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StartUpHubTokyo Pythonプログラミング講座 模範解答 20210320
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# 現役高校教員が教えるPythonプログラミング講座" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## 代表的なショートカットコマンド(かっこ内はMAC)\n", | |
| "\n", | |
| "|操作内容\t|コマンド\t|\n", | |
| "|:-----------|:------------:|\n", | |
| "|セルを実行し、下のセルに移動する\t|Shift + Enter|\n", | |
| "|セルを実行する\t|Ctrl(?) + Enter|\n", | |
| "|セルを実行し、下にセルを追加する\t|Alt + Enter|\n", | |
| "|コメントアウト\t|Ctrl(?) + ／|\n", | |
| "|上にセルを追加する\t|Ctrl(?) + m -> a|\n", | |
| "|下にセルを追加する\t|Ctrl(?) + m -> b|\n", | |
| "|選択しているセルをカット\t|Ctrl(?) + m -> d|" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "### このセルの上にセルを追加してみよう。\n", | |
| "### このセルの下にセルを追加してみよう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## プログラムを実行してみよう" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "579" | |
| ] | |
| }, | |
| "execution_count": 2, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "123 + 456" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "56088" | |
| ] | |
| }, | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "123 * 456" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1000" | |
| ] | |
| }, | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "10 ** 3" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "579\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "print(123 +456)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Python\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "print(\"Python\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "1 + 1 = 2\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "print(\"1 + 1 =\", 1 + 1)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## 変数を使おう" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "文字式$x+5$について、$x$の値を変えて変化を見てみよう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "7" | |
| ] | |
| }, | |
| "execution_count": 8, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#x+5のxに2を代入する\n", | |
| "#イコールの左に変数を、イコールの右に代入したい数をかく\n", | |
| "x = 2\n", | |
| "\n", | |
| "x + 5" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "7" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#xにx+2を代入する。\n", | |
| "x = 5\n", | |
| "\n", | |
| "x = x + 2\n", | |
| "\n", | |
| "x" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "7" | |
| ] | |
| }, | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#xに2を足す。\n", | |
| "x = 5\n", | |
| "\n", | |
| "x += 2\n", | |
| "\n", | |
| "x" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "3" | |
| ] | |
| }, | |
| "execution_count": 11, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#xに2を引く。\n", | |
| "x = 5\n", | |
| "\n", | |
| "x -= 2\n", | |
| "\n", | |
| "x" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "'python'" | |
| ] | |
| }, | |
| "execution_count": 12, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#変数xに'py'を代入し、定数'thon'と連結する。\n", | |
| "x = 'py'\n", | |
| "\n", | |
| "x + 'thon'" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### 問題1\n", | |
| "次のとおりプログラムを書いてみよう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "あなたの誕生日の月をmに代入し、日をdに代入してください。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "m = 6\n", | |
| "d = 14" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "mを2倍して、さらに5を足した結果をmmに代入してください。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "mm = m * 2 + 5" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "mmに50をかけて、dを足し、さらに250を引いてください。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "614" | |
| ] | |
| }, | |
| "execution_count": 15, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "mm * 50 + d - 250" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "最後に出力された結果があなたの誕生日になっていれば、プログラムがうまく書けています。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## IF文" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "$n$が20以上であれば「成年」を表示しましょう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 16, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "成年\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# 「if」の後にはコロン「:」をつける。\n", | |
| "# 「if」の処理の中身の記述する際は、インデントをつける。\n", | |
| " \n", | |
| "n = 30\n", | |
| "\n", | |
| "if n >= 20:\n", | |
| " print(\"成年\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 17, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "# n = 15にしてみる。\n", | |
| " \n", | |
| "n = 15\n", | |
| "\n", | |
| "if n >= 20:\n", | |
| " print(\"成年\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "$n$が20以上であれば「成年」を表示し、そうでなければ「未成年」を表示しましょう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 18, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "成年\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# 「else」の後も「if」と同じように、コロン「:」やインデントをつける。\n", | |
| "\n", | |
| "n = 30\n", | |
| "\n", | |
| "if n >= 20:\n", | |
| " print(\"成年\")\n", | |
| "else:\n", | |
| " print(\"未成年\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "$n$が20未満であれば「未成年」を表示し、20であれば「はたち」と表示し、そうでなければ「成年」を表示しましょう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 19, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "未成年\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# nの値を変えて、何度か試してみましょう。\n", | |
| "\n", | |
| "n = 10\n", | |
| "\n", | |
| "if n < 20:\n", | |
| " print(\"未成年\")\n", | |
| "elif n == 20:\n", | |
| " print(\"はたち\")\n", | |
| "else:\n", | |
| " print(\"成年\")\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## FOR文" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "range(<数値>)の使い方" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 20, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "range(0, 10)" | |
| ] | |
| }, | |
| "execution_count": 20, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#range(10)で0から10までの範囲を作ることができる\n", | |
| "range(10)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 21, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "0\n", | |
| "1\n", | |
| "2\n", | |
| "3\n", | |
| "4\n", | |
| "5\n", | |
| "6\n", | |
| "7\n", | |
| "8\n", | |
| "9\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "#range(10)の範囲の中身は、0以上10未満の整数\n", | |
| "for n in range(10):\n", | |
| " print(n)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 22, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "range(1, 10)" | |
| ] | |
| }, | |
| "execution_count": 22, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#range(1, 10)で1から10までの範囲を作ることができる\n", | |
| "range(1, 10)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 23, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "1\n", | |
| "2\n", | |
| "3\n", | |
| "4\n", | |
| "5\n", | |
| "6\n", | |
| "7\n", | |
| "8\n", | |
| "9\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "#range(1, 10)の範囲の中身は、1以上10未満の整数\n", | |
| "for n in range(1, 10):\n", | |
| " print(n)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 24, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "range(1, 10, 2)" | |
| ] | |
| }, | |
| "execution_count": 24, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "#range(1,10,2)で、2ごとに増える1から10までの範囲を作ることができる\n", | |
| "range(1,10,2)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 25, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "1\n", | |
| "3\n", | |
| "5\n", | |
| "7\n", | |
| "9\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "#range(1,10)の範囲の中身は、2ごとに増える1以上10未満の整数\n", | |
| "for n in range(1,10,2):\n", | |
| " print(n)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### 問題2\n", | |
| "次のとおりプログラムを書いてみよう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "1から100までの奇数を表示しましょう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 26, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "1\n", | |
| "3\n", | |
| "5\n", | |
| "7\n", | |
| "9\n", | |
| "11\n", | |
| "13\n", | |
| "15\n", | |
| "17\n", | |
| "19\n", | |
| "21\n", | |
| "23\n", | |
| "25\n", | |
| "27\n", | |
| "29\n", | |
| "31\n", | |
| "33\n", | |
| "35\n", | |
| "37\n", | |
| "39\n", | |
| "41\n", | |
| "43\n", | |
| "45\n", | |
| "47\n", | |
| "49\n", | |
| "51\n", | |
| "53\n", | |
| "55\n", | |
| "57\n", | |
| "59\n", | |
| "61\n", | |
| "63\n", | |
| "65\n", | |
| "67\n", | |
| "69\n", | |
| "71\n", | |
| "73\n", | |
| "75\n", | |
| "77\n", | |
| "79\n", | |
| "81\n", | |
| "83\n", | |
| "85\n", | |
| "87\n", | |
| "89\n", | |
| "91\n", | |
| "93\n", | |
| "95\n", | |
| "97\n", | |
| "99\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "for i in range(1, 101, 2):\n", | |
| " print(i)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "1から100までの奇数のうち3の倍数のみを表示しましょう。<br>\n", | |
| "ヒント : 5 % 3 ・・・ 5を3で割った余りを算出(この場合は2)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 27, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "3\n", | |
| "9\n", | |
| "15\n", | |
| "21\n", | |
| "27\n", | |
| "33\n", | |
| "39\n", | |
| "45\n", | |
| "51\n", | |
| "57\n", | |
| "63\n", | |
| "69\n", | |
| "75\n", | |
| "81\n", | |
| "87\n", | |
| "93\n", | |
| "99\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "for i in range(1, 101, 2):\n", | |
| " if i % 3 == 0:\n", | |
| " print(i)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## <本日のメインテーマ>1%の確率であたるくじは、100回引けば1回はあたるのか!?" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### 1. 理論値をかんがえてみる。\n", | |
| "当たる確率は$\\frac{1}{100}$、\\\n", | |
| "はずれる確率は$\\frac{99}{100}$\\\n", | |
| "\\\n", | |
| "\\\n", | |
| "100回連続で外れる確率は、\\\n", | |
| "$\\frac{99}{100} \\times \\frac{99}{100} \\times \\frac{99}{100} \\times \\cdots = (\\frac{99}{100})^{100}$" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 28, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "0.3660323412732292" | |
| ] | |
| }, | |
| "execution_count": 28, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "p = (99 / 100) ** 100\n", | |
| "\n", | |
| "p" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "ということは、100回引いて1回以上は当たる確率は、1から上記の確率を引けばよい。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### 2.確率は、その事象が起こる場合と起こらない場合を足すと1になる。\n", | |
| "\\\n", | |
| "100回くじを引いて100回ともはずれる確率を上記の通り求めました。\\\n", | |
| "なので、1から上記確率pをひいた値が、100回くじを引いて少なくとも1回は当たる確率になります。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 29, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "0.6339676587267709" | |
| ] | |
| }, | |
| "execution_count": 29, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "1 - p" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## 理論値が本当に正しいのかシミュレーションしてみよう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "100回くじを引いて、当たりが1回以上出るかを確かめてみる。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 30, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "65" | |
| ] | |
| }, | |
| "execution_count": 30, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "# 1から100までの乱数を発生させる\n", | |
| "import random\n", | |
| "\n", | |
| "random.randint(1, 100)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 31, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "はずれ\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# 1から100のうち、1が当たり、2～100ははずれとします。\n", | |
| "\n", | |
| "i = random.randint(1, 100)\n", | |
| "\n", | |
| "if i == 1:\n", | |
| " print(\"当たり\")\n", | |
| "else:\n", | |
| " print(\"はずれ\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 32, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
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| "はずれ\n", | |
| "はずれ\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# 100回くじをひく\n", | |
| "\n", | |
| "for r in range(100):\n", | |
| " i = random.randint(1, 100)\n", | |
| "\n", | |
| " if i == 1:\n", | |
| " print(\"当たり\")\n", | |
| " else:\n", | |
| " print(\"はずれ\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 33, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
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| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n", | |
| "はずれ\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# 1回以上あたりが出るかをたしかめるだけなので、当たりが出たら処理を終わりにする。\n", | |
| "for r in range(100):\n", | |
| " i = random.randint(1, 100)\n", | |
| "\n", | |
| " if i == 1:\n", | |
| " print(\"当たり\")\n", | |
| " break # breakを使うと途中で処理を終える\n", | |
| " else:\n", | |
| " print(\"はずれ\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 34, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "試行回数 : 1000\n", | |
| "当たり : 626\n", | |
| "確率 : 0.626\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# 上記の処理を繰り返す回数を格納する変数\n", | |
| "lot = 1000\n", | |
| "\n", | |
| "\n", | |
| "# 当たりの回数を格納する変数 => 初期値0\n", | |
| "hit = 0\n", | |
| "\n", | |
| "\n", | |
| "\n", | |
| "# 1000回繰り返す\n", | |
| "for r in range(lot):\n", | |
| " \n", | |
| " # 100回試行する\n", | |
| " for i in range(100):\n", | |
| " p = random.randint(1, 100)\n", | |
| "\n", | |
| " # あたったらループをぬける\n", | |
| " if p == 1:\n", | |
| " hit += 1\n", | |
| " break # breakを使うと途中で処理を終える\n", | |
| " \n", | |
| "print(\"試行回数 : \", lot)\n", | |
| "print(\"当たり : \", hit)\n", | |
| "print(\"確率 : \", hit / lot)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "試行回数が増えると理論値に近づいていくことを確認してみよう。" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 35, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "試行回数 : 100\n", | |
| "確率 : 0.65\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 200\n", | |
| "確率 : 0.62\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 300\n", | |
| "確率 : 0.6033333333333334\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 400\n", | |
| "確率 : 0.6075\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 500\n", | |
| "確率 : 0.618\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 600\n", | |
| "確率 : 0.62\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 700\n", | |
| "確率 : 0.6257142857142857\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 800\n", | |
| "確率 : 0.61625\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 900\n", | |
| "確率 : 0.6088888888888889\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1000\n", | |
| "確率 : 0.615\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1100\n", | |
| "確率 : 0.610909090909091\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1200\n", | |
| "確率 : 0.6133333333333333\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1300\n", | |
| "確率 : 0.6169230769230769\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1400\n", | |
| "確率 : 0.62\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1500\n", | |
| "確率 : 0.6193333333333333\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1600\n", | |
| "確率 : 0.615\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1700\n", | |
| "確率 : 0.6147058823529412\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1800\n", | |
| "確率 : 0.6177777777777778\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 1900\n", | |
| "確率 : 0.6178947368421053\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2000\n", | |
| "確率 : 0.614\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2100\n", | |
| "確率 : 0.6138095238095238\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2200\n", | |
| "確率 : 0.6154545454545455\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2300\n", | |
| "確率 : 0.6117391304347826\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2400\n", | |
| "確率 : 0.6141666666666666\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2500\n", | |
| "確率 : 0.6152\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2600\n", | |
| "確率 : 0.6157692307692307\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2700\n", | |
| "確率 : 0.6174074074074074\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2800\n", | |
| "確率 : 0.6182142857142857\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 2900\n", | |
| "確率 : 0.6206896551724138\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3000\n", | |
| "確率 : 0.6206666666666667\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3100\n", | |
| "確率 : 0.6193548387096774\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3200\n", | |
| "確率 : 0.6175\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3300\n", | |
| "確率 : 0.6193939393939394\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3400\n", | |
| "確率 : 0.6208823529411764\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3500\n", | |
| "確率 : 0.6211428571428571\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3600\n", | |
| "確率 : 0.6208333333333333\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3700\n", | |
| "確率 : 0.6205405405405405\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3800\n", | |
| "確率 : 0.6210526315789474\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 3900\n", | |
| "確率 : 0.6207692307692307\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4000\n", | |
| "確率 : 0.62125\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4100\n", | |
| "確率 : 0.6219512195121951\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4200\n", | |
| "確率 : 0.6226190476190476\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4300\n", | |
| "確率 : 0.6248837209302326\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4400\n", | |
| "確率 : 0.6247727272727273\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4500\n", | |
| "確率 : 0.6255555555555555\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4600\n", | |
| "確率 : 0.6278260869565218\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4700\n", | |
| "確率 : 0.6291489361702127\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4800\n", | |
| "確率 : 0.6295833333333334\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 4900\n", | |
| "確率 : 0.6285714285714286\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5000\n", | |
| "確率 : 0.628\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5100\n", | |
| "確率 : 0.6278431372549019\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5200\n", | |
| "確率 : 0.6275\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5300\n", | |
| "確率 : 0.6283018867924528\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5400\n", | |
| "確率 : 0.627962962962963\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5500\n", | |
| "確率 : 0.6278181818181818\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5600\n", | |
| "確率 : 0.6285714285714286\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5700\n", | |
| "確率 : 0.6285964912280702\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5800\n", | |
| "確率 : 0.6293103448275862\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 5900\n", | |
| "確率 : 0.6289830508474576\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 6000\n", | |
| "確率 : 0.6281666666666667\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 6100\n", | |
| "確率 : 0.6285245901639345\n", | |
| "#--------------------------------#\n", | |
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| ] | |
| }, | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
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| { | |
| "name": "stdout", | |
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| ] | |
| }, | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
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| "#--------------------------------#\n", | |
| "試行回数 : 85800\n", | |
| "確率 : 0.6312121212121212\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 85900\n", | |
| "確率 : 0.6311990686845169\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86000\n", | |
| "確率 : 0.6312209302325581\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86100\n", | |
| "確率 : 0.6311614401858304\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86200\n", | |
| "確率 : 0.6312180974477958\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86300\n", | |
| "確率 : 0.6312630359212051\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86400\n", | |
| "確率 : 0.6312731481481482\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86500\n", | |
| "確率 : 0.6312369942196532\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86600\n", | |
| "確率 : 0.631270207852194\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86700\n", | |
| "確率 : 0.6312226066897347\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 86800\n", | |
| "確率 : 0.6311520737327189\n", | |
| "#--------------------------------#\n" | |
| ] | |
| }, | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "試行回数 : 86900\n", | |
| "確率 : 0.6311162255466053\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87000\n", | |
| "確率 : 0.6311034482758621\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87100\n", | |
| "確率 : 0.6311366245694604\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87200\n", | |
| "確率 : 0.6311811926605505\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87300\n", | |
| "確率 : 0.6311798396334479\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87400\n", | |
| "確率 : 0.6311327231121281\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87500\n", | |
| "確率 : 0.6311314285714286\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87600\n", | |
| "確率 : 0.6311301369863014\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87700\n", | |
| "確率 : 0.6311744583808437\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87800\n", | |
| "確率 : 0.6311503416856492\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 87900\n", | |
| "確率 : 0.6311376564277588\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88000\n", | |
| "確率 : 0.6311931818181818\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88100\n", | |
| "確率 : 0.6311577752553916\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88200\n", | |
| "確率 : 0.6312018140589569\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88300\n", | |
| "確率 : 0.6311778029445073\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88400\n", | |
| "確率 : 0.6311764705882353\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88500\n", | |
| "確率 : 0.6312429378531074\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88600\n", | |
| "確率 : 0.6311738148984198\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88700\n", | |
| "確率 : 0.631217587373168\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88800\n", | |
| "確率 : 0.6312725225225225\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 88900\n", | |
| "確率 : 0.6312260967379077\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89000\n", | |
| "確率 : 0.6311460674157303\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89100\n", | |
| "確率 : 0.6311111111111111\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89200\n", | |
| "確率 : 0.6310874439461883\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89300\n", | |
| "確率 : 0.6310638297872341\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89400\n", | |
| "確率 : 0.6309843400447427\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89500\n", | |
| "確率 : 0.631072625698324\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89600\n", | |
| "確率 : 0.63109375\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89700\n", | |
| "確率 : 0.6309810479375697\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89800\n", | |
| "確率 : 0.6309576837416481\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 89900\n", | |
| "確率 : 0.631012235817575\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90000\n", | |
| "確率 : 0.6309111111111111\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90100\n", | |
| "確率 : 0.6308324084350722\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90200\n", | |
| "確率 : 0.630920177383592\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90300\n", | |
| "確率 : 0.6309413067552603\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90400\n", | |
| "確率 : 0.6309734513274337\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90500\n", | |
| "確率 : 0.6309171270718232\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90600\n", | |
| "確率 : 0.6309381898454746\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90700\n", | |
| "確率 : 0.6309151047409041\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90800\n", | |
| "確率 : 0.6308590308370045\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 90900\n", | |
| "確率 : 0.6308030803080308\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91000\n", | |
| "確率 : 0.6308351648351649\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91100\n", | |
| "確率 : 0.630834248079034\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91200\n", | |
| "確率 : 0.6307236842105263\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91300\n", | |
| "確率 : 0.6307447973713034\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91400\n", | |
| "確率 : 0.6307221006564552\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91500\n", | |
| "確率 : 0.6307540983606558\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91600\n", | |
| "確率 : 0.6306222707423581\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91700\n", | |
| "確率 : 0.630556161395856\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91800\n", | |
| "確率 : 0.6305882352941177\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 91900\n", | |
| "確率 : 0.6305658324265506\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92000\n", | |
| "確率 : 0.6304891304347826\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92100\n", | |
| "確率 : 0.630586319218241\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92200\n", | |
| "確率 : 0.6306616052060737\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92300\n", | |
| "確率 : 0.630715059588299\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92400\n", | |
| "確率 : 0.6307142857142857\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92500\n", | |
| "確率 : 0.6306702702702702\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92600\n", | |
| "確率 : 0.6306371490280778\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92700\n", | |
| "確率 : 0.6306364617044229\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92800\n", | |
| "確率 : 0.6307112068965517\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 92900\n", | |
| "確率 : 0.6306458557588805\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93000\n", | |
| "確率 : 0.6305913978494624\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93100\n", | |
| "確率 : 0.6305692803437164\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93200\n", | |
| "確率 : 0.6305901287553648\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93300\n", | |
| "確率 : 0.6307073954983923\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93400\n", | |
| "確率 : 0.6306638115631692\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93500\n", | |
| "確率 : 0.6306310160427807\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93600\n", | |
| "確率 : 0.6305448717948718\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93700\n", | |
| "確率 : 0.6304909284951974\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93800\n", | |
| "確率 : 0.6305117270788912\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 93900\n", | |
| "確率 : 0.6304898828541001\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94000\n", | |
| "確率 : 0.6305106382978724\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94100\n", | |
| "確率 : 0.6305632306057386\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94200\n", | |
| "確率 : 0.630583864118896\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94300\n", | |
| "確率 : 0.6305408271474019\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94400\n", | |
| "確率 : 0.6305190677966102\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94500\n", | |
| "確率 : 0.6306455026455027\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94600\n", | |
| "確率 : 0.6306871035940803\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94700\n", | |
| "確率 : 0.6306863780359029\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94800\n", | |
| "確率 : 0.6307172995780591\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 94900\n", | |
| "確率 : 0.6307060063224447\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95000\n", | |
| "確率 : 0.6306842105263157\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95100\n", | |
| "確率 : 0.6306729758149316\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95200\n", | |
| "確率 : 0.6307457983193278\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95300\n", | |
| "確率 : 0.6307345225603358\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95400\n", | |
| "確率 : 0.6307337526205451\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95500\n", | |
| "確率 : 0.6306910994764398\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95600\n", | |
| "確率 : 0.6307112970711297\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95700\n", | |
| "確率 : 0.6307210031347963\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95800\n", | |
| "確率 : 0.6307515657620042\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 95900\n", | |
| "確率 : 0.6307194994786236\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96000\n", | |
| "確率 : 0.6307291666666667\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96100\n", | |
| "確率 : 0.6307492195629553\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96200\n", | |
| "確率 : 0.6307484407484407\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96300\n", | |
| "確率 : 0.6307372793354101\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96400\n", | |
| "確率 : 0.6308091286307054\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96500\n", | |
| "確率 : 0.6307253886010362\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96600\n", | |
| "確率 : 0.6306521739130435\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96700\n", | |
| "確率 : 0.6307135470527404\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96800\n", | |
| "確率 : 0.6307851239669422\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 96900\n", | |
| "確率 : 0.6308359133126935\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97000\n", | |
| "確率 : 0.6308247422680412\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97100\n", | |
| "確率 : 0.630854788877446\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97200\n", | |
| "確率 : 0.6308230452674897\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97300\n", | |
| "確率 : 0.6308427543679342\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97400\n", | |
| "確率 : 0.6308418891170431\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97500\n", | |
| "確率 : 0.6308615384615385\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97600\n", | |
| "確率 : 0.6308196721311475\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97700\n", | |
| "確率 : 0.6308290685772774\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97800\n", | |
| "確率 : 0.6309100204498977\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 97900\n", | |
| "確率 : 0.6308682328907048\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98000\n", | |
| "確率 : 0.6308163265306123\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98100\n", | |
| "確率 : 0.6307543323139654\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98200\n", | |
| "確率 : 0.6307841140529532\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98300\n", | |
| "確率 : 0.6307833163784333\n", | |
| "#--------------------------------#\n" | |
| ] | |
| }, | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "試行回数 : 98400\n", | |
| "確率 : 0.6307926829268292\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98500\n", | |
| "確率 : 0.6308832487309645\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98600\n", | |
| "確率 : 0.630841784989858\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98700\n", | |
| "確率 : 0.630790273556231\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98800\n", | |
| "確率 : 0.6308400809716599\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 98900\n", | |
| "確率 : 0.6308493427704752\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99000\n", | |
| "確率 : 0.6308888888888889\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99100\n", | |
| "確率 : 0.6308678102926337\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99200\n", | |
| "確率 : 0.6309072580645161\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99300\n", | |
| "確率 : 0.6309768378650554\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99400\n", | |
| "確率 : 0.631056338028169\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99500\n", | |
| "確率 : 0.6311859296482412\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99600\n", | |
| "確率 : 0.6311746987951807\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99700\n", | |
| "確率 : 0.6312337011033099\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99800\n", | |
| "確率 : 0.6312725450901804\n", | |
| "#--------------------------------#\n", | |
| "試行回数 : 99900\n", | |
| "確率 : 0.6312912912912912\n", | |
| "#--------------------------------#\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "# 10万回繰り返す\n", | |
| "lot = 100000\n", | |
| "\n", | |
| "# 当たりの回数を格納する変数 => 初期値0\n", | |
| "hit = 0\n", | |
| "\n", | |
| "for r in range(lot):\n", | |
| "\n", | |
| " for i in range(100):\n", | |
| " i = random.randint(1, 100)\n", | |
| "\n", | |
| " if i == 1:\n", | |
| " hit += 1\n", | |
| " break\n", | |
| "\n", | |
| " if r != 0 and r % 100 == 0:\n", | |
| " \n", | |
| " print(\"試行回数 : \", r)\n", | |
| " print(\"確率 : \", hit / r)\n", | |
| " print(\"#--------------------------------#\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### おまけ グラフにしてみる" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 36, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "# 10万回繰り返す\n", | |
| "lot = 100000\n", | |
| "lotArray = []\n", | |
| "\n", | |
| "# 当たりの回数を格納する変数 => 初期値0\n", | |
| "hit = 0\n", | |
| "hitArray = []\n", | |
| "\n", | |
| "for r in range(lot):\n", | |
| "\n", | |
| " for i in range(100):\n", | |
| " i = random.randint(1, 100)\n", | |
| "\n", | |
| " if i == 1:\n", | |
| " hit += 1\n", | |
| " break\n", | |
| "\n", | |
| " if r != 0 and r % 100 == 0:\n", | |
| " \n", | |
| " lotArray.append(r)\n", | |
| " hitArray.append(hit / r)\n", | |
| " " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 37, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.legend.Legend at 0x20dc9d04370>" | |
| ] | |
| }, | |
| "execution_count": 37, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 1440x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "## グラフを作成する\n", | |
| "# 実測値と理論値を描画\n", | |
| "\n", | |
| "%matplotlib inline\n", | |
| "import matplotlib.pyplot as plt\n", | |
| "\n", | |
| "fig = plt.figure(figsize = (20, 10))\n", | |
| "ax = fig.add_subplot(111)\n", | |
| "ax.grid()\n", | |
| "\n", | |
| "ax.plot(lotArray, hitArray)\n", | |
| "ax.plot([0, lot], [1 - p, 1 - p])\n", | |
| "\n", | |
| "ax.legend([\"measured value\", \"theoretical value\"])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "以下のサイトでは、円グラフで可視化してみました。\\\n", | |
| "https://www.pon-x.jp/entry/2020/11/09/090651" | |
| ] | |
| } | |
| ], | |
| "metadata": { | |
| "celltoolbar": "Raw Cell Format", | |
| "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": 2 | |
| } |
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