637 lines
90 KiB
Plaintext
637 lines
90 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "93d8c208-e950-4681-b4fe-1c78fc1b2a21",
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"metadata": {},
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"source": [
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"# Рабочая тетрадь No 1"
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]
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},
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{
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"cell_type": "markdown",
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"id": "362b66a9",
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"metadata": {},
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"source": [
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"1.3 Задание"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "b9a69252-6f4f-496f-bb22-6bbbed2cdcac",
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"metadata": {},
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"outputs": [],
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"source": [
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"x = 5 >= 2\n",
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"A = {1,3,7,8}\n",
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"B = {2,4,5,10,'apple'}\n",
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"C = A & B\n",
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"df = 'Антонова Антонина', 34, 'ж'\n",
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"z = 'type'\n",
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"D = [1, 'title', 2, 'content']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "553ba58d-ca06-49fb-a652-cede2cc33559",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True | <class 'bool'> \n",
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" {8, 1, 3, 7} | <class 'set'> \n",
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" {2, 4, 5, 'apple', 10} | <class 'set'> \n",
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" set() | <class 'set'> \n",
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" ('Антонова Антонина', 34, 'ж') | <class 'tuple'> \n",
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" type | <class 'str'> \n",
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" [1, 'title', 2, 'content'] | <class 'list'>\n"
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]
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}
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],
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"source": [
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"print(x, '|', type(x), '\\n', A, '|', type(A), '\\n', B, '|', type(B),\n",
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" '\\n', C, '|', type(C), '\\n', df, '|', type(df), '\\n',\n",
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" z, '|', type(z),'\\n', D, '|', type(D),)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2ee18350-697a-4d9a-a22a-4362b7870a7f",
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"metadata": {},
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"source": [
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"2.3 Задание"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "092547e5-a728-4b08-9640-8acc2537285c",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"х принадлежит (5, +infinity)\n"
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]
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}
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],
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"source": [
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"x = 10\n",
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"\n",
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"if x < -5:\n",
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" print(\"x принадлежит (-infinity, -5)\")\n",
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"elif x >= -5 and x <= 5:\n",
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" print(\"x принадлежит [-5;5]\")\n",
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"else:\n",
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" print(\"х принадлежит (5, +infinity)\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b157c155-7cd1-485d-9dbd-63075743a3a3",
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"metadata": {},
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"source": [
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"Задание 3.3.1"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "638e3938-cdbe-48b5-a089-f47a1b7317f5",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"10\n",
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"7\n",
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"4\n",
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"1\n"
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]
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}
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],
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"source": [
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"x = 10\n",
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"while x > 0:\n",
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" print(x)\n",
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" x -= 3"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c64c1c7a-d9ec-491c-8b2f-4d0e3ac33d64",
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"metadata": {},
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"source": [
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"Задание 3.3.2."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "f6d05bd4-277e-4420-9368-3d3eb457e521",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Пол\n",
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"Возраст\n",
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"Группа крови\n"
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]
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}
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],
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"source": [
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"list_of_human_characters = [\"Пол\", \"Возраст\", \"Группа крови\"]\n",
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"\n",
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"for character in list_of_human_characters:\n",
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" print(character)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f31280d8-374d-443e-8578-530748ea61aa",
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"metadata": {},
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"source": [
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"Задание 3.3.3."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "0a5413ba-1e73-473a-9940-326b75d2cb68",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n"
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]
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}
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],
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"source": [
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"list_of_numbers = range(2, 16)\n",
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"\n",
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"print(list(list_of_numbers))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1a8bf4ca-ec68-4224-b3cb-a57e7bfda81b",
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"metadata": {},
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"source": [
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"Задание 3.3.4."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "bc3e295f-1fa1-4822-96ec-87b128e97ec2",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"105\n",
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"80\n",
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"55\n",
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"30\n",
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"5\n"
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]
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}
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],
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"source": [
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"for i in range(105, 4, -25):\n",
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" print(i)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c7cfb41f-d1dd-4e64-b524-6061eec4377a",
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"metadata": {},
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"source": [
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"Задание 3.3.5."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "071fff6c-ef63-40ea-bb59-b3c740cdd667",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[8, 1, 6, 3, 4, 5, 2, 7, 0, 9]\n"
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]
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}
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],
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"source": [
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"x = [0,1,2,3,4,5,6,7,8,9]\n",
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"x[::2] = x[::2][::-1]\n",
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"\n",
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"print(x)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0f07122f-4736-43ae-b784-9f809eb15867",
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"metadata": {},
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"source": [
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"4.3.1 Задание"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 66,
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"id": "c0d364bc-976e-4e92-b23c-f0612d4d116e",
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"metadata": {},
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"outputs": [],
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"source": [
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"import random\n",
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"from statistics import median\n",
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"from matplotlib import pyplot as plt\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 67,
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"id": "a0e5ad2a-4f64-4dd1-a23e-f094834a1883",
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"metadata": {},
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"outputs": [],
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"source": [
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"count = 1000\n",
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"\n",
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"x_values = np.concatenate([np.random.random(count)])\n",
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"y_values = list(range(count))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 68,
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"id": "90791a47-6edf-4d72-9ffc-2a859a9b5b2f",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.48475484828462484\n",
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"0.4998818822942002\n"
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]
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}
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],
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"source": [
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"avg_value = sum(x_values) / len(x_values)\n",
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"median_value = median(x_values)\n",
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"\n",
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"print(avg_value)\n",
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"print(median_value)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 69,
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"id": "892aab6d-5ce0-4d66-b45a-e4ba218aff39",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD4CAYAAAAAczaOAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAABmcklEQVR4nO29f5Bcx30n9undHYC7kM0FI0glrgiCVklEhEOIFRAJZSZXApUYPtGG1oRFSEeddY5SqiSObeIYhKCPZQIOWUQKkSFfXZIrluOcXZKpBQl6RRx0B9omFedokTKgXQiGRNxJpghyyViwiaVNYAHO7nb+mOlFT09/v/3tfv1mFjvvU8UiOTvzXr/X3d/+/vx8ldYaFSpUqFChN9DX7QFUqFChQoXOoRL6FSpUqNBDqIR+hQoVKvQQKqFfoUKFCj2ESuhXqFChQg9hoNsDCOHd7363XrduXbeHUaFChQrXFE6ePPk3Wus17udLXuivW7cOJ06c6PYwKlSoUOGaglLqFd/nlXunQoUKFXoIldCvUKFChR5CJfQrVKhQoYdQCf0KFSpU6CFUQr9ChQoVeghBoa+U+j2l1I+VUn9pfXaDUuqPlVL/sfnv1dbfHlBK/UApdVYptd36fLNS6nTzb/9CKaXyP06FCsDE5DRuP/Asbtl7DLcfeBYTk9M9OYYKFXyQpGz+awD/EsAfWJ/tBfCnWusDSqm9zf+/Xyn1YQCfAbABwI0A/kQp9SGt9TyA/xPAFwG8AOAbAH4WwL/N9SC9gInJaex7+gxmZusAgNVDNTz08xswNjrS5ZEtHUxMTuOBp05jtj4PAJiemcUDT50GgKT3NDE5jYPHz+L1mVncODyIPdtv9V7H/t71gzVcfGcO9XndNgYAoutVqFAWgkJfa/1nSql1zsefAvDx5n//PoBvAri/+fnXtNZXALyslPoBgI8qpX4E4Ce11t8CAKXUHwAYQ5eEvnQjLyVMTE5jzxOnUF+4SoV94VIde548BSBNoC1HHDx+dlHgG8zW53Hw+NnFdxQjyCUHiPs9cyi7Y9h/9Awu1xe81zNjL3NNLtV1v1THtVyRWpz1Xq31GwCgtX5DKfWe5ucjaGjyBq81P6s3/9v93Aul1BfRsAqwdu3axCH6kVsTjLlvkYV98PjZFoFvUJ/XLQKt1/H6zCz7ecz8Sw4QANh/9Ezb93y4cCn+MMg1r91a90XHNTE5jf1Hzyy+u+HBGvbt2ACgsphSkbsi1+en18znXmitHwPwGABs2bIla5cX6UbOiRwbjhJm3N+6pUF1U3O7cXgQ0573cePwIIC4+Q8dIEDjWX3CPAbUYeCOqch77ca6l4AbFwDsefLUopsMaFhR/2x8Cv39yus+i7XmehGp2Tt/rZR6HwA0//3j5uevAbjJ+t77Abze/Pz9ns9LhS+YJtnIuRFa2BzMM3AnnxFo7u8eeOo0pmdmoXF1Y5QdUOzWfQ32bL8Vg7X+ls8Ga/3Ys/1WADJBbuB7r+7n+4+eEY1rsNaP4cGa6Lu+MRV9r91Y9xJw4zp4/GyLwDdYANo+t/eT713tHp/CgxNXXWm9HGhPFfpPA/h8878/D+Dr1uefUUqtVErdAuCDAL7ddAX9vVJqazNr55es35QCapMMD/k3HrXBcyB1w9nPQKHWrxYFmo0iB00RUPe97/CpjmyssdERPHrXRowMD0IBGBkexKN3bVzU8iSC3CB0gEi1fDOGfTs2eK9HHQb2mIrOZ8xzG+QUjNS1uHHFHkjm+753pQF89YVzmJicFh0KyxlB945S6nE0grbvVkq9BuAhAAcAHFZKfQHAOQCfBgCt9Rml1GEA3wMwB+BXmpk7APDfo5EJNIhGALfUIC61SVYO9GGw1t/yN3sjl4GQy4GC7xlsrFrRj1p/H3aPT+Hg8bMtJqzEt12G+Uvdd17rjvmQx0ZHyHvs2X5ri6sNaPgep2dmcfuBZ1veg/k39Z4kAlcBeH7vHS2fudcD0DYmd00W1dR9z82t+5wxAO5avnEBwMUrcxgeqkW5zoxCR70TjatzRh0KW26+Ydm7gSTZO58l/vQJ4vuPAHjE8/kJAP8ganQFQE38W7N1HNq1SSzwcgjH2A0XegYF4NCuTXjgqdOLmSLupuQOmjKDetR9gaXhQ7YFthmncRT43gN1gExMTrMWmIF7sHMHErfOYhQHbs1K13LOGAB3LXMg2sFaoOG7r/Up9PcpzHsSGHzQza9xa5A7JDWA+w4v/2y4JU+tnApuk3AbzwYlHE+88iaee+m8+CCI3XCSZwhtSu6gKTOoR2luBhKXVtkBOHO93eNTbbESyXsw6yIE1xXk0/ClzypVHEIHetHEgZQYQOhaY6MjOHj8bJtWX1/QGB6s4a3L9UWBzuGtpgK0Z/ut3rkFrh6S1KGQ0yJdqsHkZSv0uU0inQxKOH71hXOsduhDzIaTPMPu8Snvb6ZnZnHL3mO4cXgQOzePeA8n6re+zRm7cM3f7jt8CvOenRryIXcqrfDg8bNkcDwk2Di3m0JDYxyx3pXvufY8cQpQYDNQbEgVh1wHeshSjFkTEiuFs8xjxgw03tWJV95s2adA6yFJHQrA1TTaImtuqabIAstY6LubZHioBq2Be8enFjcmwE8G5xu0YQfUcp7s3Ea33RO+8U3PzOLIyemWIKaB1FWQunDN32JdWp1MK+QEeyjWwv320K5NIkHsq7kICRuJ4pBLQ6cUjm3r1wTz6t31KrFSQmsy5Epzr/fw2EZsufmGtv2/e3wKNw4P4qc/cAP+/IdvkoL/wqU6Jiank9fdUk2RBZY54drY6Aie33sHDu3ahMv1hUX/t09o+1LvYjJ6TAZA7lRF8wwvH7gTz++9Y3HB+DJLXFDZHaGsFIMiGSOhLBofOplWSM2tAoKxFuq3I03XoYuY8Rthk4qULB0fqPl77qXz5JqgMuYABNfCnu23otbfWs5jMtN867XWp7B6qAaFBh3JyoFGQoOdGeTb/2Zc3zn3Fu7Zuhb9DAVYkUw3as5NwkA3U0WXraZvI5QFA/hPdirTg9IOUvzDqXCtgBhXhdRVUFQIx7q0UrOcUkDFHn76A+HsjdjAPBdY9GH/0TPRFqPRsKdnZtvWqCRpgHLZuPflXIOhgG1wLbiLuPn/3HqVWKPUuJ576Ty+dPdtuJdxlaZq+9Scm0wxaqydwLLW9A2kQso92X3azj1b1wY17JR7S+DmOgNYtAJGIjU814IA0KaB5NIapeC0vdwYGx3Bzs0jbaXi3zn3VlD7irViKE2VwoVL9SiL0a3nsEvgJRYWpaE/OHE6ak0UURJ8NCP1Bb24J22tHcCiVu+jwHCtUW5cY6MjbNFcqrXum3OfwtiJ2hkXPaHpSzUtSit2N4zxFaak7KViYnK6pSR9ema2hWwtNS3UXNunLe3cPIIjJ6dFGSPZYhmEtlcGnnvpfLJ1FmPFUJqqzZjKITQmqhhpZHiwrUbAB0pw+hIWuDVB7QnJHpBSXrjrVHK9kAW5b8cGMuMs1Vo337dTUVMTB3KjJzT9Pdtv9ZL/uJAKaKN1UNq1Qc6ir/1Hz7SVntfn9WIsIsWHbsCZv6Fr5qRdCGl7uSEVNDl8sL7YzM/d9r7CY+X+JhEmXFWx70A89t03sHLgqthYtaJ/0Z9+8cpcm6Um3QMSq1LipvX9LhTDMnuHgvHDS+ferJl7x6cwIyguK5MNwIee0PTHRkdIv51Bit9z2/o1bVqPL2WPu4ZUK6Y2pv15SlooEDZ/uWvmyFKw/dGS8aW+Q/d3VMWn2YRlp90999J58Xc5wVAkFhJ7oLrv6+I78wCuUkqbAOvMpXrU3EgsValG7P5OEsMKZcRJ595dMyFDtWw2AB96QugDDSFMTSgloG34BMCRk9NtufDb1q/Bcy+dx/TMLO47fAr3jk8tXh9AqUIkBROT0+hTisypDwlYLktBen+umMuMg/p+6macnplFrU+hZrE1Aq2bsOy0u1Qh5qKIay+3a6G+oDG0YgCTv/kzUb+TCGbqcBserGHVygFWCZAoRKHCQsncS60R1XyebhRs9YzQpzZGURfI4y++igWtvZq/EaRGMF1X60s
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 432x288 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {
|
|||
|
|
"needs_background": "light"
|
|||
|
|
},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"plt.scatter(x_values, y_values)\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "5320fef5-cf42-4dd4-a09c-2705a93864c2",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"4.3.2 Задание"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 70,
|
|||
|
|
"id": "d9b6bc90-8c75-4a0b-a3d9-739e12c1769b",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"import numpy as np\n",
|
|||
|
|
"import matplotlib.pyplot as plt"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 71,
|
|||
|
|
"id": "7dc99ddf-fcbe-4a91-9ee3-f102f5c525c7",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"def function(x):\n",
|
|||
|
|
" return (np.sqrt(1 + np.e ** np.sqrt(x) + np.cos(x ** 2)) / abs(1 - np.sin(x) ** 3)) + np.log(2 * x)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 72,
|
|||
|
|
"id": "d1bf7069-4c70-4ca5-852c-5c0481c9ee23",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 432x288 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {
|
|||
|
|
"needs_background": "light"
|
|||
|
|
},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"x = np.arange(1, 11, 1)\n",
|
|||
|
|
"y = function(x)\n",
|
|||
|
|
"\n",
|
|||
|
|
"plt.grid()\n",
|
|||
|
|
"plt.plot(x, y)\n",
|
|||
|
|
"plt.scatter(x[:len(x)//2], y[:len(x)//2])\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "3abb52c1",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"4.3.3 Задание"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 17,
|
|||
|
|
"id": "b4763e0b-af25-4f52-b6f0-6f8461eeb686",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"import numpy as np\n",
|
|||
|
|
"import matplotlib.pyplot as plt\n",
|
|||
|
|
"from numpy import trapz"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 18,
|
|||
|
|
"id": "0e8d1e51-9c2c-495d-bb97-0462401e6c36",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"def funtion2(x):\n",
|
|||
|
|
" return abs(np.cos(x * np.e ** (np.cos(x) + np.log(x + 1))))"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 34,
|
|||
|
|
"id": "55b31fe0",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"x = np.arange(0, 11, 1)\n",
|
|||
|
|
"y = funtion2(x)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 35,
|
|||
|
|
"id": "898021c3-9fd5-4328-bbe1-d23c3cc004dc",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 432x288 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {
|
|||
|
|
"needs_background": "light"
|
|||
|
|
},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"plt.grid()\n",
|
|||
|
|
"plt.plot(x, y)\n",
|
|||
|
|
"plt.fill_between(x, y)\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 36,
|
|||
|
|
"id": "7a18f9fa-0283-4c42-a7f4-9724ea606def",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"6.748183214657723\n"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"area = trapz(y)\n",
|
|||
|
|
"print(area)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "984e6926",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"4.3.4 Задание"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 22,
|
|||
|
|
"id": "c5227063-0e66-4e3d-a867-65b7a939ad2f",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"import numpy as np\n",
|
|||
|
|
"import matplotlib.pyplot as plt\n",
|
|||
|
|
"from numpy import trapz"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 26,
|
|||
|
|
"id": "06b78197-20da-49e8-a625-059bfa571add",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"apple_share = [132, 135, 145, 147, 124, 139, 149, 151, 141, 149, 148, 177]\n",
|
|||
|
|
"google_share = [1727, 1783, 2000, 2242, 2360, 2427, 2597, 2750, 2794, 2761, 2901, 2934]\n",
|
|||
|
|
"microsoft_share = [217, 239, 236, 242, 251, 247, 271, 284, 301, 289, 329, 330] "
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 27,
|
|||
|
|
"id": "afdf47d8",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 432x288 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {
|
|||
|
|
"needs_background": "light"
|
|||
|
|
},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"x = np.arange(1, 13, 1)\n",
|
|||
|
|
"\n",
|
|||
|
|
"plt.grid()\n",
|
|||
|
|
"plt.plot(x, apple_share, label=\"apple\")\n",
|
|||
|
|
"plt.plot(x, microsoft_share, label=\"microsoft\")\n",
|
|||
|
|
"plt.plot(x, google_share, label=\"google\")\n",
|
|||
|
|
"plt.title(\"График цен акций\")\n",
|
|||
|
|
"plt.legend()\n",
|
|||
|
|
"plt.show()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"id": "2b385688",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"4.3.5 Задание"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 25,
|
|||
|
|
"id": "0e1778ed",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"Чтобы выйти из программы введите exit\n"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"Введите (+, -, *, /, **, e, sin, cos): exit\n"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"Программа завершена\n"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"import math as m\n",
|
|||
|
|
"\n",
|
|||
|
|
"print(\"Чтобы выйти из программы введите exit\")\n",
|
|||
|
|
"\n",
|
|||
|
|
"while True:\n",
|
|||
|
|
" user_input = input(\"Введите (+, -, *, /, **, e, sin, cos): \")\n",
|
|||
|
|
" if user_input == \"exit\":\n",
|
|||
|
|
" break \n",
|
|||
|
|
" elif user_input in ['+', '-', '*', '/', '**', 'e', 'sin', 'cos']:\n",
|
|||
|
|
" x = float(input(\"x = \"))\n",
|
|||
|
|
" y = float(input(\"y = \"))\n",
|
|||
|
|
" \n",
|
|||
|
|
" if user_input == 'e':\n",
|
|||
|
|
" print(\"e ** (x + y) = \", m.e**(x + y))\n",
|
|||
|
|
" elif user_input == 'sin':\n",
|
|||
|
|
" print(\"sin(x + y) =\", m.sin(x + y))\n",
|
|||
|
|
" elif user_input == 'cos':\n",
|
|||
|
|
" print(\"cos(x + y) =\", m.cos(x + y))\n",
|
|||
|
|
" else:\n",
|
|||
|
|
" formula = f\"{x} {user_input} {y}\"\n",
|
|||
|
|
" print(formula, \"=\", eval(formula))\n",
|
|||
|
|
" else:\n",
|
|||
|
|
" print(\"Неверный знак операции!\")\n",
|
|||
|
|
"\n",
|
|||
|
|
"print(\"Программа завершена\")"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"id": "5fda3145",
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": []
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"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": "3.9.7"
|
|||
|
|
},
|
|||
|
|
"vscode": {
|
|||
|
|
"interpreter": {
|
|||
|
|
"hash": "c8e7b8a5fb18722c706c80178f617ac0f7a16c4b5a7c63b4b737eecf7a54cfec"
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"nbformat": 4,
|
|||
|
|
"nbformat_minor": 5
|
|||
|
|
}
|