Say goodbye to messy datasets! This project uses Python to clean and transform disorganized electricity tariff data, tackling issues like inconsistent date formats and unwanted characters. With Power BI, the cleaned data comes to life through dynamic visualizations, offering actionable insights at a glance.
Highlights:
Used Python’s pandas to clean extra spaces, underscores, and invalid dates
Parsed and standardized date columns for seamless analysis
Removed unnecessary suffixes (st, nd, th) to enhance consistency
Created compelling Power BI dashboards to visualize key trends and metrics
Unlock the power of Python and Power BI for efficient data cleaning and impactful storytelling! 🚀
Refine your keyword strategy with this project! Using SQL, we cleaned, transformed, and categorized keyword data, ensuring only the most relevant terms are considered for marketing and SEO campaigns. By removing noise and focusing on actionable metrics, this workflow streamlines decision-making and enhances results.
Highlights:
Filtered out keywords with insufficient search volume (NULL or 0 values) to focus on impactful terms
Replaced missing competition values with 0 for better data continuity
Joined tables to enrich keywords with estimated CTR and click data
Categorized keywords into actionable groups to simplify campaign targeting
Supercharge your SEO strategy with clean, categorized data and better insights into search behavior! 🚀
Cleaning electricity tariff data has never been easier! This project tackles disorganized date columns head-on, using SQL to transform inconsistent formats into structured, actionable data. From removing clutter to extracting and standardizing key components, SQL shines as the ultimate tool for data preparation.
Highlights:
Eliminated extra spaces and underscores for cleaner records
Extracted and standardized dates with SUBSTRING() and CHARINDEX()
Removed unwanted suffixes like st, nd, and th for consistency
Streamlined datasets by dropping redundant columns
Transform raw, chaotic data into polished insights with SQL! Perfect for data professionals looking to enhance their preprocessing game. 🚀