Interactive 1.5*IQR Box & Whisker Plot Outlier Transformation and Detection (Upload Your Data)
Upload a CSV file containing a single column of numbers (no header, no symbols) Box & Whisker
Expected format: one number per line. Example:
• Logarithm uses natural log (ln), computed only for values > 0.
• Square Root is computed only for values ≥ 0.
• Power uses exponent 2 (x²), applied to all values.
12.490-3.1
• Logarithm uses natural log (ln), computed only for values > 0.
• Square Root is computed only for values ≥ 0.
• Power uses exponent 2 (x²), applied to all values.
Box & Whisker: Original
Box & Whisker: Logarithm (ln)
Box & Whisker: Power (x²)
Box & Whisker: Square Root
About This Tool
This tool generates four box‑and‑whisker plots to help you analyze outliers in your dataset. The first plot highlights any statistical outliers in your original column of numbers, using the 1.5×IQR Outlier Rule to flag values above the upper whisker or below the lower whisker. The next three box plots show how your data changes after applying common transformations: LOG, Power, and Square Root. By comparing all four visualizations, you can quickly identify which transformation reduces or removes outliers, making your data more consistent with the rest of your values. This is especially useful for preventing extreme values from distorting key descriptive statistics—such as the average—that are often used in KPI reporting.
