From 85df221a795b02bdd985f3f3a3491b5bda0beb83 Mon Sep 17 00:00:00 2001 From: Ian Culp <57159226+icculp@users.noreply.github.com> Date: Fri, 11 Jun 2021 21:27:53 -0500 Subject: [PATCH] removing np import, re-running output --- word_count.ipynb | 35 +++++++++++++++++------------------ 1 file changed, 17 insertions(+), 18 deletions(-) diff --git a/word_count.ipynb b/word_count.ipynb index 7a19a21..7722901 100644 --- a/word_count.ipynb +++ b/word_count.ipynb @@ -5,7 +5,7 @@ "colab": { "name": "Untitled25.ipynb", "provenance": [], - "authorship_tag": "ABX9TyOJqhnf6/YgfQMx6pfh6Fth", + "authorship_tag": "ABX9TyMioTaWOtZ3dcIebltCT4IN", "include_colab_link": true }, "kernelspec": { @@ -33,11 +33,10 @@ "id": "kT4wyWuy2szs" }, "source": [ - "import numpy as np\n", "import os\n", "import pandas as pd" ], - "execution_count": 7, + "execution_count": 1, "outputs": [] }, { @@ -47,7 +46,7 @@ "base_uri": "https://localhost:8080/" }, "id": "9J62Uh4H2Y9g", - "outputId": "f4147b98-f72a-4ad2-8b5b-c3bb9f0c86db" + "outputId": "0ac3147d-fdb4-4b9c-d96b-4da334730a93" }, "source": [ "!git clone https://github.com/icculp/Learning-Bitcoin-from-the-Command-Line.git" @@ -58,12 +57,12 @@ "output_type": "stream", "text": [ "Cloning into 'Learning-Bitcoin-from-the-Command-Line'...\n", - "remote: Enumerating objects: 6634, done.\u001b[K\n", - "remote: Counting objects: 100% (238/238), done.\u001b[K\n", - "remote: Compressing objects: 100% (196/196), done.\u001b[K\n", - "remote: Total 6634 (delta 109), reused 82 (delta 42), pack-reused 6396\u001b[K\n", - "Receiving objects: 100% (6634/6634), 7.53 MiB | 13.87 MiB/s, done.\n", - "Resolving deltas: 100% (4068/4068), done.\n" + "remote: Enumerating objects: 6637, done.\u001b[K\n", + "remote: Counting objects: 100% (241/241), done.\u001b[K\n", + "remote: Compressing objects: 100% (199/199), done.\u001b[K\n", + "remote: Total 6637 (delta 110), reused 82 (delta 42), pack-reused 6396\u001b[K\n", + "Receiving objects: 100% (6637/6637), 7.53 MiB | 18.46 MiB/s, done.\n", + "Resolving deltas: 100% (4069/4069), done.\n" ], "name": "stdout" } @@ -103,7 +102,7 @@ " # print(chapter, count)\n", " return pd.DataFrame(counts, columns=columns)" ], - "execution_count": 35, + "execution_count": 3, "outputs": [] }, { @@ -115,7 +114,7 @@ "chapter_word_counts = count_words()\n", "chapter_word_counts.sort_values(by=['Chapter'], inplace=True)" ], - "execution_count": 38, + "execution_count": 4, "outputs": [] }, { @@ -126,13 +125,13 @@ "height": 631 }, "id": "IPkG4oQJ6f1e", - "outputId": "d057cf19-4d40-477a-964c-d2b6154e1e73" + "outputId": "eea2f4b6-c3d3-48b5-dc62-97885c18d48d" }, "source": [ "from google.colab import data_table\n", "data_table.DataTable(chapter_word_counts, include_index=False)" ], - "execution_count": 39, + "execution_count": 5, "outputs": [ { "output_type": "execute_result", @@ -229,7 +228,7 @@ "metadata": { "tags": [] }, - "execution_count": 39 + "execution_count": 5 } ] }, @@ -240,13 +239,13 @@ "base_uri": "https://localhost:8080/" }, "id": "4dFD792BBy0S", - "outputId": "945da188-2d3b-4061-8f23-08e39e6f97f4" + "outputId": "3c4dc4ff-ceb3-4ff5-d40d-c606eec83a8c" }, "source": [ "total_count = chapter_word_counts['Word Count'].sum()\n", "total_count" ], - "execution_count": 44, + "execution_count": 6, "outputs": [ { "output_type": "execute_result", @@ -258,7 +257,7 @@ "metadata": { "tags": [] }, - "execution_count": 44 + "execution_count": 6 } ] }