{ "cells": [ { "cell_type": "markdown", "id": "15535787-de37-47fe-9231-d20ba3e8ce45", "metadata": {}, "source": [ "# TUTORIAL" ] }, { "cell_type": "markdown", "id": "f62541d9-3e6a-445c-b1e9-a7eae2e8eb5c", "metadata": { "tags": [] }, "source": [ "# Example use-cases of this Text-Fabric dataset\n", "\n", "The following are several use-case examples that demonstrate the utilization of the Text-Fabric dataset, While Text-Fabric, which is implemented as a Python package, can be employed in any stand-alone Python script, it is commonly utilized from within a [Jupyter Notebook](https://jupyter.org) — an interactive web-based computational environment enabling users to create and share documents with live code, visualizations, and text, thus facilitating the inclusion of explanatory notes alongside queries and results obtained from Text-Fabric. The Notebooks are grouped into specific focus areas and topics, albeit somewhat arbitrarily.\n", "\n", "**Please note that some of these notebooks are still under development.**\n", "\n", "## Basic / general\n", "\n", "* [Load Text-Fabric in Jupyter notebook](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/tutorial/usecases/load_text_fabric.ipynb)\n", "* [Print a specific verse](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/print_verse.ipynb)\n", "* [Some system statistics](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/Some_system_statistics.ipynb)\n", "* [Some corpus statistics](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/Some_corpus_statistics.ipynb)\n", "* [Various text formats](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/tutorial/usecases/various_text_formats.ipynb)\n", "\n", "## Grammatical\n", "\n", "* [The particles μέν and δέ](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/particles_men_and_de.ipynb)\n", "* [The use of μονογενής](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/use_of_monogenes.ipynb)\n", "* [The use of προσκυνέω](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/use_of_proskyneo.ipynb)\n", "* [Incongruenct adverb and noun](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/tutorial/usecases/incongruent_adverb_noun.ipynb)\n", "* [Pronominal redundancy](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/pronominal_redundancy.ipynb)\n", "\n", "## Syntactical \n", "\n", "* [Genitive objectivus or subjectivus](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/genitive_objectivus_or_subjectivus.ipynb)\n", "* [The Granville Sharp rule](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/tutorial/usecases/Granville_Sharp_rule.ipynb)\n", "* [Articulated proper nouns](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/tutorial/usecases/articulated_proper_nouns.ipynb)\n", "* [Constituents order and phrase structure](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/constituents_order_and_phrase_structure.ipynb)\n", "* [Repetition of nouns](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/repetition_of_nouns.ipynb)\n", "* [Appositions](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/appositions.ipynb)\n", "* [Speaking to objects](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/main/tutorial/find_objects.ipynb)\n", "\n", "## Advanced\n", " \n", "* [Advanced search options](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/tutorial/usecases/advanced_search_options.ipynb)\n", "* [Data is interpretation](https://nbviewer.org/github/tonyjurg/Nestle1904LFT/blob/tutorial/usecases/interpretation.ipynb)\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 5 }