Data Cleaner is a Streamlit-based application designed to provide users with a convenient interface for cleaning and processing tabular data files (CSV, XLS, XLSX). This application allows users to perform various data cleaning operations easily.

Clone this repository to your local machine.

https://github.com/SiddhantDembi/Data-Cleaning.git

Install the required dependencies using

pip install -r requirements.txt

Run the Streamlit application locally using

streamlit run data.py

or

python -m streamlit run data.py

• Replace Null Values: Replace missing (null) values with a custom value.
• Remove Duplicate Rows: Eliminate duplicate rows from the dataset.
• Remove Missing Values: Remove rows containing missing values.
• Convert to Lowercase: Convert text columns to lowercase.
• Delete Columns: Select and delete specific columns from the dataset.
• Sort Column: Sort a column in ascending or descending order based on lexicographical order.
• Capitalize Columns: Capitalize the first letter of elements in selected columns.

1. Upload File: Upload an Excel (XLS, XLSX) or CSV file.
2. Select Sheet (for Excel files): If uploading an Excel file, select the sheet you want to clean.
3. Choose Cleaning Options: Select the cleaning options you want to apply to your data.
4. Download Cleaned File: Download the cleaned data in the same format as your input file or in CSV format.

To demonstrate the functionality of Data Cleaner, a sample CSV file (sample.csv) is provided. You can download the sample file by clicking the "Download Test Sample" button within the application.