to work with text files. Any tips?

These text files are CSV (Comma Separated Values). It is a simple file format used to store tabular data.
You may explore Python's inbuilt module called csv.
Following code snippet an example to load .csv file in Python:
import csv
filename = 'us_population.csv'
with open(filename, 'r') as csvfile:
csvreader = csv.reader(csvfile)

How to read Json files in a directory separately with a for loop and performing a calculation

Update: Sorry it seems my question wasn't asked properly. So I am analyzing a transportation network consisting of more than 5000 links. All the data included in a big CSV file. I have several JSON files which each consist of subset of this network. I am trying to loop through all the JSON files INDIVIDUALLY (i.e. not trying to concatenate or something), read the JSON file, extract the information from the CVS file, perform calculation, and save the information along with the name of file in new dataframe. Something like this:
enter image description here
This is the code I wrote, but not sure if it's efficient enough.
name=[]
percent_of_truck=[]
path_to_json = \\directory
import glob
z= glob.glob(os.path.join(path_to_json, '*.json'))
for i in z:
with open(i, 'r') as myfile:
l=json.load(myfile)
name.append(i)
d_2019= final.loc[final['LINK_ID'].isin(l)] #retreive data from main CSV file
avg_m=(d_2019['AADTT16']/d_2019['AADT16']*d_2019['Length']).sum()/d_2019['Length'].sum() #calculation
percent_of_truck.append(avg_m)
f=pd.DataFrame()
f['Name']=name
f['% of truck']=percent_of_truck

I'm assuming here you just want a dictionary of all the JSON. If so, use the JSON library ( import JSON). If so, this code may be of use:
import json
def importSomeJSONFile(f):
return json.load(open(f))
# make sure the file exists in the same directory
example = importSomeJSONFile("example.json")
print(example)
#access a value within this , replacing key with what you want like "name"
print(JSON_imported[key])

Since you haven't added any Schema or any other specific requirements.
You can follow this approach to solve your problem, in any language you prefer
Get Directory of the JsonFiles, which needs to be read
Get List of all files present in directory
For each file-name returned in Step2.
Read File
Parse Json from String
Perform required calculation

Pandas to understand inconsistent seperator for csv files

Depending on the regional settings the csv file exported from excel may be different thus giving me error in my script. Therefore i m thinking what is the best way to fix this issue.
Does anyone knows how to achieve that?

I ended up using the following snippet:
import csv
sniffer = csv.Sniffer()
sample_bytes = 32
dialect = sniffer.sniff(open("semicolons.csv").read(sample_bytes))
print dialect.delimiter
source: https://www.kite.com/python/examples/3323/csv-sniff-a-sample-of-a-csv-file-to-determine-its-dialect

How to rename files and change the file type as well?

I have a list with .dbf files which I want to change to .csv files. By hand I open them in excel and re-save them as .csv, but this takes too much time.
Now I made a script which changes the file name, but when I open it, it is still a .dbf file type (although it is called .csv). How can I rename the files in such a way that the file type also changes?
My script uses (the dbf and csv file name are listed in a seperate csv file):
IN = dbffile name
OUT = csvfile name
for output_line in lstRename:
shutil.copyfile(IN,OUT)

Changing the name of a file (and the extension is just part of the complete name) has absolutely no effect on the contents of the file. You need to somehow convert the contents from one format to the other.
Using my dbf module and python it is quite simple:
import dbf
IN = 'some_file.dbf'
OUT = 'new_name.csv'
dbf.Table(IN).export(filename=OUT)
This will create a .csv file that is actually in csv format.

If you have ever used VB or looked into VBA, you can write a simple excel script to open each file, save it as csv and then save it with a new name.
Use the macro recorder to record you once doing it yourself and then edit the resulting script.
I have now created a application that automates this. Its called xlsto (look for the xls.exe release file). It allows you to pick a folder and convert all xls files to csv (or any other type).

You need a converter
Search for dbf2csv in google.

It depends what you want to do. It seems like you want to convert files to other types. There are many converters out there, but a computer alone doesn't know every file type. For that you will need to download some software. If all you want to do is change the file extension,
(ex. .png, .doc, .wav) then you can set your computer to be able to change both the name and the extension. I hoped I helped in some way :)

descargar libreria dbfpy desde http://sourceforge.net/projects/dbfpy/?source=dlp
import csv,glob
from dbfpy import dbf
entrada = raw_input(" entresucarpetadbf ::")
lisDbf = glob.glob(entrada + "\\*dbf")
for db in lisDbf:
print db
try:
dbfFile = dbf.Dbf(open(db,'r'))
csvFile = csv.writer(open(db[:-3] + "csv", 'wb'))
headers = range(len(dbfFile.fieldNames))
allRows = []
for row in dbfFile:
rows = []
for num in headers:
rows.append(row[num])
allRows.append(rows)
csvFile.writerow(dbfFile.fieldNames)
for row in allRows:
print row
csvFile.writerow(row)
except Exception,e:
print e

It might be that the new file name is "xzy.csv.dbf". Usually in C# I put quotes in the filename. This forces the OS to change the filename. Try something like "Xzy.csv" in quotes.

Get the inputs from Excel and use those inputs in python script

How to get the inputs from excel and use those inputs in python.

Take a look at xlrd
This is the best reference I found for learning how to use it: http://www.dev-explorer.com/articles/excel-spreadsheets-and-python

Not sure if this is exactly what you're talking about, but:
If you have a very simple excel file (i.e. basically just one table filled with string-values, nothing fancy), and all you want to do is basic processing, then I'd suggest just converting it to a csv (comma-seperated value file). This can be done by "saving as..." in excel and selecting csv.
This is just a file with the same data as the excel, except represented by lines seperated with commas:
cell A:1, cell A:2, cell A:3
cell B:1, cell B:2, cell b:3
This is then very easy to parse using standard python functions (i.e., readlines to get each line of the file, then it's just a list that you can split on ",").
This if of course only helpful in some situations, like when you get a log from a program and want to quickly run a python script which handles it.
Note: As was pointed out in the comments, splitting the string on "," is actually not very good, since you run into all sorts of problems. Better to use the csv module (which another answer here teaches how to use).

import win32com
Excel=win32com.client.Dispatch("Excel.Application")
Excel.Workbooks.Open(file path)
Cells=Excel.ActiveWorkBook.ActiveSheet.Cells
Cells(row,column).Value=Input
Output=Cells(row,column).Value

If you can save as a csv file with headers:
Attrib1, Attrib2, Attrib3
value1.1, value1.2, value1.3
value2,1,...
Then I would highly recommend looking at built-in the csv module
With that you can do things like:
csvFile = csv.DictReader(open("csvFile.csv", "r"))
for row in csvFile:
print row['Attrib1'], row['Attrib2']