{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Example usage\n",
                "\n",
                "Here we will demonstrate how to use pycounts to count the words in a text file and plot the top 5 results.\n",
                "\n",
                "## Imports"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "import pycounts_tt25\n",
                "from matplotlib import pyplot as plt"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Create a text file\n",
                "\n",
                "We'll first create a text file to work with using a famous quote from Einstein:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "quote = \"Insanity is doing the same thing over and over and expecting different results.\"\n",
                "with open(\"einstein.txt\", \"w\") as file:\n",
                "    file.write(quote)\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Count words\n",
                "\n",
                "We can count the words in our text file using the `count_words()`` function. Note that this function removes punctuation and makes all words lowercase before counting."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "counts = pycounts_tt25.count_words(\"einstein.txt\")\n",
                "print(counts)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Plot words\n",
                "\n",
                "We can now plot the result using the plot_words() function:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": [
                "fig = pycounts_tt25.plot_words(counts, n=5)"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3",
            "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": "3.8.5"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 4
}