Skip to content

Instantly share code, notes, and snippets.

@ischurov

ischurov/Untitled.ipynb

Last active October 21, 2017 11:59
Show Gist options
  • Save ischurov/bdf2cc3c4ad1e5be176324d15209b9f4 to your computer and use it in GitHub Desktop.
Save ischurov/bdf2cc3c4ad1e5be176324d15209b9f4 to your computer and use it in GitHub Desktop.
Download ZIP
web scrapping day 2.ipynb
Display the source blob
Display the rendered blob
Raw
Untitled.ipynb
{
"cells": [
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "3 * 2",
"execution_count": 1,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 1,
"data": {
"text/plain": "6"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "4 * (1 + 3)",
"execution_count": 2,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 2,
"data": {
"text/plain": "16"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "*Первое занятие*\n\n**Python**"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "sqrt(4)",
"execution_count": 3,
"outputs": [
{
"output_type": "error",
"ename": "NameError",
"evalue": "name 'sqrt' is not defined",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-3-718d7f173e1d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msqrt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'sqrt' is not defined"
]
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "import math",
"execution_count": 4,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "math.sqrt(4)",
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 5,
"data": {
"text/plain": "2.0"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "math.log(12)",
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 6,
"data": {
"text/plain": "2.4849066497880004"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "import math as m",
"execution_count": 7,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "m.sqrt(4)",
"execution_count": 8,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 8,
"data": {
"text/plain": "2.0"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "from math import sqrt",
"execution_count": 9,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "sqrt(4)",
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 10,
"data": {
"text/plain": "2.0"
},
"metadata": {}
}
]
},
{
"metadata": {
"code_folding": [],
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# не делайте так:\n# from math import *",
"execution_count": 11,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "x = 12\ny = 6\nx + y",
"execution_count": 12,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 12,
"data": {
"text/plain": "18"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "z = 5\nz",
"execution_count": 16,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 16,
"data": {
"text/plain": "5"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "print(\"z =\", z)\nprint(\"x =\", x)\nprint(\"Hello, World!\")",
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"text": "z = 5\nx = 12\nHello, World!\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "x = 12",
"execution_count": 17,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "12.",
"execution_count": 18,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 18,
"data": {
"text/plain": "12.0"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "6 / 2",
"execution_count": 19,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 19,
"data": {
"text/plain": "3.0"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "type(12)",
"execution_count": 20,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 20,
"data": {
"text/plain": "int"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "type(3.)",
"execution_count": 21,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 21,
"data": {
"text/plain": "float"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "type(\"Hello\")",
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 22,
"data": {
"text/plain": "str"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "x = 12",
"execution_count": 23,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "y = str(x)",
"execution_count": 24,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "y",
"execution_count": 25,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 25,
"data": {
"text/plain": "'12'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "some_number_in_string = '12.3456'",
"execution_count": 26,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "float(some_number_in_string)",
"execution_count": 27,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 27,
"data": {
"text/plain": "12.3456"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_string = \"Hello\"\nother_string = \"World\"",
"execution_count": 28,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_string + other_string",
"execution_count": 29,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 29,
"data": {
"text/plain": "'HelloWorld'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_list = [0, 10, 20, 30, 40]",
"execution_count": 30,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list[3]",
"execution_count": 31,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 31,
"data": {
"text/plain": "30"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list[1:4]",
"execution_count": 32,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 32,
"data": {
"text/plain": "[10, 20, 30]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list[:3]",
"execution_count": 33,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 33,
"data": {
"text/plain": "[0, 10, 20]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_list.append(123)",
"execution_count": 34,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list",
"execution_count": 35,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 35,
"data": {
"text/plain": "[0, 10, 20, 30, 40, 123]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_list.append(\"Hello\")",
"execution_count": 36,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list",
"execution_count": 37,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 37,
"data": {
"text/plain": "[0, 10, 20, 30, 40, 123, 'Hello']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "other_list = my_list",
"execution_count": 38,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_list[0] = 1000",
"execution_count": 39,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "other_list",
"execution_count": 40,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 40,
"data": {
"text/plain": "[1000, 10, 20, 30, 40, 123, 'Hello']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_string = \"Hello, world! This is a test.\"",
"execution_count": 41,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "other_string = my_string.replace(\" \", \"_\")",
"execution_count": 44,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_string",
"execution_count": 43,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 43,
"data": {
"text/plain": "'Hello, world! This is a test.'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "other_string",
"execution_count": 45,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 45,
"data": {
"text/plain": "'Hello,_world!_This_is_a_test.'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list = [1, 2, 3]\nmy_list = my_list.append(4)\nprint(my_list)",
"execution_count": 46,
"outputs": [
{
"output_type": "stream",
"text": "None\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "len(other_list)",
"execution_count": 48,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 48,
"data": {
"text/plain": "7"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "other_list",
"execution_count": 49,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 49,
"data": {
"text/plain": "[1000, 10, 20, 30, 40, 123, 'Hello']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "other_list[-1]",
"execution_count": 50,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 50,
"data": {
"text/plain": "'Hello'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "other_list[-2]",
"execution_count": 51,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 51,
"data": {
"text/plain": "123"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_string = \"12.45%\"",
"execution_count": 52,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "percent = float(my_string[:-1]) * 0.01",
"execution_count": 53,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "percent",
"execution_count": 54,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 54,
"data": {
"text/plain": "0.1245"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "percent = float(my_string.replace(\"%\", \"\")) * 0.01",
"execution_count": 55,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_tuple = (12, 34, 3, 2)",
"execution_count": 56,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_tuple[2]",
"execution_count": 57,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 57,
"data": {
"text/plain": "3"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_tuple[1] = 123",
"execution_count": 58,
"outputs": [
{
"output_type": "error",
"ename": "TypeError",
"evalue": "'tuple' object does not support item assignment",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-58-98ba7d0548cd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmy_tuple\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m123\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
]
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_list = [1, 2, 3, 5]",
"execution_count": 60,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_list.insert(1, 'Hello')",
"execution_count": 61,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list",
"execution_count": 62,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 62,
"data": {
"text/plain": "[1, 'Hello', 2, 3, 5]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "other_list = my_list.copy()",
"execution_count": 63,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_tuple",
"execution_count": 64,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 64,
"data": {
"text/plain": "(12, 34, 3, 2)"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "list_from_tuple = list(my_tuple)",
"execution_count": 65,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "list_from_tuple",
"execution_count": 66,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 66,
"data": {
"text/plain": "[12, 34, 3, 2]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "some_dict = {'Ann': 3, 'Bob': 5, 'Dan': 3}",
"execution_count": 67,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "some_dict['Ann']",
"execution_count": 68,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 68,
"data": {
"text/plain": "3"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "some_dict['Ann'] = 4",
"execution_count": 69,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "some_dict",
"execution_count": 70,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 70,
"data": {
"text/plain": "{'Ann': 4, 'Bob': 5, 'Dan': 3}"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "some_dict['Claudia'] = 3",
"execution_count": 71,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "some_dict",
"execution_count": 72,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 72,
"data": {
"text/plain": "{'Ann': 4, 'Bob': 5, 'Claudia': 3, 'Dan': 3}"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list = [3, 2, 10, 54]",
"execution_count": 74,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "for element in my_list:\n if element >= 10:\n print(element)\nprint(\"That's all\")",
"execution_count": 80,
"outputs": [
{
"output_type": "stream",
"text": "10\n54\nThat's all\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "large_numbers = []\nfor element in my_list:\n if element >= 10:\n large_numbers.append(element)\nprint(large_numbers)",
"execution_count": 81,
"outputs": [
{
"output_type": "stream",
"text": "[10, 54]\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "large_numbers = [element*2 for element in my_list if element >= 10]",
"execution_count": 84,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "large_numbers",
"execution_count": 85,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 85,
"data": {
"text/plain": "[20, 108]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "some_dict",
"execution_count": 86,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 86,
"data": {
"text/plain": "{'Ann': 4, 'Bob': 5, 'Claudia': 3, 'Dan': 3}"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "for key in some_dict:\n print(key, some_dict[key])",
"execution_count": 88,
"outputs": [
{
"output_type": "stream",
"text": "Ann 4\nBob 5\nDan 3\nClaudia 3\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "for key, value in some_dict.items():\n print(key, value)",
"execution_count": 89,
"outputs": [
{
"output_type": "stream",
"text": "Ann 4\nBob 5\nDan 3\nClaudia 3\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "good_students = []\nfor student, grade in some_dict.items():\n if grade == 5:\n good_students.append(student)",
"execution_count": 106,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "good_students",
"execution_count": 107,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 107,
"data": {
"text/plain": "['Bob']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "good_students = [student for student, grade in some_dict.items()\n if grade == 5]",
"execution_count": 108,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "good_students",
"execution_count": 109,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 109,
"data": {
"text/plain": "['Bob']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "a = 12\nb = 54",
"execution_count": 91,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "a, b = (b, a)",
"execution_count": 92,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "x, y = [23, 45]",
"execution_count": 97,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "some_dict.items()",
"execution_count": 98,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 98,
"data": {
"text/plain": "dict_items([('Ann', 4), ('Bob', 5), ('Dan', 3), ('Claudia', 3)])"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "students = ['Ann', 'Dan', 'Bob', 'Claudia']\ngrades = [3, 2, 5, 4]",
"execution_count": 99,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "for student, grade in zip(students, grades):\n print(student, grade)",
"execution_count": 100,
"outputs": [
{
"output_type": "stream",
"text": "Ann 3\nDan 2\nBob 5\nClaudia 4\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "list(zip(students, grades))",
"execution_count": 101,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 101,
"data": {
"text/plain": "[('Ann', 3), ('Dan', 2), ('Bob', 5), ('Claudia', 4)]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "list(zip([1,2,3], [4, 5, 6], [7, 8, 9]))",
"execution_count": 103,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 103,
"data": {
"text/plain": "[(1, 4, 7), (2, 5, 8), (3, 6, 9)]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "name = input(\"Enter your name: \")\nprint(\"Hello,\", name)",
"execution_count": 112,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": "Enter your name: Hello\nHello, Hello\n"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "a = 12\nd = 5\nwhile a < 100:\n a = a + d\n print(a)",
"execution_count": 114,
"outputs": [
{
"output_type": "stream",
"text": "17\n22\n27\n32\n37\n42\n47\n52\n57\n62\n67\n72\n77\n82\n87\n92\n97\n102\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "while True:\n s = input(\"Enter some number: \")\n if s.isdecimal():\n break\nprint(int(s) + 10)",
"execution_count": 115,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": "Enter some number: Haha\nEnter some number: 123\n133\n"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_dict = {1: 2, 3: 14, 5: 32}",
"execution_count": 116,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_dict[1]",
"execution_count": 117,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 117,
"data": {
"text/plain": "2"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "sums = {(1, 2): 3, (4, 8): 12}",
"execution_count": 118,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "sums[(1, 2)]",
"execution_count": 119,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 119,
"data": {
"text/plain": "3"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_dict = {'Ann': 5, 'Ann': 3, 'Bob': 4}",
"execution_count": 120,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_dict['Ann']",
"execution_count": 122,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 122,
"data": {
"text/plain": "3"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "gradebook = {'Ann': [3, 2], 'Bob': [], 'Dan': [4, 5, 3]}",
"execution_count": 123,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "gradebook['Ann']",
"execution_count": 124,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 124,
"data": {
"text/plain": "[3, 2]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "gradebook = {'Ann': {'Math': 3, 'Economics': 4, 'Programming': 5},\n 'Dan': {'Math': 4, 'Economics': 5, 'History': 3}}",
"execution_count": 125,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "gradebook['Dan']['Economics']",
"execution_count": 128,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 128,
"data": {
"text/plain": "5"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# JSON",
"execution_count": 129,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "table = [[1, 2, 3], \n [4, 5, 6]]",
"execution_count": 130,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "table[0]",
"execution_count": 131,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 131,
"data": {
"text/plain": "[1, 2, 3]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "table[1]",
"execution_count": 132,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 132,
"data": {
"text/plain": "[4, 5, 6]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "# упражнение: получить первый столбец таблицы table\ncolumn = []\nfor row in table:\n column.append(row[0])\ncolumn",
"execution_count": 133,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 133,
"data": {
"text/plain": "[1, 4]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "column = [row[0] for row in table]",
"execution_count": 134,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "column",
"execution_count": 135,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 135,
"data": {
"text/plain": "[1, 4]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "def times2(x):\n print(\"x =\", x)\n return x * 2",
"execution_count": 139,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "times2(5)",
"execution_count": 140,
"outputs": [
{
"output_type": "stream",
"text": "x = 5\n",
"name": "stdout"
},
{
"output_type": "execute_result",
"execution_count": 140,
"data": {
"text/plain": "10"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "times2(5) + times2(7)",
"execution_count": 141,
"outputs": [
{
"output_type": "stream",
"text": "x = 5\nx = 7\n",
"name": "stdout"
},
{
"output_type": "execute_result",
"execution_count": 141,
"data": {
"text/plain": "24"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "def times2(x):\n print(x * 2)",
"execution_count": 142,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "times2(10)",
"execution_count": 143,
"outputs": [
{
"output_type": "stream",
"text": "20\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "z = times2(10)",
"execution_count": 144,
"outputs": [
{
"output_type": "stream",
"text": "20\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "print(z)",
"execution_count": 146,
"outputs": [
{
"output_type": "stream",
"text": "None\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "def get_column(table, i):\n return [row[i] for row in table]",
"execution_count": 147,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "table",
"execution_count": 149,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 149,
"data": {
"text/plain": "[[1, 2, 3], [4, 5, 6]]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "get_column(table, 0)",
"execution_count": 151,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 151,
"data": {
"text/plain": "[1, 4]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list = my_list * 100000",
"execution_count": 156,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "len(my_list)",
"execution_count": 157,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 157,
"data": {
"text/plain": "400000"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "%%timeit\nnew_list = []\nfor i in range(len(my_list)):\n new_list.append(my_list[i] * 10)",
"execution_count": 159,
"outputs": [
{
"output_type": "stream",
"text": "83.3 ms ± 6.07 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "%%timeit\nnew_list = []\nfor element in my_list:\n new_list.append(element * 10)",
"execution_count": 160,
"outputs": [
{
"output_type": "stream",
"text": "53.4 ms ± 2.21 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "%%timeit\nnew_list = [element * 10 for element in my_list]",
"execution_count": 161,
"outputs": [
{
"output_type": "stream",
"text": "26.1 ms ± 1.4 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "for i in range(5):\n print(\"Hello\")",
"execution_count": 152,
"outputs": [
{
"output_type": "stream",
"text": "Hello\nHello\nHello\nHello\nHello\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "C_n_k",
"execution_count": 1,
"outputs": [
{
"output_type": "error",
"ename": "NameError",
"evalue": "name 'C_n_k' is not defined",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-1-7cba926a07a5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mC_n_k\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mNameError\u001b[0m: name 'C_n_k' is not defined"
]
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "def C_n_k(n, k):\n return factorial(n) // factorial(k) // factorial(n-k)",
"execution_count": 1,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "def factorial(n):\n f = 1\n for i in range(1, n + 1):\n f *= i\n return f",
"execution_count": 3,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "C_n_k(4, 2)",
"execution_count": 4,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 4,
"data": {
"text/plain": "6"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "$$\nC_n=\\frac{n!}{k!(n-k)!}\n$$"
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "def factorial_rec(n):\n if n == 0:\n return 1\n if n > 0:\n return factorial_rec(n - 1) * n",
"execution_count": 5,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "factorial(10000)",
"execution_count": 13,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 13,
"data": {
"text/plain": "28462596809170545189064132121198688901480514017027992307941799942744113400037644437729907867577847758158840621423175288300423399401535187390524211613827161748198241998275924182892597878981242531205946599625986706560161572036032397926328736717055741975962099479720346153698119897092611277500484198845410475544642442136573303076703628825803548967461117097369578603670191071512730587281041158640561281165385325968425825995584688146430425589836649317059251717204276597407446133400054194052462303436869154059404066227828248371512038322178644627183822923899638992827221879702459387693803094627332292570555459690027875282242544348021127559019169425429028916907219097083690539873747452483372899521802363282741217040268086769210451555840567172555372015852132829034279989818449313610640381489304499621599999359670892980190336998484404665419236258424947163178961192041233108268651071354516845540936033009607210346944377982349430780626069422302681885227592057029230843126188497606560742586279448827155956831533440534425446648416894580425709461673613187605234982286326452921529423479870603344290737158688499178932580691483168854251956006172372636323974420786924642956012306288720122652952964091508301336630982733806353972901506581822574295475894399765113865541208125788683704239208764484761569001264889271590706306409661628038784044485191643790807186112370622133415415065991843875961023926713276546986163657706626438638029848051952769536195259240930908614471907390768585755934786981720734372093104825475628567777694081564074962275254993384112809289637516990219870492405617531786346939798024619737079041868329931016554150742308393176878366923694849025999607729684293977427536263119825416681531891763234839190821000147178932184227805135181734921901146246875769835373441456013122615221391178759688367364087207937002992038279198038702372078039140312368997608152840306051116709484722224870389199993442071395836983063962232079115624044250808919914319837120445598344047556759489212101498152454543594285414390843564419984224855478532163624030098442855331829253154206551237079705816393460296247697010388742206441536626733715428700789122749340684336442889847100840641600093623935261248037975293343928764398316390312776450722479267851700826669598389526150759007349215197592659192708873202594066382118801988854748266048342256457705743973122259700671936061763513579529821794290797705327283267501488024443528681645026165662837546519006171873442260438919298506071515390031106684727360135816706437861756757439184376479658136100599638689552334648781746143243573224864326798481981458432703035895508420534788493364582482592033288089025782388233265770205248970937047210214248413342465268206806732314214483854074182139621846870108359582946965235632764870475718351616879235068366271743711915723361143070121120767608697851559721846485985918643641716850899625516820910793570231118518174775010804622585521314764897490660752877082897667514951009682329689732000622392888056658036140311285465929084078033974900664953205873164948093883816198658850827382468034897864757116679890423568018303504133875731972630897909435710687797301633918087868474943633533893373586906405848417828065196275826434429258058422212947649402948622670761832988229004072390403733168207417413251656688443079339447019208905620788387585342512820957359307018197708340163817638278562539516825426644614941044711579533262372815468794080423718587423026200264221822694188626212107297776657401018376182280136857586442185863011539843712299107010094061929413223202773193959467006713695377097897778118288242442920864816134179562017471831609687661043140497958198236445807368209404022211181530051433387076607063149616107771117448059552764348333385744040212757031851527298377435921878558552795591028664457917362007221858143309977294778923720717942857756271300923982397921957581197264742642878266682353915687857271620146192244266266708400765665625807109474398740110772811669918806268726626565583345665007890309050656074633078027158530817691223772813510584527326591626219647620571434880215630815259005343721141000303039242866457207328473481712034168186328968865048287367933398443971236735084527340196309427697652684170174990756947982757825835229994315633322107439131550124459005324702680312912392297979030417587823398622373535054642646913502503951009239286585108682088070662734733200354995720397086488066040929854607006339409885836349865466136727880748764700702458790118046518296111277090609016152022111461543158317669957060974618085359390400067892878548827850938637353703904049412684618991272871562655001270833039950257879931705431882752659225814948950746639976007316927310831735883056612614782997663188070063044632429112260691931278881566221591523270457695867512821990938942686601963904489718918597472925310322480210543841044325828472830584297804162405108110326914001900568784396341502696521048920272140232160234898588827371428695339681755106287470907473718188014223487248498558198439094651708364368994306189650243288353279667190184527620551085707626204244509623323204744707831190434499351442625501701771017379551124746159471731862701565571266295855125077711738338208419705893367323724453280456537178514960308802580284067847809414641838659226652806867978843250660537943046250287105104929347267471267499892634627358167146935060495110340755404658170393481046758485625967767959768299409334026387269378365320912287718077451152622642548771835461108886360843272806227776643097283879056728618036048633464893371439415250259459652501520959536157977135595794965729775650902694428088479761276664847003619648906043761934694270444070215317943583831051404915462608728486678750541674146731648999356381312866931427616863537305634586626957894568275065810235950814888778955073939365341937365700848318504475682215444067599203138077073539978036339267334549549296668759922530893898086430606532961793164029612492673080638031873912596151131890359351266480818568366770286537742390746582390910955517179770580797789289752490230737801753142680363914244720257728891784950078117889336629750436804214668197824272980697579391742229456683185815676816288797870624531246651727622758295493421483658868919299587402095696000243560305289829866386892076992834030549710266514322306125231915131843876903823706205399206933943716880466429711476743564486375026847698148853105354063328845062012173302630676481322931561043551941761050712449024873277273112091945865137493190965162497691657553812198566432207978666300398938660238607357858114394715872800893374165033792965832618436073133327526023605115524227228447251463863269369763762510196714380125691227784428426999440829152215904694437282498658085205186576292992775508833128672638418713277780874446643875352644733562441139447628780974650683952982108174967958836452273344694873793471790710064978236466016680572034297929207446822322848665839522211446859572858403863377278030227591530497865873919513650246274195899088374387331594287372029770620207120213038572175933211162413330422773742416353553587977065309647685886077301432778290328894795818404378858567772932094476778669357537460048142376741194182671636870481056911156215614357516290527351224350080604653668917458196549482608612260750293062761478813268955280736149022525819682815051033318132129659664958159030421238775645990973296728066683849166257949747922905361845563741034791430771561168650484292490281102992529678735298767829269040788778480262479222750735948405817439086251877946890045942060168605142772244486272469911146200149880662723538837809380628544384763053235070132028029488392008132135446450056134987017834271106158177289819290656498688081045562233703067254251277277330283498433595772575956224703707793387146593033088629699440318332665797514676502717346298883777397848218700718026741265997158728035440478432478674907127921672898523588486943546692255101337606377915164597254257116968477339951158998349081888281263984400505546210066988792614558214565319696909827253934515760408613476258778165867294410775358824162315779082538054746933540582469717674324523451498483027170396543887737637358191736582454273347490424262946011299881916563713847111849156915054768140411749801454265712394204425441028075806001388198650613759288539038922644322947990286482840099598675963580999112695367601527173086852756572147583507122298296529564917835071750835741362282545055620270969417476799259229774888627411314587676147531456895328093117052696486410187407673296986649236437382565475022816471926815559883196629848307776666840622314315884384910519058281816740764463033300119710293036455866594651869074475250837841987622990415911793682799760654186088721626654886492344391030923256910633775969739051781122764668486791736049404393703339351900609387268397299246478483727274770977466693599784857120156789000241947269220974984127323147401549980920381459821416481176357147801554231599667838534854486406936410556913531335231184053581348940938191821898694825383960989942822027599339635206217705343572073396250574216769465101608495601439303244304271576099527308684609204422226103154229984444802110098161333824827375218998738205315164927134498105950159974800571591912202154487748750103473246190633941303030892399411985006225902184164409988173214324422108554248620896250260604398180189026317781146617454999771440665232863846363847001655618153861098188111181734191305505024860345856755585637511729774299329074944236579668332700918367338977347901759248885660379952771540569083017311723894140326159612292912225191095948743805673381278538616491842786938417556898047100859868372033615175158097022566275200160956192229925401759878522038545913771783976389811198485803291048751666921195104514896677761598249468727420663437593207852618922687285527671324883267794152912839165407968344190239094803676688707838011367042753971396201424784935196735301444404037823526674437556740883025225745273806209980451233188102729012042997989005423126217968135237758041162511459175993279134176507292826762236897291960528289675223521425234217247841869317397460411877634604625637135309801590617736758715336803958559054827361876112151384673432884325090045645358186681905108731791346215730339540580987172013844377099279532797675531099381365840403556795731894141976511436325526270639743146526348120032720096755667701926242585057770617893798231096986788448546659527327061670308918277206432551919393673591346037757083193180845929565158875244597601729455720505595085929175506510115665075521635142318153548176884196032085050871496270494017684183980582594038182593986461260275954247433376226256287153916069025098985070798660621732200163593938611475394561406635675718526617031471453516753007499213865207768523824884600623735896608054951652406480547295869918694358811197833680141488078321213457152360124065922208508912956907835370576734671667863780908811283450395784812212101117250718383359083886187574661201317298217131072944737656265172310694884425498369514147383892477742320940207831200807235326288053906266018186050424938788677872495503255424284226596271050692646071767467502337805671893450110737377034119346113374033865364675136733661394731550211457104671161445253324850197901083431641989998414045044901130163759520675715567509485243580269104077637210998671624254795385312852889930956570729218673523216666097874989635362610529821472569482799996220825775840988458484250391189447608729685184983976367918242266571167166580157914500811657192200233759765317495922397884982814705506190689275625210462185661305800255607974609726715033327032310025274640428755556546883765838802543227403507431684278620637697054791726484378174446361520570933228587284315690756255569305558818822603590006739339952504379887470935079276181116276309771257983975996526612120317495882059435754883862282508401408885720583992400971219212548074097752974278775912566026443482713647231849125180866278708626116699989634812405803684794587364820124653663228889011636572270887757736152003450102268890189101673572058661410011723664762657835396364297819011647056170279631922332294228739309233330748258937626198997596530084135383241125899639629445129082802023225498936627506499530838925632246794695960669046906686292645006219740121782899872979704859021775060092893328957272392019589994471945147360850770400725717439318148461909406269545285030526341000565022226152309364882887122046454267700577148994335147162504252365173710266068647253458120186683273953682547456536553597546685788700056988360286686450740256993087483441094086086303707908295240576731684941855810482475304758923392801571302824106234999945932390521409856559565661346003396150515164758852742214732517999548977992849522746029855666700811871200856155016457400484170210303038996339253337466556817824410737409336919294104632307731994759826307383499600770372410446285414648704116273895649834555162165685114551383822047005483996671706246467566101291382048909121117229386244253158913066987462045587244806052829378148302622164542280421757760762365459828223070815503469404938317755053305094698999476119419231280721807216964378433313606760676965187138394338772485493689061845700572043696666465080734495814495966306246698679832872586300064215220210171813917325275173672262621454945468506006334692713838311715849753092643252486960220059099802663765386225463265168414963306369548086551101256757717890616694758344043486218485369591602172030456183497524162039926441331651884768606830642004858557924473340290142588876403712518642229016333691585063273727199596362912783344786218887871009533753551054688980236378263714926913289564339440899470121452134572117715657591451734895195016800621353927175419843876163543479806920886666227099512371706241924914282576453125769939735341673046864585181979668232015693792684926999983992413571941496882273704022820805171808003400480615261792013978945186295290558440703738300533552421153903385185829366779190610116306233673144419202893857201855569596330833615450290424822309297087124788002017383072060482680156675397593789931793515799958929562156307338416294599900276730832827716595064217966523190439250543226753731811755315476780739470338931185107297724318378972674957455778183345495942317353558291046967315391275975687281861691161083156337232639968881490543943261197182274996791176628553401860198315809629981791107208804992292016062059067271273599461871634945774995805337947187105456452579396024210259136415528398395201773012712514892051061708228008339985665786646920737114269682301770416324829479409558694699089379165191006305185352102345189798127619143061864362703081977124992751056732909481202057747100687703379708934229207183903744167503493818836342229284946790660285674293251642569044363473087656797056595677285291081242733154406580199802711579126254172797452862574865921933293805915239524735518887119860391319654287576290190503964083560246277534314409155642181729459941596061979622633242715863425977947348682074802021538734729707999753332987785531053820162169791880380753006334350766147737135939362651905222242528141084747045295688647757913502160922040348449149950778743107189655725492651282693489515795075486172341394610365176616750329948642244039659511882264981315925080185126386635308622223491094629059317829408195640484702456538305432056506924422671863255307640761872086780391711356363501269525091291020496042823232628996502758951052844368177415730941874894428065427561430975828127698124936993313028946670560414084308942231140912722238148470364341019630413630736771060038159590829746410114421358321042574358350220737173219745089035573187350445827238770728271406162997919629357224104477155051652535867544109395079218369015261138440382680054150924346511711436477899444553993653667727589565713987505542990824585609510036934663100673714708029927656933435500927189854050109917474979991554392031908961967615444686048175400695689471463928245383807010444181045506171305160584355817521032338465829201071030061124283407458607006060194830551364867021020364708470807422704371893706965688795617928713045224516842027402021966415605280335061293558739079393524404092584248380607177444609964035221891022961909032569042381374492494906892314330884224399631396391545854065286326468807581148748371408284176455226386313520264894016262494802388568231599102952620337126449279901938211134518446387544516391239377974190576649911764237637722282802318465738050121277809680315691477264910257503508758792248110223544524410872448565700755187132146592093548504552829170749596775404450779494836371756062326925757412813110241910373338080434325310884694831555729402265394972913817581338619457057799561808755951413644907613109617155928376585840036489374076822257523935988731081689667688287403837192827690431514106997678303819085690713091931340846019511147482766350724676534922040058626677632935516631939622498979912708004465982264899125226813124300528104995058595676527123591494442612554437618645029202881358582871789577224116380815161831603129728796987480139828621645629196153096358337313619724773332353025466571196902611237380629030242904275794549030022660847446513161741691916851746464945459696005330885252792083472495235473110674109099223541055506299687642153951249355986311346661725116890785633328935569150449485189113488301876365100638502565916433021928565596263914382895068324838727165616560111531517055222955765944972454788815532316417453267167978861141165355597588331979638070962998880767303616940317736448140427867784251232449974693421348217179595190698204602997172001174857303889719205597414742453011135869766256607770970225633261701108463784795555258504578058879440756064974127974530918418405207558526462208821483646754652237609210787539190454684852349759986044943322828073120679922402477507514105890774627334319091255451352225329275913842047384603056163154236552935312278389759446515787337343463172280001031380425481404022090580405056003860937403435068863081434683848900708938565050027569059678069404698435184535134141031615133683043714786642925389717165978629010728400758939700388317742648163725113277369926827709465342583596111881955092462062153978121197244762623771534452048069819082524943963962251113831177428978535825590832490480497516047104257569753442551515779815600370847230603484753977513688390404316017486248871339311818523029425425676202485688393970836748788453789172574145155917919035398535077200900594979352939459631213445503368260690059828717723533375221941915547303742062343262892968397015058892191112049249864792053410872349115430987182160055762209075732304626106597744947658346313025598636315029959672352476943975462530206788193304372284800209305354155640664838569378144603138697563459200233462606995955513484754147891180830329816421587452922952678937925647752029052675349356673744293182673374571642465407748267901046778759085408130531447176455869894169668940436489952465247443988349583871206296485413357553813419500498743813369062703973874586604296871595820715766599826607317005624465541763024501349159567288942619746144496908671655859782729228702723774835097362901019130417812735773037781804081589136005207315806941034305003184349342360269244733060013861119781774472669608928321052543116496033420102032603863672532889648333405862204843616575362001468405476649666473566979572953394809138263703324220930839366954980688240491622063147911494642042500022450413425558561937442905257252436320054487441524307305215070491020434076572476865095751174125413729531644521765577235348601821566833352520532830000108344008762266843817023235605645158256954177359197813649975559601912567744942717986360045847405209290089397315276024304951653864431388147876977541478757432610159879709758855625806766197973098472460769484821127948427976536607055051639104415022554420329721292033009353356687294595912327965886376486894188433640548494009574965791657687213927330153555097865114767947399690623184878377515462613823651665956337209345708208301840482797005728071432925727577436229587047361641609731817241594204270366066404089740245521530725227388637241859646455223673260411164598464020010216920823315155388821071527191267876531795071908204525100447821291318544054814494151867114207103693891129125012750853466337717749376016543454696390042711129829255096830420665725364279472200020835313883708781649957189717629338794854271276882652003766325924561614868744897471519366219275665852462114457407010675380427564184440834805203838265052601698584060084788422421887856927897751810442805474427229455167420335686460609977973124950433321425205053675790499520783597650415379001132579536040655172654879022173595444151139429231648950663177813039057462082449171921311864129633704661406456900178942356738775523130952785912774533241855442484484493664210731348819180640189222317302156645813473186449997905781662091469870718039388885781280740226363602294114354869871402143572055947730892808653678920201935102605361567924483276749476117858316071865710310842200560259545115191391309119544447844361032741876102338843391687589233423790859841968266525610628751237572318491474951945985728897934981791761822652480408237128109790772638864286067917082288575852703470839714561619926247844794692794996845945632382702297364173503430783194115698247820013290851202878474805860188960045901745974055630732714487679085288867978809970695240681006625611440014983413580889737246844064948857074167687916413224205373654067330186392497910915474785959163865597507090581175924899502214799250945635582514315814464060134283490422798357939659258985200763845646681640732681928346007767285876284900068874564639274964415904034033672337814491597032941787294155061054129515400159393851663929325677429557549480046658273579653990940233543644649376827272541873627547532976808190325336141086433084237771738995221536763095302045902438694632702895293994483013577589081214884558493819874505920914067209522469096263076941753340983698859363700314973728977996360018626500174929290087931189997822963712306642297996163582572600112288983647651418045975770042120833949364659647336464289044499325396227091907373705772051322815957863227591912786054297862953188615559804728160710864132803585400160055575686855791785977899197902656592621283007225351401525973569300729015392211116868504740402172174442051738000251361000494534119324331668344243125963098812396962202358858395587831685194833126653577353244379935683215269177042249034574534858913812582681366908929476809052635560638119661306063936938411817713545929884317232912236262458868394202889981693561169865429884776513118227662526739978808816010470651542335015671353744817086234314662531190291040152262927104099285072418843329007277794754111637552176563589316326636049381218401837512818884771168975479483767664084842753623074019542183217985496260666590347925816342392670947839907062923166535037285019751324813803837070894638925470887039085723581006130628646664710006104352115778926613432214655311411882596942926284522109026688414975763341554921135581254616558078273470115814006008345762133130389987843270653719956709570847385786092649188858378739239165554263577301292243641604062551736892335636568854365851646207821875741724364525814143487632761341752707376754922276287782264765154315341585713773522730335403376364204258034257264749686217823666951353410677378421131371131987373222891805275062812277716412494412401207125954319991746574745892582613712825555535080404143944557295994554635608487251339462936358940832098964801619583130429720964794128539388996265368928263807677168759588502216464582430940165009688797366157733560316836710386895228270941509545222744002735499253670214715994056544813842186380128799900820933576320736369405991424263718294000613741900579513096298545330748197802568301089672873802234820488862973130369689882640657904781562389778485365025691064231795736025330908763271784911189748432246868086340383964176127605788646574472284824932687443062551220506955168464669477183681911432873544815836350548146411099960143390595799766290646881295025039150923633011076070632863317393378149693380247580035052789782755750928604039420506342939327064636161031822879248152679306862749237275631852225654266008556849497720285909150930495425967473648331437236349555448901598668408362176913559656039519670425368863482369587129462524759031776813184977588276576740482558136502103649585505703259219957675334264223783723586058509403583977103476670644788640831109650302565215607464019652716999732373465237173456595514559493098166644006211599349133180135150528651842178828026343325934755850761168697709125580056185683710540856081249519403148064618719402577663285267019698387567561524696759028106864896869293315954352097687527137201616160931174250199709289684940034696242325688410665113304377412256176258658941236728171145526423894512631717834790276921171452887352955019336759218908006048633737786728180610254782570436788449503518925787499836694785908612975543084122677060954347612133717433156783790162012337237023338316414706428592185977610158232721997915062871868186750981665537745013020880333904353639770263363809098526494532628146558065546504823486429495390613257400496912888340518222933644476683855037967975809619983575807027759535968788226194659612223044549275600274955168583542582295336042834426318478068825395450746691877897765406038432512843812811316856204608617289408229658626174420766920297427930088129519854678713548623236610413216581279267151545961594352593456757445992307889205519540082316409719591250025455237503106735639748835542480449681383030671851931491335789202123605308199952020584503423499932150962634977812456658304680581824563524814625849331926195406884818446445248429486063016169476663242625231476322371109695369483824482316410396224507675405614287468267835723704895606990652792688455844512046654853378534026646645042339638488257719874953611300494215593735545211926186721478265416885604094928290056616883807637656690510740892510549165222968878676968631652514917701499900066637344546120262780701925698706225540928945194718778004306130021828287425867048748480826948573444778244078734102710824870269523830804910960482013901294024631244800159336670212658317677879752965963472576894326540435889267293950687860830626266263287392087327302547910099932113388977807814336728791448768373686467748528777737403547472871644217767820712964506270880978637928144071192505141148004907055608097229299792441471062852247029870699869227676341773513258602908903875707454368077876422385333700692089616351009233587303986543906071880952557553380364725895007306772122528078179471056481171378557451057691044322925429024149433588396093679321361696954251299731031032804436954501929843820842383121265825740594509426942777307124802176915781835720087170538773256017987133005505911377823841791640280841409623820847637393013930778428554545222367559824666250608754284876104145661362227642405914304455580856318180935230407793891614902116292400515074914068443203230365609954878620999194306564455332547135557365318516011700321550690787716752062881527885897149410320986984083048966524351030502444679931779147659103428949129054120361601695671222140806369405940304552186212879933092856231022418446365289097444640151986623183881962444822590783585914043686193019041458962693878907034982169868696934448086213990534591792826654304798207219634134755646525483143771156678459077797196510772468000293581546267646310224279007313631352522067062951125935874473134186492497282784796644585448962932905262058065248588707020879389134476083344653170939242408249328008915731319541348311820927752486880548733943315867562666122179355051190609992911379445634995627391898459029021713155706096267881673302940198464237390445098028030948975981259252055850973537436556825780313681902007151675693827281818824587541710721180806556448039122504537089422695358382192535075692834095639859265599740391316709290043996275976830375217503360879028295673068862263077729733533853682668734519035709709687322323738300494090123239274318759046526327095178406267264828893646896593219169521106361729757074376148061601331104911692271318609404145014842866423634716982892418180484365230538864559809839273836490685480823014267803143937440431807822678779494006206489151248952516543005634448375046751754207043313372486870633237561645232360481932024377596890914783372179553676992603235715185513391098402739063753280702313301755754269396202629423910945323537910125948964941812563672992967084250667599803456273455598559628512281414582556024841783305645240508450065988755987518601335860624932784487772006842296591945516539562982960591610046578907214842054861830418175604559815168088031783080261445994444677918012432146400983610678683412974872596729258786806223080115822026289014364459002301645823666709265571264559925790622304745235625575111770791512002789380975775468546121017307522799241407026308137792971909461413145802081087738121624539858769697371425881836152605069380926917712087321915005831977113322793572385071940612761291872572099404930250277748156614021327434743881966413330052634229082906400927944924808556131183440161804801357032507836323938921567643159620442612809700944107776130638909071294456394056601559246025454204771186140420155233371270501377121034570009578009389265329385720478576508777149663403003562380595757191609382171312222810465858388943507176431939973012661591423837170284400120399485880996231859472474858776584355077006934099220340378772192728370301380838144394114984971730766162961342059105014814283949700695951676939041557902856356911055547312684571497449635320554677940775184056667637222969090346128706829887104278761090090999160443821794511763620835379716161833124364431267855435550800507986124664397724135502128238026726719914989727248512981287283697489276420792868666970177259794407858155909332508554131299946581118527691652464790819119384233275897699573012098103009171001695718791616942270079528915191912521053891838538959315167400505723817401030621004380243011187977704252328073236575129609372456053680037516596164236147709330391224409752871732067976128120428026739256557305675931512645750047875756531854825821411574030473147492511910835615765732002546109686701890307648531373832912682481741181359032826625082549313211431478953352317043989053928534946642886074268371824902498092479487226633686823799580875637040808655649321905489637785549531167397935270799470452399153297534358690514105864096534514182896474439367182852711843560799285895978176543950113088848419163516673213692860830956744502801800373716458009168082972708715609185038654053436660045504985624687376022557041595800250174095361839287643458003670864954057941720085136357127163768323493134230703821274484501440529541695374381945459456533165140990993722722801019654652726227831512103467686166826131471843610025517863247950150022953695466317739589344131481485834694374523981159954666071205997794363440185078360899108948073419633939259318973940943110042116729120199722626609871927014024105805515315100109804996044147291039451030312664114726736839973315035036742741546992633165270432940675237449075056739508929674779115800864399992564817208847429250821546279856079127768611946086210349405535850134472190244543824521089284409498132717010673966471114931896789977661595488186193176900175027901783824624387873831483279500879026433992577026588005849778984624295660321276945810824348129690840972550671054732471317254997191901039553305847040728081693158626093886019147689944137673621432083607375131574376316754666479186753896571555100850626810005119827486807780592667765654100834778571024250133253391587384761024129794736751001163498977803745930025457609870671092153597115178252014281216647543034075128600240297038428615984289816602143429849088917359682192284469123035904329877231843309914187264674607558318725713138832356015809009594182530207799397648462597901883341793830920965841463574411985878296475850943053008148341821747826603773762252997703468752903517310792083220038080809212164346586817989810504274375385786789186350517717501606531826406928883250135919517178537687865881752366421534010961295763074762648070312757365787762352859057153932484576503944390496668087711899192498933896524852395536795827530614167131757915756386606004839994179548705868209201195154952031294562451315422506574858629161606523796643010172693950282294667489681746821163996794950294284013099235901278250437428192557634533217576162292751110598368271567229778620053722932314082887058749444060116236521627717558503013451471452765841864277071769968435499620257547431811994883385806759692359580622165832464092095350648357935817742903018315351290014321495518177456908388719320697769695657771754499149911431368950836160692539606469893374870942933219185601299108564470256257163505508620689240297589684714283678684735455533583477652536156578189996983068654671736445996343136468195427420490472433064675001442697508322369013083895492637066778406531328664886080129513771720847581157719491012345141774941482773580041432667332379617716965698582785832300505265883502247868050648201444570593197343382923860072601696510903258980909912837652275381493529845099414966933862815568031306981064525192703818515872648691762563239441425216118427769145067718411735714396681005615483952443154944864238384298900399826113322468963346522104692545137969276009719645338955332105584245640187448611050959111766828942711640054010503770420346052521318228045892998637903572350665108782350043349942391285236308896510989246641056331584171142885304143772286629832318970869030400301325951476774237516158840915838059151673504519131178193943428482922272304061422582078027829148070426761629302539228321084917759984200595105312164731818409493139800444072847325902609169730998153853939031280878823902948001579008000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "factorial_rec(10000)",
"execution_count": 12,
"outputs": [
{
"output_type": "error",
"ename": "RecursionError",
"evalue": "maximum recursion depth exceeded in comparison",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRecursionError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-12-612a80d79466>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfactorial_rec\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10000\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m<ipython-input-5-fcd35d6dc97f>\u001b[0m in \u001b[0;36mfactorial_rec\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfactorial_rec\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"... last 1 frames repeated, from the frame below ...\n",
"\u001b[0;32m<ipython-input-5-fcd35d6dc97f>\u001b[0m in \u001b[0;36mfactorial_rec\u001b[0;34m(n)\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfactorial_rec\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded in comparison"
]
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "%%timeit\nfactorial_rec(100)",
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"text": "29.8 µs ± 656 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "%%timeit\nfactorial(100)",
"execution_count": 9,
"outputs": [
{
"output_type": "stream",
"text": "9.79 µs ± 256 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "C_n_k(10, 3)",
"execution_count": 166,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 166,
"data": {
"text/plain": "120"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "x = 5",
"execution_count": 167,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "x",
"execution_count": 170,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 170,
"data": {
"text/plain": "7"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "x = 7",
"execution_count": 169,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_list = [2, 3, 10, 65, 123]",
"execution_count": 14,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "for i, element in enumerate(my_list):\n print(\"element\", element, \"has index\", i)",
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"text": "element 2 has index 0\nelement 3 has index 1\nelement 10 has index 2\nelement 65 has index 3\nelement 123 has index 4\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "list(enumerate(my_list))",
"execution_count": 16,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 16,
"data": {
"text/plain": "[(0, 2), (1, 3), (2, 10), (3, 65), (4, 123)]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "A = {1, 2, 3, 4}\nB = {3, 4, 10, 20, 40}",
"execution_count": 17,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "A & B",
"execution_count": 18,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 18,
"data": {
"text/plain": "{3, 4}"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "A | B",
"execution_count": 19,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 19,
"data": {
"text/plain": "{1, 2, 3, 4, 10, 20, 40}"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list = [1, 1, 2, 3, 3, 3, 3, 4]\nset(my_list)",
"execution_count": 20,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 20,
"data": {
"text/plain": "{1, 2, 3, 4}"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "f = open(\"test.txt\")\nfor line in f:\n print(line.rstrip())\nf.close()",
"execution_count": 23,
"outputs": [
{
"output_type": "stream",
"text": "Hello, World!\nФЫВА ПРОЛДЖЭ\nOkay...\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "\" asdj lasd lj asd \".strip()",
"execution_count": 24,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 24,
"data": {
"text/plain": "'asdj lasd lj asd'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "print(\"Hello\")\nprint(\"World\")",
"execution_count": 22,
"outputs": [
{
"output_type": "stream",
"text": "Hello\nWorld\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "f = open(\"test.txt\")\nlines = f.readlines()\nprint(lines)\nf.close()",
"execution_count": 26,
"outputs": [
{
"output_type": "stream",
"text": "['Hello, World!\\n', 'ФЫВА ПРОЛДЖЭ\\n', 'Okay...\\n']\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "with open(\"test.txt\") as f:\n lines = f.readlines()\nprint(lines)",
"execution_count": 29,
"outputs": [
{
"output_type": "stream",
"text": "['Hello, World!\\n', 'ФЫВА ПРОЛДЖЭ\\n', 'Okay...\\n']\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "with open(\"test.txt\") as f:\n for line in f:\n print(line)\n print(\"Once again\")\n for line in f:\n print(line)\n print(\"That's all\")",
"execution_count": 33,
"outputs": [
{
"output_type": "stream",
"text": "Hello, World!\n\nФЫВА ПРОЛДЖЭ\n\nOkay...\n\nOnce again\nThat's all\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "with open(\"test.txt\", encoding=\"cp1251\") as f:\n everything = f.read()",
"execution_count": 46,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "print(everything)",
"execution_count": 47,
"outputs": [
{
"output_type": "stream",
"text": "Hello, World!\nФЫВА ПРОЛДЖЭ\nOkay...\n\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "with open(\"other_test.txt\", \"w\") as f:\n print(\"Hello\", file=f)\n print(12, 3,56, file=f)",
"execution_count": 36,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "with open(\"other_test.txt\") as f:\n print(\"\".join(f))",
"execution_count": 37,
"outputs": [
{
"output_type": "stream",
"text": "Hello\n12 3 56\n\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "s = \"Hello, \\n \\t this is a test\"\nwords = s.split()",
"execution_count": 41,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "words",
"execution_count": 42,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 42,
"data": {
"text/plain": "['Hello,', 'this', 'is', 'a', 'test']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "s.split(\",\")",
"execution_count": 44,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 44,
"data": {
"text/plain": "['Hello', ' \\n \\t this is a test']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "\"--\".join([\"one\", \"two\", \"three\"])",
"execution_count": 45,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 45,
"data": {
"text/plain": "'one--two--three'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "print(\"A\", \"B\")",
"execution_count": 48,
"outputs": [
{
"output_type": "stream",
"text": "A B\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "s = \"0\"\ntry:\n x = float(s)\n print(\"float: \", x)\n print(1/x)\nexcept ValueError:\n print(s,\"is not float number\")\nexcept ZeroDivisionError:\n print(\"cannot divide by 0\")",
"execution_count": 55,
"outputs": [
{
"output_type": "stream",
"text": "float: 0.0\ncannot divide by 0\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "# не делайте так\ntry:\n pass\n # ..\nexcept:\n pass\n",
"execution_count": 57,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "import pandas as pd",
"execution_count": 58,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "df = pd.DataFrame({'x': [1, 2, 3], 'y': [12, 15, 17]})",
"execution_count": 59,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df",
"execution_count": 60,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 60,
"data": {
"text/plain": " x y\n0 1 12\n1 2 15\n2 3 17",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>x</th>\n <th>y</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>1</td>\n <td>12</td>\n </tr>\n <tr>\n <th>1</th>\n <td>2</td>\n <td>15</td>\n </tr>\n <tr>\n <th>2</th>\n <td>3</td>\n <td>17</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "df = pd.DataFrame([[1, 2], [4, 5], [8, 9]], \n columns=('x', 'y'),\n index=('a', 'b', 'c')\n )",
"execution_count": 76,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df",
"execution_count": 77,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 77,
"data": {
"text/plain": " x y\na 1 2\nb 4 5\nc 8 9",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>x</th>\n <th>y</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>a</th>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>b</th>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>c</th>\n <td>8</td>\n <td>9</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "df.to_csv(\"sample.csv\")",
"execution_count": 78,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "with open(\"sample.csv\") as f:\n print(\"\".join(f))",
"execution_count": 79,
"outputs": [
{
"output_type": "stream",
"text": ",x,y\na,1,2\nb,4,5\nc,8,9\n\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df.loc['a']",
"execution_count": 80,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 80,
"data": {
"text/plain": "x 1\ny 2\nName: a, dtype: int64"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df.iloc[0]",
"execution_count": 81,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 81,
"data": {
"text/plain": "x 1\ny 2\nName: a, dtype: int64"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df['x']",
"execution_count": 82,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 82,
"data": {
"text/plain": "a 1\nb 4\nc 8\nName: x, dtype: int64"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "df = pd.read_csv(\"sample.csv\", index_col=0)",
"execution_count": 89,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df",
"execution_count": 90,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 90,
"data": {
"text/plain": " x y\na 1 2\nb 4 5\nc 8 9",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>x</th>\n <th>y</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>a</th>\n <td>1</td>\n <td>2</td>\n </tr>\n <tr>\n <th>b</th>\n <td>4</td>\n <td>5</td>\n </tr>\n <tr>\n <th>c</th>\n <td>8</td>\n <td>9</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from IPython.core.display import HTML\nHTML('<a href=\"http://example.com\">link</a>')",
"execution_count": 93,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 93,
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": "<a href=\"http://example.com\">link</a>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "HTML(\"\"\"<p>Это абзац со \n<a href='https://hse.ru/'>ссылкой</a>.</p>\n<ol>\n <li>Раз</li>\n <li>Два</li>\n <li>Три</li>\n</ol>\n<ul>\n <li>Раз</li>\n <li>Два</li>\n <li>Три</li>\n</ul>\n<table>\n <tr><th>1</th><th>2</th></tr>\n <tr><td>Раз</td><td>Два</td></tr>\n <tr><td>Три</td><td>Четыре</td></tr>\n</table>\n\"\"\")",
"execution_count": 101,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 101,
"data": {
"text/plain": "<IPython.core.display.HTML object>",
"text/html": "<p>Это абзац со \n<a href='https://hse.ru/'>ссылкой</a>.</p>\n<ol>\n <li>Раз</li>\n <li>Два</li>\n <li>Три</li>\n</ol>\n<ul>\n <li>Раз</li>\n <li>Два</li>\n <li>Три</li>\n</ul>\n<table>\n <tr><th>1</th><th>2</th></tr>\n <tr><td>Раз</td><td>Два</td></tr>\n <tr><td>Три</td><td>Четыре</td></tr>\n</table>\n"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "from bs4 import BeautifulSoup",
"execution_count": 102,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "html = \"\"\"\n<p>Это абзац со \n<a href='https://hse.ru/'>ссылкой</a>.</p>\n<p>Это другой абзац</p>\n\"\"\"",
"execution_count": 113,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup = BeautifulSoup(html, 'lxml')",
"execution_count": 114,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup",
"execution_count": 115,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 115,
"data": {
"text/plain": "<html><body><p>Это абзац со \n<a href=\"https://hse.ru/\">ссылкой</a>.</p>\n<p>Это другой абзац</p>\n</body></html>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "type(soup)",
"execution_count": 116,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 116,
"data": {
"text/plain": "bs4.BeautifulSoup"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup.find(\"p\")",
"execution_count": 117,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 117,
"data": {
"text/plain": "<p>Это абзац со \n<a href=\"https://hse.ru/\">ссылкой</a>.</p>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "a = soup.find(\"p\").find(\"a\")",
"execution_count": 110,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "a",
"execution_count": 111,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 111,
"data": {
"text/plain": "<a href=\"https://hse.ru/\">ссылкой</a>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "a['href']",
"execution_count": 112,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 112,
"data": {
"text/plain": "'https://hse.ru/'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup.find_all(\"p\")[1]",
"execution_count": 119,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 119,
"data": {
"text/plain": "<p>Это другой абзац</p>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup.p",
"execution_count": 120,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 120,
"data": {
"text/plain": "<p>Это абзац со \n<a href=\"https://hse.ru/\">ссылкой</a>.</p>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup(\"p\")",
"execution_count": 128,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 128,
"data": {
"text/plain": "[<p>Это абзац со \n <a href=\"https://hse.ru/\">ссылкой</a>.</p>, <p>Это другой абзац</p>]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "html = \"\"\"\n<html><body>\n<ol>\n<li><a href=\"one.html\">This is first page</a></li>\n<li><a href=\"two.html\">This is second page</a></li>\n<li><a href=\"last.html\">The last one</a></li>\n<li>Item without a</li>\n<li><a>without href</a></li>\n</ol>\n<p><a href=\"other.html\">Some other link</a></p>\n</body>\n</html>\n\"\"\"",
"execution_count": 163,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# задача: получить список адресов, на которые есть ссылки внутри\n# элементов списка\n# План:\n# 1. Создать из строки html объект BeautifulSoup\n# 2. Найти в нём тег <ol>\n# 3. Внутри тега <ol> найти все теги <li>\n# 4. Внутри каждого тега <li> найти тег <a>\n# 5. Взять у полученного тега <a> атрибут href, \n# положить его в список",
"execution_count": 164,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup = BeautifulSoup(html, 'lxml')\nitems = soup.find(\"ol\").find_all(\"li\") # soup.ol(\"li\")",
"execution_count": 165,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "hrefs = []\nfor li in items:\n a = li.find(\"a\")\n if a and 'href' in a.attrs:\n hrefs.append(a['href'])",
"execution_count": 187,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "a.attrs",
"execution_count": 188,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 188,
"data": {
"text/plain": "{}"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_list = []\nif not my_list:\n print(\"list is empty\")",
"execution_count": 162,
"outputs": [
{
"output_type": "stream",
"text": "list is empty\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "hrefs = [li.a['href'] for li in soup.ol(\"li\") \n if li.a and 'href' in li.a.attrs]\nhrefs",
"execution_count": 191,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 191,
"data": {
"text/plain": "['one.html', 'two.html', 'last.html']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "html = \"\"\"\n<p>Hello</p>\n\"\"\"",
"execution_count": 147,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup = BeautifulSoup(html, 'lxml')",
"execution_count": 149,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "a = soup.p.a\nif not a:\n print(\"No a\")",
"execution_count": 153,
"outputs": [
{
"output_type": "stream",
"text": "No a\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "my_dict = {'a': 1, 'b': 2}",
"execution_count": 167,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "my_dict.get('asf', 0)",
"execution_count": 176,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 176,
"data": {
"text/plain": "0"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "'a' in my_dict",
"execution_count": 185,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 185,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "'c' in my_dict",
"execution_count": 186,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 186,
"data": {
"text/plain": "False"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "a.string",
"execution_count": 195,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 195,
"data": {
"text/plain": "'without href'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "html = \"\"\"\n<html><body>\n<ol>\n<li><a href=\"one.html\"><b>This is first </b><b>page</b></a></li>\n<li><a href=\"two.html\">This is second page</a></li>\n<li><a href=\"last.html\">The last one</a></li>\n<li>Item without a</li>\n<li><a>without href</a></li>\n</ol>\n<p>Test <a href=\"other.html\">Some other link</a> test</p>\n</body>\n</html>\n\"\"\"\nsoup = BeautifulSoup(html, 'lxml')",
"execution_count": 213,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "list(soup.p.children)",
"execution_count": 210,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 210,
"data": {
"text/plain": "['Test ', <a href=\"other.html\">Some other link</a>, ' test']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup.p.string",
"execution_count": 207,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup.li.string",
"execution_count": 214,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "print(soup.ol.text)",
"execution_count": 219,
"outputs": [
{
"output_type": "stream",
"text": "\nThis is first page\nThis is second page\nThe last one\nItem without a\nwithout href\n\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "'hello' in 'hello, world'",
"execution_count": 220,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 220,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "',' in 'hello, world'",
"execution_count": 221,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 221,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "'.' in 'hello, world'",
"execution_count": 222,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 222,
"data": {
"text/plain": "False"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "s = \"Hello, world\"",
"execution_count": 223,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "s.find(\",\")",
"execution_count": 226,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 226,
"data": {
"text/plain": "5"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "s.startswith(\"Hello, \")",
"execution_count": 227,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 227,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "html = \"\"\"\n<html><body>\n<ol>\n<li><a href=\"one.html\"><b>This is first </b><b>page</b></a></li>\n<li><a href=\"two.html\">This is second page</a></li>\n<li><a href=\"last.html\">The last one</a></li>\n<li>Item without a</li>\n<li><a>without href</a></li>\n</ol>\n<p>Test <a href=\"other.html\">Some other link</a> test</p>\n</body>\n</html>\n\"\"\"\nsoup = BeautifulSoup(html, 'lxml')\n# Найти первую ссылку, содержащую текст \"last\"",
"execution_count": 228,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "last_a = None\nfor a in soup(\"a\"):\n if 'last' in a.text:\n last_a = a\n break\nprint(last_a['href'])",
"execution_count": 237,
"outputs": [
{
"output_type": "stream",
"text": "last.html\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "last_a = next((a for a in soup('a') if 'lastttt' in a.text),\n None)\nprint(last_a)",
"execution_count": 236,
"outputs": [
{
"output_type": "stream",
"text": "None\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "last_a = [a for a in soup('a') if 'last' in a.text][0]\nprint(last_a)",
"execution_count": 240,
"outputs": [
{
"output_type": "stream",
"text": "<a href=\"last.html\">The last one</a>\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "import requests",
"execution_count": 241,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "r = requests.get(\"https://ru.wikipedia.org/wiki/Екатеринбург\")",
"execution_count": 291,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from urllib.request import quote",
"execution_count": 298,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "quote(\"Пермь\")",
"execution_count": 299,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 299,
"data": {
"text/plain": "'%D0%9F%D0%B5%D1%80%D0%BC%D1%8C'"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "if r:\n text = r.text",
"execution_count": 293,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "soup = BeautifulSoup(text, 'lxml')",
"execution_count": 294,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def get_density(soup):\n for tr in soup.find(\"table\", \n class_=\"infobox\")(\"tr\"):\n if tr.th and 'Плотность' in tr.th.text:\n print(tr.td)\n s = tr.td.p.string\n return (float(\n s.replace(\"чел./км²\", \"\")\n .rstrip()\n .replace(\" \", \"\")\n .replace(',', '.')))",
"execution_count": 328,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "s.find(\"\\xa0\")",
"execution_count": 274,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 274,
"data": {
"text/plain": "7"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "s.split()",
"execution_count": 275,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 275,
"data": {
"text/plain": "['1310,53', 'чел./км²']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "selector = \"#mw-pages a\"\nr = requests.get(\"https://ru.wikipedia.org/wiki/Категория:Города-миллионеры_России\")\nsoup = BeautifulSoup(r.text, 'lxml')",
"execution_count": 305,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "cities = soup.select(selector)",
"execution_count": 313,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# pip install robobrowser\n\nfrom robobrowser import browser",
"execution_count": 317,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "br = browser.RoboBrowser(parser='lxml')",
"execution_count": 320,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "br.open(\"https://ru.wikipedia.org/wiki/Категория:Города-миллионеры_России\")\nlinks = br.parsed.select(selector)[1:]\ndensities = []\nfor link in links[:]:\n br.follow_link(link)\n densities.append(get_density(br.parsed))\n br.back()\ndensities",
"execution_count": 332,
"outputs": [
{
"output_type": "stream",
"text": "<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>1181,8 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>1743,14 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>3110,91 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>1915 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>2765 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>4833,36 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>3078 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>3170,2 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>2056,89 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>1310,53 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>2583,92 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>2160,28 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>3764,49 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>1575,81 чел./км²</p>\n</td>\n<td class=\"\" style=\"width:50%; text-align:left; padding-left:0.5em; padding-right:0.5em;\">\n<p>2262 чел./км²</p>\n</td>\n",
"name": "stdout"
},
{
"output_type": "execute_result",
"execution_count": 332,
"data": {
"text/plain": "[1181.8,\n 1743.14,\n 3110.91,\n 1915.0,\n 2765.0,\n 4833.36,\n 3078.0,\n 3170.2,\n 2056.89,\n 1310.53,\n 2583.92,\n 2160.28,\n 3764.49,\n 1575.81,\n 2262.0]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "links",
"execution_count": 336,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 336,
"data": {
"text/plain": "[<a href=\"/wiki/%D0%92%D0%BE%D0%BB%D0%B3%D0%BE%D0%B3%D1%80%D0%B0%D0%B4\" title=\"Волгоград\">Волгоград</a>,\n <a href=\"/wiki/%D0%92%D0%BE%D1%80%D0%BE%D0%BD%D0%B5%D0%B6\" title=\"Воронеж\">Воронеж</a>,\n <a href=\"/wiki/%D0%95%D0%BA%D0%B0%D1%82%D0%B5%D1%80%D0%B8%D0%BD%D0%B1%D1%83%D1%80%D0%B3\" title=\"Екатеринбург\">Екатеринбург</a>,\n <a href=\"/wiki/%D0%9A%D0%B0%D0%B7%D0%B0%D0%BD%D1%8C\" title=\"Казань\">Казань</a>,\n <a href=\"/wiki/%D0%9A%D1%80%D0%B0%D1%81%D0%BD%D0%BE%D1%8F%D1%80%D1%81%D0%BA\" title=\"Красноярск\">Красноярск</a>,\n <a href=\"/wiki/%D0%9C%D0%BE%D1%81%D0%BA%D0%B2%D0%B0\" title=\"Москва\">Москва</a>,\n <a href=\"/wiki/%D0%9D%D0%B8%D0%B6%D0%BD%D0%B8%D0%B9_%D0%9D%D0%BE%D0%B2%D0%B3%D0%BE%D1%80%D0%BE%D0%B4\" title=\"Нижний Новгород\">Нижний Новгород</a>,\n <a href=\"/wiki/%D0%9D%D0%BE%D0%B2%D0%BE%D1%81%D0%B8%D0%B1%D0%B8%D1%80%D1%81%D0%BA\" title=\"Новосибирск\">Новосибирск</a>,\n <a href=\"/wiki/%D0%9E%D0%BC%D1%81%D0%BA\" title=\"Омск\">Омск</a>,\n <a href=\"/wiki/%D0%9F%D0%B5%D1%80%D0%BC%D1%8C\" title=\"Пермь\">Пермь</a>,\n <a href=\"/wiki/%D0%A0%D0%BE%D1%81%D1%82%D0%BE%D0%B2-%D0%BD%D0%B0-%D0%94%D0%BE%D0%BD%D1%83\" title=\"Ростов-на-Дону\">Ростов-на-Дону</a>,\n <a href=\"/wiki/%D0%A1%D0%B0%D0%BC%D0%B0%D1%80%D0%B0\" title=\"Самара\">Самара</a>,\n <a href=\"/wiki/%D0%A1%D0%B0%D0%BD%D0%BA%D1%82-%D0%9F%D0%B5%D1%82%D0%B5%D1%80%D0%B1%D1%83%D1%80%D0%B3\" title=\"Санкт-Петербург\">Санкт-Петербург</a>,\n <a href=\"/wiki/%D0%A3%D1%84%D0%B0\" title=\"Уфа\">Уфа</a>,\n <a href=\"/wiki/%D0%A7%D0%B5%D0%BB%D1%8F%D0%B1%D0%B8%D0%BD%D1%81%D0%BA\" title=\"Челябинск\">Челябинск</a>]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "cities = [link.string for link in links]",
"execution_count": 334,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "cities",
"execution_count": 335,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 335,
"data": {
"text/plain": "['Волгоград',\n 'Воронеж',\n 'Екатеринбург',\n 'Казань',\n 'Красноярск',\n 'Москва',\n 'Нижний Новгород',\n 'Новосибирск',\n 'Омск',\n 'Пермь',\n 'Ростов-на-Дону',\n 'Самара',\n 'Санкт-Петербург',\n 'Уфа',\n 'Челябинск']"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "df = pd.DataFrame({'city': cities,\n 'density': densities},\n index = range(1, len(cities) + 1)\n )",
"execution_count": 340,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df",
"execution_count": 341,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 341,
"data": {
"text/plain": " city density\n1 Волгоград 1181.80\n2 Воронеж 1743.14\n3 Екатеринбург 3110.91\n4 Казань 1915.00\n5 Красноярск 2765.00\n6 Москва 4833.36\n7 Нижний Новгород 3078.00\n8 Новосибирск 3170.20\n9 Омск 2056.89\n10 Пермь 1310.53\n11 Ростов-на-Дону 2583.92\n12 Самара 2160.28\n13 Санкт-Петербург 3764.49\n14 Уфа 1575.81\n15 Челябинск 2262.00",
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>city</th>\n <th>density</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>Волгоград</td>\n <td>1181.80</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Воронеж</td>\n <td>1743.14</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Екатеринбург</td>\n <td>3110.91</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Казань</td>\n <td>1915.00</td>\n </tr>\n <tr>\n <th>5</th>\n <td>Красноярск</td>\n <td>2765.00</td>\n </tr>\n <tr>\n <th>6</th>\n <td>Москва</td>\n <td>4833.36</td>\n </tr>\n <tr>\n <th>7</th>\n <td>Нижний Новгород</td>\n <td>3078.00</td>\n </tr>\n <tr>\n <th>8</th>\n <td>Новосибирск</td>\n <td>3170.20</td>\n </tr>\n <tr>\n <th>9</th>\n <td>Омск</td>\n <td>2056.89</td>\n </tr>\n <tr>\n <th>10</th>\n <td>Пермь</td>\n <td>1310.53</td>\n </tr>\n <tr>\n <th>11</th>\n <td>Ростов-на-Дону</td>\n <td>2583.92</td>\n </tr>\n <tr>\n <th>12</th>\n <td>Самара</td>\n <td>2160.28</td>\n </tr>\n <tr>\n <th>13</th>\n <td>Санкт-Петербург</td>\n <td>3764.49</td>\n </tr>\n <tr>\n <th>14</th>\n <td>Уфа</td>\n <td>1575.81</td>\n </tr>\n <tr>\n <th>15</th>\n <td>Челябинск</td>\n <td>2262.00</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df.set_index('city', inplace=True)",
"execution_count": 345,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df.loc['Казань']",
"execution_count": 347,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 347,
"data": {
"text/plain": "density 1915.0\nName: Казань, dtype: float64"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df.to_csv(\"densities.csv\")",
"execution_count": 348,
"outputs": []
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "# https://goo.gl/ethTcS",
"execution_count": 349,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "url = \"https://www.atsenergo.ru/nreport?fid=5BFC3D07A2950112E053AC103C8C1375\"",
"execution_count": 354,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "r = requests.get(url, stream=True)\npath = \"file.xls\"\nif r.status_code == 200:\n with open(path, 'wb') as f:\n for chunk in r:\n f.write(chunk)",
"execution_count": 355,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "import pandas as pd\ndf = pd.read_excel(\"file.xls\", skiprows=3, \n header=2)",
"execution_count": 15,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "df.mean()",
"execution_count": 18,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 18,
"data": {
"text/plain": "Unnamed: 1 11.500000\nГЭС 621.868815\nАЭС 2187.819933\nТЭС 1165.631370\nСЭС 10.976190\nВЭС 1.062500\nпрочие ВИЭ NaN\nГЭС.1 45.226339\nАЭС.1 2182.107500\nТЭС.1 751.235959\nСЭС.1 10.976190\nВЭС.1 1.062500\nпрочие ВИЭ.1 NaN\nГЭС.2 256.637351\nАЭС.2 2182.107500\nТЭС.2 906.660978\nСЭС.2 10.976190\nВЭС.2 1.062500\nпрочие ВИЭ.2 NaN\nГЭС.3 1174.416929\nАЭС.3 2187.911600\nТЭС.3 1362.008614\nСЭС.3 10.976190\nВЭС.3 1.062500\nпрочие ВИЭ.3 NaN\nUnnamed: 26 1509.733508\nUnnamed: 27 793.069897\nUnnamed: 28 780.091108\nUnnamed: 29 1255.844540\nUnnamed: 30 1157.049322\ndtype: float64"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
}
],
"metadata": {
"kernelspec": {
"name": "python3",
"display_name": "Python 3",
"language": "python"
},
"language_info": {
"name": "python",
"version": "3.6.1",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"file_extension": ".py"
},
"gist": {
"id": "bdf2cc3c4ad1e5be176324d15209b9f4",
"data": {
"description": "web scrapping day 2.ipynb",
"public": true
}
},
"_draft": {
"nbviewer_url": "https://gist.github.com/bdf2cc3c4ad1e5be176324d15209b9f4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment