# Reading a TXT File with Double Quotes 
import pandas as pd

# Sample data in a TXT file (sample.txt)
# "Name";"Age";"City"
# "Alice";"25";"New York"
# "Bob";"30";"Los Angeles"
# "Charlie";"35";"Chicago"

df = pd.read_csv('sample1.txt', sep=';', quotechar='"') #, skiprows=1
print(df)

# Reading a TXT File 
import pandas as pd

# Sample data in a TXT file (sample.txt)
# This is a header line to be ignored
# "Name","Age","City"
# "Alice","25","New York"
# "Bob","30","Los Angeles"
# "Charlie","35","Chicago"

df = pd.read_csv('sample2.txt', sep=',', quotechar='"') #, skiprows=1
df = pd.read_csv('sample3.txt', sep='|', quotechar='"')
print(df)

# Reading a TXT File with Custom Separator and Double Quotes
import pandas as pd

# Sample data in a TXT file (sample.txt)
# "Name"|"Age"|"City"
# "Alice"|"25"|"New York"
# "Bob"|"30"|"Los Angeles"
# "Charlie"|"35"|"Chicago"

# Reading the TXT file with a custom separator
df = pd.read_csv('sample3.txt', sep='|', quotechar='"')

# Display the DataFrame
print(df)

# Processing a Large Text File Line by Line
def process_line(line):
    # Here you can add your logic to process each line
    print(line.strip())  # For demonstration, just print the line

#with open('large_file.txt', 'r') as file:    
with open('sample3.txt', 'r') as file:
    # Iterate through each line in the file
    for line in file:
        process_line(line)

# Handling Different Separators and Ignoring the First Line
def process_fields(fields):
    # Here you can add your logic to process each field
    print(fields)  # For demonstration, just print the fields

#with open('large_file.txt', 'r') as file:    
with open('sample2.txt', 'r') as file:
    # Skip the first line (header)
    next(file)
    for line in file:
        # Split the line by a specific separator (e.g., comma, semicolon)
        fields = line.strip().split(';')
        process_fields(fields)

# Using csv Module for More Complex Parsing
import csv

def process_row(row):
    # Here you can add your logic to process each row
    print(row)  # For demonstration, just print the row

#with open('large_file.txt', 'r') as file:    
with open('sample2.txt', 'r') as file:
    reader = csv.reader(file, delimiter=';', quotechar='"')
    for row in reader:
        process_row(row)