Upload a CSV file and instantly get count, mean, median, standard deviation, min, and max for every numeric column.
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Supports single file (.csv,text/csv)
Upload or paste a CSV file to begin.
Compute the Pearson correlation coefficient between every pair of numeric columns in a CSV file.
Visualize the distribution of any numeric column from a CSV file as an adjustable-bin histogram.
Generate a box-and-whisker plot showing the five-number summary and outliers for each numeric column in a CSV file.
Plot any two numeric columns from a CSV file against each other, with the Pearson correlation coefficient shown alongside.
Convert code between 40+ programming languages — Python, JavaScript, Java, C++, Go, Rust, and more. Private, browser-based.
Verify if two MD5/SHA256 signature hashes match side-by-side.
Calculate password bit-entropy and verify characters strength parameters.
Encode or decode strings using ROT13, Caesar, and Vigenere ciphers.
Parses a CSV file (using a robust CSV parser that correctly handles quoted fields and embedded commas, not naive comma-splitting) and computes standard descriptive statistics for every numeric column automatically — no manual column selection or spreadsheet formulas required.
A column is treated as numeric if at least half its values parse as numbers, tolerating a reasonable number of missing or non-numeric entries without excluding an otherwise-numeric column.
Before modeling or drawing conclusions, a handful of summary statistics catch most of the obvious problems and surprises in a new dataset.
Under RFC 4180, fields containing commas, double quotes or line breaks should be enclosed in double quotes, with inner quotes doubled. Why naive splitting breaks.
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