Gist 6ab67c7133edab5b3b01760a3f226a25

100%

Gist 6ab67c7133edab5b3b01760a3f226a25

✓ Published0🌍 Public

Last edited Feb 22, 2024

Created on Feb 22, 2024

This example compares the frequency of uppercase letters in the King James and Luther Bibles, printing a percentage of all uppercase letters per book. Using Python’s `re` module with custom regular expressions, it filters out lines with fewer than four words, skips verses’ opening formatting, and excludes all-uppercase words before counting letters. The output reports each translation’s uppercase share, revealing stylistic differences in capitalization. The script reads local text files (`kjv.txt`, `luther.txt`) and computes letter counts via `matchLetters` and `matchUCLetters` patterns.

AI-generated description

Similar vizzes

Loading thumbnail…

JS Bin

This example counts character frequency in a long string of text and outputs a sorted array of characters with their occurrence counts. The code uses JavaScript's `reduce` method to build a frequency object, then sorts the result in descending order using a custom `compareNumbers` function. The data source is a hardcoded string of lowercase letters and underscores. The final output is logged to the console via `console.log`, showing the sorted array in descending order by frequency.

JJn1532

50% match

Loading thumbnail…

Adapted from https://github.com/akleemans/letter-frequency

A comparative visualization of letter frequencies across 16 languages, shown as an interactive network of letters and language nodes. The visualization uses `d3.forceSimulation` to position nodes, with link widths encoding frequency values from the CSV dataset. Hovering highlights a selected language or letter, revealing its frequency distribution across connected nodes. The code accesses the raw CSV data and applies force-directed layout to cluster related letters and languages, making cross-linguistic similarities and differences visually apparent.

CCliffordAnderson

49% match

Loading thumbnail…

Custom Texts

This example presents custom keyboard-practice word lists for MonkeyType, organized by language and focus area. The lists include English and German texts targeting specific letters, hand usage, dates, or frequently mistyped words. The visualization shows the raw text file contents as plain, concatenated strings. A shell script (update-toc.sh) generates the table of contents by parsing filenames with grep and sed, while the included Python script (word-type-test.py) demonstrates a typing-speed game using termios and tty for character input.

BBastiTee

48% match

Loading thumbnail…

Gist 9d6f5a0980393c12aca5243aae8947e0

This example demonstrates how to modify font attributes for a selected range of text within a Sketch document using the Sketch JavaScript API. It applies small-caps styling by accessing the text layer’s editing delegate and text storage, then constructs an `NSFontFeatureSettingsAttribute` dictionary to adjust the font descriptor. The code specifically uses `NSFontFeatureTypeIdentifierKey` and `NSFontFeatureSelectorIdentifierKey` for the `kLowerCaseType` and `kLowerCaseSmallCapsSelector` settings, then creates a new `NSFont` with `NSFontDescriptor` and applies it to the selected range via `addAttributes:range:`.

KKevinGutowski

48% match

Loading thumbnail…

A solution to a codefights daily puzzle that was amusing and might be useful to reference

This example demonstrates a Python solution to a Codefights puzzle that decompresses a run-length encoded string, sorts its letters, and returns the kth character. The visualization shows how the algorithm groups identical letters using `itertools.groupby` and `sorted`, then aggregates their counts with `sum`. It uses `re.findall` to parse letter-number pairs and a pairwise iteration to handle adjacent matches. The code returns -1 for invalid inputs or when k exceeds the total character count, illustrating a compact approach to string compression challenges.

BBBischof

47% match

Loading thumbnail…

Knuth/McIlroy word count task using Haskell

This example demonstrates a word-frequency analysis task using Haskell, showing how to compute and display the most common words from standard input. It chains data transformations through a pipeline: converting text to lowercase, replacing non-letter characters with newlines, splitting into words, and tallying counts with a hash map. The code relies on `Data.HashMap.Strict` for efficient key-value aggregation via `HashMap.fromListWith`, and uses `Data.List` for sorting and taking the top *n* results. The final output lists each word with its count, sorted in descending order of frequency. The example highlights functional composition and lazy evaluation in a concise, read-backwards data-flow style.

FFranklin Chen

47% match

Loading thumbnail…

Example from Programming4Humanists

This example visualizes word frequency in a text by processing the poem’s lines and filtering out common stopwords. It shows a ranked list of words by their occurrence count, displayed in descending order. The code uses XQuery 3.0 with functions like `fn:tokenize`, `fn:distinct-values`, and `fn:count` to compute frequencies, while reading the source text and stopword list from gist URLs. The rendering approach is a simple textual output of word elements, each carrying a `frequency` attribute, rather than a graphical chart.

CCliffordAnderson

47% match

Loading thumbnail…

Letter Count Bar Chart

This interactive bar chart visualizes the frequency of each letter in a text file, updating live as the user types in a textarea. The chart loads Peter Piper’s tongue twister asynchronously via `d3.text`, counts characters with JavaScript, and renders SVG rectangles using `d3.scaleLinear` and `d3.scaleBand`. Axes are drawn with `d3.axisBottom` and `d3.axisRight`, and the chart animates with D3’s enter/update/exit pattern on each `keyup` event.

115Dkatz

46% match