diff --git a/docs/index.md b/docs/index.md
index 82eb6c0..6404bc2 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,12 +1,12 @@
-# CSV-UTILS DOCUMENTATION
+# CSV-UTILITE DOCUMENTATION
 
-csv-util is a Python package designed to facilitate working with CSV files in a more convenient and Pythonic manner compared to the built-in csv module. It provides a set of modules with classes and functions to perform various tasks related to CSV file handling.
+csv-utilite is a Python package designed to facilitate working with CSV files in a more convenient and Pythonic manner compared to the built-in csv module. It provides a set of modules with classes and functions to perform various tasks related to CSV file handling.
 
 ## Installation
 
-You can install csv-util via pip:
+You can install csv-utilite via pip:
 
-```pip install csv-utils ```
+```pip install csv_utilite ```
 
 ## CORE MODULES
 
@@ -14,13 +14,13 @@ You can install csv-util via pip:
 
 This module contains the Reader class, which extends the functionality of csv.reader. It offers additional features such as automatic type casting, handling missing values, and support for different dialects.
 
-``` from csv_util.reader import Reader ```
+``` from csv_utilite import Reader ```
 
 ### Example usage
 ```python
-from csv_utils.reader import Reader 
+from csv_utilite import Reader 
 
-with open('kano.csv', 'r') as file:
+with open('myfile.csv', 'r') as file:
   reader = Reader(file, dialect='excel', type_cast=True, na_values=['', 'NULL'])
   for row in reader:
     print(row)  
@@ -32,11 +32,11 @@ with open('kano.csv', 'r') as file:
 
 The writer.py module includes the Writer class, a subclass of csv.writer, enhanced with features like automatic type casting and support for different dialects.
 
-``` from csv_util.writer import Writer ```
+``` from csv_utilite import Writer ```
  
 ### Example usage
 ```python
-from csv_utils.writer import Writer
+from csv_utilite import Writer
 with open('output.csv', 'w', newline='') as file:
     writer = Writer(file, dialect='excel', na_rep='NA')
     writer.writerow([1, 2.5, True, None, 'abc'])
@@ -50,19 +50,19 @@ with open('output.csv', 'w', newline='') as file:
 This module provides functions for common operations on CSV data, such as filtering rows, sorting, merging multiple files, and handling headers.
 
 
-``` from csv_util.manipulation import filter_rows, sort_rows ```
+``` from csv_utilite import filter_rows, sort_rows ```
 
 ### Example usage
 ```python
-from csv_utils.manipulation import filter_rows, sort_rows, merge_files  
+from csv_utilite import filter_rows, sort_rows, merge_files  
 # Filter rows
 data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
 filtered_data = filter_rows(data, lambda row: sum(row) > 10)
-print(filtered_data)  # Output: [[7, 8, 9]]
+print(filtered_data)  
 
 # Sort rows
 sorted_data = sort_rows(data, key=lambda row: row[1], reverse=True)
-print(sorted_data)  # Output: [[7, 8, 9], [4, 5, 6], [1, 2, 3]]
+print(sorted_data)  
 
 # Merge files
 file_paths = ['file1.csv', 'file2.csv', 'file3.csv']
@@ -76,28 +76,28 @@ merge_files(file_paths, output_path, dialect='excel', has_header=True)
 formatting.py includes functions for formatting CSV data, such as adding or removing quotes, handling newlines within fields, and customizing delimiters.
 
 
-``` from csv_util.formatting import add_quotes, remove_quotes ```
+``` from csv_utilite import add_quotes, remove_quotes ```
 
 ### Example usage
 
 ```python
 import csv
-from csv_utils.formating import quote_fields, remove_quotes, handle_newlines
+from csv_utilite import quote_fields, remove_quotes, handle_newlines
 
 # Quote fields
 data = [['Name', 'Age', 'City'], ['John', 25, 'New York'], ['Jane', 30, 'London, UK']]
 quoted_data = quote_fields(data, quoting=csv.QUOTE_NONNUMERIC)
-print(quoted_data)  # Output: [['Name', 'Age', '"London, UK"'], ['"John"', '25', '"New York"'], ['"Jane"', '30', '"London, UK"']]
+print(quoted_data)  
 
 # Remove quotes
 quoted_data = [['"Name"', '"Age"', '"City"'], ['"John"', '"25"', '"New York"'], ['"Jane"', '"30"', '"London, UK"']]
 unquoted_data = remove_quotes(quoted_data)
-print(unquoted_data)  # Output: [['Name', 'Age', 'City'], ['John', '25', 'New York'], ['Jane', '30', 'London, UK']]
+print(unquoted_data)  
 
 # Handle newlines
 data = [['Name', 'Address'], ['John', '123 Main St.\nNew York, NY'], ['Jane', 'Flat 5\nLondon, UK']]
 formatted_data = handle_newlines(data, replacement=' ')
-print(formatted_data)  # Output: [['Name', 'Address'], ['John', '123 Main St. New York, NY'], ['Jane', 'Flat 5 London, UK']]
+print(formatted_data) 
 
 ```
 
@@ -106,12 +106,12 @@ print(formatted_data)  # Output: [['Name', 'Address'], ['John', '123 Main St. Ne
 
 The validation.py module provides functions to validate CSV data against predefined rules or schemas, ensuring data integrity and consistency.
 
-``` from csv_util.validation import validate_schema ```
+``` from csv_utilite import validate_schema ```
 
 ### Example usage
 
 ```python
-from csv_utils.validation import validate_rows, validate_headers
+from csv_utilite import validate_rows, validate_headers
 # Validate rows
 data = [[1, 2, 3], [4, 'five', 6], [7, 8, 'nine']]
 validators = {
@@ -120,13 +120,13 @@ validators = {
     2: lambda x: isinstance(x, int) and x < 10
 }
 valid_data = validate_rows(data, validators)
-print(valid_data)  # Output: [[1, 2, 3], [7, 8, 'nine']]
+print(valid_data) 
 
 # Validate headers
 headers = ['Name', 'Age', 'City', 'Country']
 required_headers = ['Name', 'Age', 'City']
 is_valid = validate_headers(headers, required_headers)
-print(is_valid)  # Output: True
+print(is_valid) 
 
 ```
 
@@ -136,21 +136,22 @@ print(is_valid)  # Output: True
 This module contains functions to convert CSV data to and from other formats like JSON, Excel, SQL tables, etc.
 
 
-``` from csv_util.conversion import csv_to_json, json_to_csv ```
+``` from csv_utilite import csv_to_json, json_to_csv ```
 
 ### Example usage
 
-```pyhton 
-from csv_utils.conversion import csv_to_json, json_to_csv
+```python
+
+from csv_utilite import csv_to_json, json_to_csv
 # CSV to JSON
 data = [['Name', 'Age', 'City'], ['John', 25, 'New York'], ['Jane', 30, 'London']]
 json_data = csv_to_json(data[1:], headers=data[0], orient='records')
-print(json_data)  # Output: [{'Name': 'John', 'Age': 25, 'City': 'New York'}, {'Name': 'Jane', 'Age': 30, 'City': 'London'}]
+print(json_data)  
 
 # JSON to CSV
 json_data = [{'Name': 'John', 'Age': 25, 'City': 'New York'}, {'Name': 'Jane', 'Age': 30, 'City': 'London'}]
 csv_data = json_to_csv(json_data, headers=['Name', 'Age', 'City'])
-print(csv_data)  # Output: [['Name', 'Age', 'City'], ['John', 25, 'New York'], ['Jane', 30, 'London']]
+print(csv_data)  
 
 ```
 
@@ -159,15 +160,15 @@ print(csv_data)  # Output: [['Name', 'Age', 'City'], ['John', 25, 'New York'], [
 The generation.py module includes functions to generate CSV files from various data sources, such as dictionaries, databases, or APIs.
 
 
-from csv_util.generation import generate_from_dict
+``` from csv_utilite import generate_from_dict ```
 
 # Example usage
 
-``` from csv_utils.generation import generate_from_db, generate_from_dict ```
+``` from csv_utilite import generate_from_db, generate_from_dict ```
 
 ```python
 
-from csv_utils.generation import generate_from_db, generate_from_dict
+from csv_utilite import generate_from_db, generate_from_dict
 
 # Generate CSV from a dictionary
 data = {'Name': 'John', 'Age': 25, 'City': 'New York'}
@@ -187,6 +188,11 @@ output_path = 'output.csv'
 generate_from_db(query, db_connection, output_path)
 
 ```
+## Contributions
+
+All meaningful contributions are welcome.
+
+We appreciate any improvements, bug fixes, or new features you can contribute to this project. Feel free to fork this repository, make your changes, and submit a pull request.
 
 # Conclusion
-csv-util simplifies CSV file handling in Python by providing a comprehensive set of classes and functions for reading, writing, manipulating, formatting, validating, converting, and generating CSV data. With its intuitive API and enhanced features, csv-util is a valuable tool for data processing tasks involving CSV files.
+csv-utilite simplifies CSV file handling in Python by providing a comprehensive set of classes and functions for reading, writing, manipulating, formatting, validating, converting, and generating CSV data. With its intuitive API and enhanced features, csv-utilite is a valuable tool for data processing tasks involving CSV files.