1678 lines
435 KiB
Plaintext
1678 lines
435 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"id": "0ca448bb-efe0-4345-af99-6d7f4dbe9155",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Hello Dima\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(\"Hello Dima\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "9b3254aa-6deb-4d6b-92ac-83a2f0938822",
|
||
"metadata": {},
|
||
"source": [
|
||
"Поздаровался с собой у меня шиза,извините..."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"id": "a02ca182-241e-4afc-9bf4-74caab5c8056",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" Имя Возраст Баллы\n",
|
||
"0 Анна 21 89\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 4 entries, 0 to 3\n",
|
||
"Data columns (total 3 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Имя 4 non-null object\n",
|
||
" 1 Возраст 4 non-null int64 \n",
|
||
" 2 Баллы 4 non-null int64 \n",
|
||
"dtypes: int64(2), object(1)\n",
|
||
"memory usage: 228.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы\n",
|
||
"count 4.000000 4.000000\n",
|
||
"mean 22.500000 85.500000\n",
|
||
"std 1.290994 8.266398\n",
|
||
"min 21.000000 76.000000\n",
|
||
"25% 21.750000 80.500000\n",
|
||
"50% 22.500000 85.500000\n",
|
||
"75% 23.250000 90.500000\n",
|
||
"max 24.000000 95.000000\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Создадим DataFrame\n",
|
||
"data = {\n",
|
||
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 22, 23, 24],\n",
|
||
" \"Баллы\": [89, 76, 95, 82]\n",
|
||
"}\n",
|
||
"df = pd.DataFrame(data)\n",
|
||
"\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head())\n",
|
||
"print(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e7cd3715-be52-4bae-90ed-1fe1684d48b3",
|
||
"metadata": {},
|
||
"source": [
|
||
"Ничего не менял в pandas: работа с таблицами"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"id": "8af5b579-a41e-47d6-96a0-bf8e095a433f",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" Имя Возраст Баллы\n",
|
||
"0 Анна 21 89\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 4 entries, 0 to 3\n",
|
||
"Data columns (total 3 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Имя 4 non-null object\n",
|
||
" 1 Возраст 4 non-null int64 \n",
|
||
" 2 Баллы 4 non-null int64 \n",
|
||
"dtypes: int64(2), object(1)\n",
|
||
"memory usage: 228.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы\n",
|
||
"count 4.000000 4.000000\n",
|
||
"mean 22.500000 85.500000\n",
|
||
"std 1.290994 8.266398\n",
|
||
"min 21.000000 76.000000\n",
|
||
"25% 21.750000 80.500000\n",
|
||
"50% 22.500000 85.500000\n",
|
||
"75% 23.250000 90.500000\n",
|
||
"max 24.000000 95.000000\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>Имя</th>\n",
|
||
" <th>Возраст</th>\n",
|
||
" <th>Баллы</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>Анна</td>\n",
|
||
" <td>21</td>\n",
|
||
" <td>89</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>Борис</td>\n",
|
||
" <td>22</td>\n",
|
||
" <td>76</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>Виктор</td>\n",
|
||
" <td>23</td>\n",
|
||
" <td>95</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>Галина</td>\n",
|
||
" <td>24</td>\n",
|
||
" <td>82</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" Имя Возраст Баллы\n",
|
||
"0 Анна 21 89\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82"
|
||
]
|
||
},
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Создадим DataFrame\n",
|
||
"data = {\n",
|
||
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 22, 23, 24],\n",
|
||
" \"Баллы\": [89, 76, 95, 82]\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head())\n",
|
||
"print(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())\n",
|
||
"\n",
|
||
"df = pd.DataFrame(data)\n",
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "413d6e98-4303-4d8b-ad19-cc30e473521b",
|
||
"metadata": {},
|
||
"source": [
|
||
"Перенес df в поседнюю строчку"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"id": "70868cf0-1fc3-4db9-a7a2-08bbea55daab",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" Имя Возраст Баллы Новый столбец\n",
|
||
"0 Анна 21 89 97.9\n",
|
||
"1 Борис 22 76 83.6\n",
|
||
"2 Виктор 23 95 104.5\n",
|
||
"3 Галина 24 82 90.2\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 4 entries, 0 to 3\n",
|
||
"Data columns (total 4 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Имя 4 non-null object \n",
|
||
" 1 Возраст 4 non-null int64 \n",
|
||
" 2 Баллы 4 non-null int64 \n",
|
||
" 3 Новый столбец 4 non-null float64\n",
|
||
"dtypes: float64(1), int64(2), object(1)\n",
|
||
"memory usage: 260.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы Новый столбец\n",
|
||
"count 4.000000 4.000000 4.000000\n",
|
||
"mean 22.500000 85.500000 94.050000\n",
|
||
"std 1.290994 8.266398 9.093038\n",
|
||
"min 21.000000 76.000000 83.600000\n",
|
||
"25% 21.750000 80.500000 88.550000\n",
|
||
"50% 22.500000 85.500000 94.050000\n",
|
||
"75% 23.250000 90.500000 99.550000\n",
|
||
"max 24.000000 95.000000 104.500000\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"Новый столбец 0\n",
|
||
"dtype: int64\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Создадим DataFrame\n",
|
||
"data = {\n",
|
||
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 22, 23, 24],\n",
|
||
" \"Баллы\": [89, 76, 95, 82]\n",
|
||
"}\n",
|
||
"df = pd.DataFrame(data)\n",
|
||
"\n",
|
||
"\n",
|
||
"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
|
||
"\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head())\n",
|
||
"print(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "487cad39-57f6-4279-a6c2-fdfc29a9ed54",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавил Новый Столбец"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "4bb55070-61a5-4fa5-96f5-173a76d7f3b9",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" Имя Возраст Баллы Группа\n",
|
||
"0 Анна 21 89 A\n",
|
||
"1 Борис 22 76 B\n",
|
||
"2 Виктор 23 95 A\n",
|
||
"3 Галина 24 82 B\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 4 entries, 0 to 3\n",
|
||
"Data columns (total 4 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Имя 4 non-null object\n",
|
||
" 1 Возраст 4 non-null int64 \n",
|
||
" 2 Баллы 4 non-null int64 \n",
|
||
" 3 Группа 4 non-null object\n",
|
||
"dtypes: int64(2), object(2)\n",
|
||
"memory usage: 260.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы\n",
|
||
"count 4.000000 4.000000\n",
|
||
"mean 22.500000 85.500000\n",
|
||
"std 1.290994 8.266398\n",
|
||
"min 21.000000 76.000000\n",
|
||
"25% 21.750000 80.500000\n",
|
||
"50% 22.500000 85.500000\n",
|
||
"75% 23.250000 90.500000\n",
|
||
"max 24.000000 95.000000\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"Группа 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"Результат группировки и агрегации:\n",
|
||
" Возраст Баллы \n",
|
||
" mean max min mean\n",
|
||
"Группа \n",
|
||
"A 22.0 95 89 92.0\n",
|
||
"B 23.0 82 76 79.0\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Создадим DataFrame\n",
|
||
"data = {\n",
|
||
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 22, 23, 24],\n",
|
||
" \"Баллы\": [89, 76, 95, 82],\n",
|
||
" \"Группа\": [\"A\", \"B\", \"A\", \"B\"] \n",
|
||
"}\n",
|
||
"df = pd.DataFrame(data)\n",
|
||
"\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head())\n",
|
||
"print(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())\n",
|
||
"\n",
|
||
"\n",
|
||
"grouped_df = df.groupby(\"Группа\").agg({\n",
|
||
" \"Возраст\": \"mean\", \n",
|
||
" \"Баллы\": [\"max\", \"min\", \"mean\"] \n",
|
||
"})\n",
|
||
"\n",
|
||
"print(\"\\nРезультат группировки и агрегации:\")\n",
|
||
"print(grouped_df)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "8e90c223-fa54-410d-ba08-62de1742e592",
|
||
"metadata": {},
|
||
"source": [
|
||
"Применить .groupby() и .agg(), чтобы сгруппировать данные : Добавил новый столбец \"Группа\" , сортировка по этому столбцу с данными - по возросту и баллам"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "bdd053ce-41ec-489b-add3-1f6ae7696210",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" Имя Возраст Баллы\n",
|
||
"0 Анна 21 89\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 4 entries, 0 to 3\n",
|
||
"Data columns (total 3 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Имя 4 non-null object\n",
|
||
" 1 Возраст 4 non-null int64 \n",
|
||
" 2 Баллы 4 non-null int64 \n",
|
||
"dtypes: int64(2), object(1)\n",
|
||
"memory usage: 228.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы\n",
|
||
"count 4.000000 4.000000\n",
|
||
"mean 22.500000 85.500000\n",
|
||
"std 1.290994 8.266398\n",
|
||
"min 21.000000 76.000000\n",
|
||
"25% 21.750000 80.500000\n",
|
||
"50% 22.500000 85.500000\n",
|
||
"75% 23.250000 90.500000\n",
|
||
"max 24.000000 95.000000\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"Отфильтрованные данные (Возраст > 21):\n",
|
||
" Имя Возраст Баллы\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Создадим DataFrame\n",
|
||
"data = {\n",
|
||
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 22, 23, 24],\n",
|
||
" \"Баллы\": [89, 76, 95, 82]\n",
|
||
"}\n",
|
||
"df = pd.DataFrame(data)\n",
|
||
"\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head())\n",
|
||
"print(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())\n",
|
||
"\n",
|
||
"\n",
|
||
"filtered_df = df[df[\"Возраст\"] > 21]\n",
|
||
"\n",
|
||
"print(\"\\nОтфильтрованные данные (Возраст > 21):\")\n",
|
||
"print(filtered_df)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "fd522fba-4acb-4c27-9b5e-9b2017285edb",
|
||
"metadata": {},
|
||
"source": [
|
||
"Фильтр по условию возраст > 21 года"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "419004f2-314c-4d43-80ea-809dfd0c7b42",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Сумма элементов массива: 15\n",
|
||
"Среднее значение: 3.0\n",
|
||
"Медиана: 3.0\n",
|
||
"Стандартное отклонение: 1.4142135623730951\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"arr = np.array([1, 2, 3, 4, 5])\n",
|
||
"print(\"Сумма элементов массива:\", np.sum(arr))\n",
|
||
"print(\"Среднее значение:\", np.mean(arr))\n",
|
||
"print(\"Медиана:\", np.median(arr))\n",
|
||
"print(\"Стандартное отклонение:\", np.std(arr))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "7403b969-857e-4f3d-b48d-5f29084c1f97",
|
||
"metadata": {},
|
||
"source": [
|
||
"numpy: массивы и вычисления - ничего не менял"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "7669894d-eb8f-44e1-9940-7d8e3183e206",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Двумерный массив:\n",
|
||
"[[1 2]\n",
|
||
" [3 4]]\n",
|
||
"Сумма элементов массива: 15\n",
|
||
"Среднее значение: 3.0\n",
|
||
"Медиана: 3.0\n",
|
||
"Стандартное отклонение: 1.4142135623730951\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"arr = np.array([1, 2, 3, 4, 5])\n",
|
||
"arr2 = np.array([[1, 2], [3, 4]])\n",
|
||
"\n",
|
||
"print(\"Двумерный массив:\")\n",
|
||
"print(arr2)\n",
|
||
"print(\"Сумма элементов массива:\", np.sum(arr))\n",
|
||
"print(\"Среднее значение:\", np.mean(arr))\n",
|
||
"print(\"Медиана:\", np.median(arr))\n",
|
||
"print(\"Стандартное отклонение:\", np.std(arr))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "1bdf6dec-1c64-45b4-8876-d06f0bce5e56",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавил 2-уx мерный массив"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "d7e136fc-f6af-4c51-8d0d-6bb9edda4837",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Сумма элементов массива: 15\n",
|
||
"Среднее значение: 3.0\n",
|
||
"Медиана: 3.0\n",
|
||
"Стандартное отклонение: 1.4142135623730951\n",
|
||
"[0. 0.875 1.75 2.625 3.5 4.375 5.25 6.125 7. ]\n",
|
||
"[[-0.73829461 1.39168458]\n",
|
||
" [-1.1057303 -0.29817264]]\n",
|
||
"[ 95 110]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"arr = np.array([1, 2, 3, 4, 5])\n",
|
||
"arr2 = np.array([[1, 2], [3, 4],[ 5,6] , [7,8] , [9,10]])\n",
|
||
"\n",
|
||
"print(\"Сумма элементов массива:\", np.sum(arr))\n",
|
||
"print(\"Среднее значение:\", np.mean(arr))\n",
|
||
"print(\"Медиана:\", np.median(arr))\n",
|
||
"print(\"Стандартное отклонение:\", np.std(arr))\n",
|
||
"\n",
|
||
"print(np.linspace(0,7,9,111))\n",
|
||
"\n",
|
||
"\n",
|
||
"print(np.random.randn(2,2))\n",
|
||
"\n",
|
||
"print(np.dot(arr,arr2))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "b6cd6c24-5579-4b39-90b7-76ecbd10435a",
|
||
"metadata": {},
|
||
"source": [
|
||
"Использовать np.linspace(), np.random.randn(), np.dot()."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "d1d54ef6-7a86-45c2-bd83-59861f7765c6",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"x = np.linspace(0, 10, 100)\n",
|
||
"y = np.sin(x)\n",
|
||
"\n",
|
||
"plt.plot(x, y, label='sin(x)')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "9fa8567f-d908-44e8-ae92-f3cac3bbfa69",
|
||
"metadata": {},
|
||
"source": [
|
||
"Ничего не менял в matplotlib: построение графиков"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "d218a2e1-79fd-4c36-a2ee-cad1dc666e8a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"x = np.linspace(0, 10, 100)\n",
|
||
"y = np.sin(x)\n",
|
||
"\n",
|
||
"plt.plot(x, y, label='sin(x)',color = \"green\")\n",
|
||
"\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "9fa5688f-5224-4118-9a16-073ac525aa60",
|
||
"metadata": {},
|
||
"source": [
|
||
"Поменял цвет на зеленый"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"id": "89fb9e65-ebca-4faf-bdff-bfcae9d6fe39",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"x = np.linspace(0, 10, 100)\n",
|
||
"y = np.sin(x)\n",
|
||
"\n",
|
||
"plt.plot(x, y, label='sin(x)',color = \"green\")\n",
|
||
"plt.plot(x, np.cos(x), label='cos(x)',color = 'red')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.title(\"График косинуса\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "de3f68f6-d780-41bc-81cb-924ba042c3db",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавил 2 график cos красный"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"id": "f9ad4a1b-30ca-4878-85e6-e36b1d6c758e",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(array([1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0.,\n",
|
||
" 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,\n",
|
||
" 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]),\n",
|
||
" array([ 0. , 0.01, 0.02, ..., 9.98, 9.99, 10. ], shape=(1001,)),\n",
|
||
" <BarContainer object of 1000 artists>)"
|
||
]
|
||
},
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"x = np.linspace(0, 10, 100)\n",
|
||
"y = np.sin(x)\n",
|
||
"\n",
|
||
"\n",
|
||
"plt.plot(x, y, label='sin(x)',color = \"green\")\n",
|
||
"plt.plot(x, np.cos(x), label='cos(x)',color = 'red')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.title(\"График косинуса\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()\n",
|
||
"plt.bar(x , y , color = 'blue' , label = 'Таблица')\n",
|
||
"plt.scatter (x , y , color ='pink' , label = 'Точки')\n",
|
||
"plt.hist (x, bins = 1000 , color = 'yellow' , label = 'Незнаю')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "25f6794e-900d-4077-a0ed-2b99f217bb34",
|
||
"metadata": {},
|
||
"source": [
|
||
"Использовал bar(синий), scatter(Розовый), hist(Желтый)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"id": "f7bb52b6-f8c8-44d3-9600-e503022f4d4a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\n",
|
||
"\n",
|
||
"df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"] # догадайтесь откуда df и её содержимое взялось\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "948fb54f-4070-4a5b-8515-960eacd5196e",
|
||
"metadata": {},
|
||
"source": [
|
||
"Ничего не менял в seaborn: работа с графиками данных"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"id": "fb7021ce-0a4e-4b1d-9a54-2af5d14620fe",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\n",
|
||
"\n",
|
||
"df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"] # догадайтесь откуда df и её содержимое взялось\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"sns.histplot(df[\"Баллы\"], kde=True, color='blue')\n",
|
||
"sns.scatterplot(x=\"Возраст\", y=\"Баллы\", hue=\"Категория\", data=df, palette='viridis')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "53381da8-6b40-46bf-97c3-0afa6f83c887",
|
||
"metadata": {},
|
||
"source": [
|
||
"histplot, scatterplot построил"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"id": "c94ca031-7c7e-4847-a4b5-0d7f0e3cda1b",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 588.236x500 with 7 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\n",
|
||
"\n",
|
||
"df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"] # догадайтесь откуда df и её содержимое взялось\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"sns.pairplot(df[[\"Возраст\", \"Баллы\", \"Категория\"]], hue=\"Категория\")\n",
|
||
"sns.heatmap(df[[\"Возраст\", \"Баллы\"]].corr(),annot=True )\n",
|
||
" \n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3ad02abd-b613-4f58-973b-7004ea253c18",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавил sns.pairplot(df), sns.heatmap(df.corr(), annot=True)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"id": "e2bd2b5d-0906-45a1-b4ed-b2eaad06555a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 92.70it/s]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"\n",
|
||
"for i in tqdm(range(100)):\n",
|
||
" time.sleep(0.01) # Симуляция долгого процесса"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "1143358a-f22d-4700-b9ec-0ad4bdaab533",
|
||
"metadata": {},
|
||
"source": [
|
||
"Ничего не менял в Прогресс-бар с tqdm"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "75c1f416-0956-487f-b3eb-a6563c7333a8",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" 0%|▍ | 1/400 [00:00<03:20, 1.99it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 0: Анна, Возраст: 21, Баллы: 89\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" 0%|▉ | 2/400 [00:01<03:20, 1.99it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 1: Борис, Возраст: 22, Баллы: 76\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" 1%|█▍ | 3/400 [00:01<03:19, 1.99it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 2: Виктор, Возраст: 23, Баллы: 95\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" 1%|█▉ | 4/400 [00:02<03:19, 1.99it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 3: Галина, Возраст: 24, Баллы: 82\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"\n",
|
||
"for index, row in tqdm(df.iterrows(), total=len(df)*100):\n",
|
||
" time.sleep(0.5) # Симуляция долгого процесса\n",
|
||
" print(f\"Обработка строки {index}: {row['Имя']}, Возраст: {row['Возраст']}, Баллы: {row['Баллы']}\")\n",
|
||
" "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "28a97b53-5a02-4dbd-bdcd-4a9244547389",
|
||
"metadata": {},
|
||
"source": [
|
||
"Использовал tqdm(df.iterrows()) для обработки строк последоватеьно , закончились значения поэтому загрущка не продолжается для наглядности замедленна"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"id": "4e55feae-c921-467f-974f-9f1891e312ff",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Загрузка: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 92.65it/s]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"\n",
|
||
"for i in tqdm(range(100), desc='Загрузка'):\n",
|
||
" time.sleep(0.01) # Симуляция долгого процесса"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "265ab519-25ff-4596-9202-88da942e9e86",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавлена надпись Загрузка "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6e48f1e0-857b-4aab-8749-24f25f594244",
|
||
"metadata": {},
|
||
"source": [
|
||
" САМОСТОЯТЕЛЬНОЕ ЗАДАНИЕ\n",
|
||
"______________________________________________________________________________________________________________________________________________________________________________________________________"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"id": "9911f371-ac9e-4d8f-bfe8-c1567f23e5a9",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Загрузка данных...\n",
|
||
"\n",
|
||
"Данные успешно загружены!\n",
|
||
"\n",
|
||
"Первые строки данных:\n",
|
||
" Группа ФИО Вариант КР КР1 пост. ток \\\n",
|
||
"0 ИКТб-2301-04-00 Анохин Игорь Вячеславович 1.0 0.5 \n",
|
||
"1 ИКТб-2301-04-00 Богданов Дмитрий Константинович 2.0 1 \n",
|
||
"2 ИКТб-2301-04-00 Боровской Степан Николаевич 3.0 0 \n",
|
||
"3 ИКТб-2301-04-00 Вайсман Всеволод Михайлович 4.0 0 \n",
|
||
"4 ИКТб-2301-04-00 Ванеева Софья Дмитриевна 5.0 0.7 \n",
|
||
"\n",
|
||
" Unnamed: 4 дом. задания прогулов до аттестации Аттестация КР2 sin ток \\\n",
|
||
"0 NaN показал NaN НА 1.75 \n",
|
||
"1 NaN показал NaN А 3.85 \n",
|
||
"2 NaN показал NaN НА 0.5 \n",
|
||
"3 NaN частично NaN НА 1.1 \n",
|
||
"4 NaN частично NaN НА 2 \n",
|
||
"\n",
|
||
" Зачет задачи ... ДОПУСК ЛАБЫ Вариант экзамен Экзамен баллы из 105 \\\n",
|
||
"0 2.2 ... NaN NaN NaN \n",
|
||
"1 А ... NaN NaN NaN \n",
|
||
"2 2 ... NaN NaN NaN \n",
|
||
"3 0 ... NaN NaN NaN \n",
|
||
"4 NaN ... NaN NaN NaN \n",
|
||
"\n",
|
||
" Бонус контрольные(баллы) Бонус лекции(баллы) Штраф за прогулы(баллы) \\\n",
|
||
"0 NaN NaN NaN \n",
|
||
"1 NaN NaN NaN \n",
|
||
"2 NaN NaN NaN \n",
|
||
"3 NaN NaN NaN \n",
|
||
"4 NaN NaN NaN \n",
|
||
"\n",
|
||
" Балл итог ИТОГ ОЦЕНКА ведомость экзамен комментарий \n",
|
||
"0 NaN NaN NaN NaN \n",
|
||
"1 NaN NaN NaN NaN \n",
|
||
"2 NaN NaN NaN NaN \n",
|
||
"3 NaN NaN NaN NaN \n",
|
||
"4 NaN NaN NaN NaN \n",
|
||
"\n",
|
||
"[5 rows x 29 columns]\n",
|
||
"\n",
|
||
"Информация о данных (df.info()):\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 89 entries, 0 to 88\n",
|
||
"Data columns (total 29 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Группа 89 non-null object \n",
|
||
" 1 ФИО 89 non-null object \n",
|
||
" 2 Вариант КР 64 non-null float64\n",
|
||
" 3 КР1 пост. ток 77 non-null object \n",
|
||
" 4 Unnamed: 4 0 non-null float64\n",
|
||
" 5 дом. задания 82 non-null object \n",
|
||
" 6 прогулов до аттестации 0 non-null float64\n",
|
||
" 7 Аттестация 77 non-null object \n",
|
||
" 8 КР2 sin ток 75 non-null object \n",
|
||
" 9 Зачет задачи 54 non-null object \n",
|
||
" 10 вариант 38 non-null object \n",
|
||
" 11 КР 1 часть 32 non-null object \n",
|
||
" 12 Зачет 71 non-null object \n",
|
||
" 13 КР3 Перех. процессы 0 non-null float64\n",
|
||
" 14 лабы вариант 6 non-null float64\n",
|
||
" 15 КР сдана 0 non-null float64\n",
|
||
" 16 КР защищена(оценка) 0 non-null float64\n",
|
||
" 17 КР загружена 0 non-null float64\n",
|
||
" 18 Ведомость курсовая 0 non-null float64\n",
|
||
" 19 ДОПУСК ЛАБЫ 0 non-null float64\n",
|
||
" 20 Вариант экзамен 0 non-null float64\n",
|
||
" 21 Экзамен баллы из 105 0 non-null float64\n",
|
||
" 22 Бонус контрольные(баллы) 0 non-null float64\n",
|
||
" 23 Бонус лекции(баллы) 0 non-null float64\n",
|
||
" 24 Штраф за прогулы(баллы) 0 non-null float64\n",
|
||
" 25 Балл итог 0 non-null float64\n",
|
||
" 26 ИТОГ ОЦЕНКА 1 non-null float64\n",
|
||
" 27 ведомость экзамен 0 non-null float64\n",
|
||
" 28 комментарий 1 non-null object \n",
|
||
"dtypes: float64(18), object(11)\n",
|
||
"memory usage: 20.3+ KB\n",
|
||
"None\n",
|
||
"\n",
|
||
"Статистика по числовым столбцам (df.describe()):\n",
|
||
" Вариант КР Unnamed: 4 прогулов до аттестации КР3 Перех. процессы \\\n",
|
||
"count 64.000000 0.0 0.0 0.0 \n",
|
||
"mean 32.515625 NaN NaN NaN \n",
|
||
"std 18.646241 NaN NaN NaN \n",
|
||
"min 1.000000 NaN NaN NaN \n",
|
||
"25% 16.750000 NaN NaN NaN \n",
|
||
"50% 32.500000 NaN NaN NaN \n",
|
||
"75% 48.250000 NaN NaN NaN \n",
|
||
"max 65.000000 NaN NaN NaN \n",
|
||
"\n",
|
||
" лабы вариант КР сдана КР защищена(оценка) КР загружена \\\n",
|
||
"count 6.000000 0.0 0.0 0.0 \n",
|
||
"mean 1.500000 NaN NaN NaN \n",
|
||
"std 0.547723 NaN NaN NaN \n",
|
||
"min 1.000000 NaN NaN NaN \n",
|
||
"25% 1.000000 NaN NaN NaN \n",
|
||
"50% 1.500000 NaN NaN NaN \n",
|
||
"75% 2.000000 NaN NaN NaN \n",
|
||
"max 2.000000 NaN NaN NaN \n",
|
||
"\n",
|
||
" Ведомость курсовая ДОПУСК ЛАБЫ Вариант экзамен Экзамен баллы из 105 \\\n",
|
||
"count 0.0 0.0 0.0 0.0 \n",
|
||
"mean NaN NaN NaN NaN \n",
|
||
"std NaN NaN NaN NaN \n",
|
||
"min NaN NaN NaN NaN \n",
|
||
"25% NaN NaN NaN NaN \n",
|
||
"50% NaN NaN NaN NaN \n",
|
||
"75% NaN NaN NaN NaN \n",
|
||
"max NaN NaN NaN NaN \n",
|
||
"\n",
|
||
" Бонус контрольные(баллы) Бонус лекции(баллы) Штраф за прогулы(баллы) \\\n",
|
||
"count 0.0 0.0 0.0 \n",
|
||
"mean NaN NaN NaN \n",
|
||
"std NaN NaN NaN \n",
|
||
"min NaN NaN NaN \n",
|
||
"25% NaN NaN NaN \n",
|
||
"50% NaN NaN NaN \n",
|
||
"75% NaN NaN NaN \n",
|
||
"max NaN NaN NaN \n",
|
||
"\n",
|
||
" Балл итог ИТОГ ОЦЕНКА ведомость экзамен \n",
|
||
"count 0.0 1.0 0.0 \n",
|
||
"mean NaN 4.0 NaN \n",
|
||
"std NaN NaN NaN \n",
|
||
"min NaN 4.0 NaN \n",
|
||
"25% NaN 4.0 NaN \n",
|
||
"50% NaN 4.0 NaN \n",
|
||
"75% NaN 4.0 NaN \n",
|
||
"max NaN 4.0 NaN \n",
|
||
"\n",
|
||
"Построение гистограммы...\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 800x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"Подсчет процентов для scatterplot...\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 800x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"Преобразование данных в числовой формат...\n",
|
||
"\n",
|
||
"Построение boxplot...\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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",
|
||
"text/plain": [
|
||
"<Figure size 800x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"Подсчет количества завалов...\n",
|
||
"Количество человек, получивших меньше 1 балла за КР1: 38\n",
|
||
"\n",
|
||
"Постепенная обработка данных...\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 0%| | 0/89 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 0: Группа: ИКТб-2301-04-00, Зачет: Зачет, КР1: 0.5\n",
|
||
"Обработка строки 1: Группа: ИКТб-2301-04-00, Зачет: зачет, КР1: 1.0\n",
|
||
"Обработка строки 2: Группа: ИКТб-2301-04-00, Зачет: зачет, КР1: 0.0\n",
|
||
"Обработка строки 3: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 0.0\n",
|
||
"Обработка строки 4: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 0.7\n",
|
||
"Обработка строки 5: Группа: ИКТб-2301-04-00, Зачет: перезачет, КР1: nan\n",
|
||
"Обработка строки 6: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 2.0\n",
|
||
"Обработка строки 7: Группа: ИКТб-2301-04-00, Зачет: зачет, КР1: 0.0\n",
|
||
"Обработка строки 8: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 0.0\n",
|
||
"Обработка строки 9: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 11%|███████████████████▏ | 10/89 [00:00<00:00, 94.10it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 10: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 11: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 0.0\n",
|
||
"Обработка строки 12: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 0.9\n",
|
||
"Обработка строки 13: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 14: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 15: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: nan\n",
|
||
"Обработка строки 16: Группа: ИКТб-2301-04-00, Зачет: зачет, КР1: 0.0\n",
|
||
"Обработка строки 17: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 18: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 1.0\n",
|
||
"Обработка строки 19: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 1.0"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 22%|██████████████████████████████████████▍ | 20/89 [00:00<00:00, 93.21it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"Обработка строки 20: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: nan\n",
|
||
"Обработка строки 21: Группа: ИКТб-2301-04-00, Зачет: зачет, КР1: 3.0\n",
|
||
"Обработка строки 22: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 23: Группа: ИКТб-2301-04-00, Зачет: не зачтено, КР1: 0.6\n",
|
||
"Обработка строки 24: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 25: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: nan\n",
|
||
"Обработка строки 26: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 27: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 0.5\n",
|
||
"Обработка строки 28: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 29: Группа: ИКТб-2302-04-00, Зачет: nan, КР1: nan\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 34%|█████████████████████████████████████████████████████████▋ | 30/89 [00:00<00:00, 92.26it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 30: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: 0.7\n",
|
||
"Обработка строки 31: Группа: ИКТб-2301-04-00, Зачет: неявка, КР1: nan\n",
|
||
"Обработка строки 32: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 33: Группа: ИКТб-2301-04-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 34: Группа: ИНБб-2301-02-00, Зачет: АО, КР1: nan\n",
|
||
"Обработка строки 35: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 3.0\n",
|
||
"Обработка строки 36: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 0.0\n",
|
||
"Обработка строки 37: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 2.0\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 45%|████████████████████████████████████████████████████████████████████████████▊ | 40/89 [00:00<00:00, 90.43it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 38: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 2.0\n",
|
||
"Обработка строки 39: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 0.5\n",
|
||
"Обработка строки 40: Группа: ИНБб-2301-02-00, Зачет: не зачтено, КР1: 0.0\n",
|
||
"Обработка строки 41: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 0.7\n",
|
||
"Обработка строки 42: Группа: ИНБб-2301-02-00, Зачет: неявка, КР1: nan\n",
|
||
"Обработка строки 43: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 1.4\n",
|
||
"Обработка строки 44: Группа: ИНБб-2301-02-00, Зачет: неявка, КР1: 0.2\n",
|
||
"Обработка строки 45: Группа: ИНБб-2301-02-00, Зачет: не зачтено, КР1: 0.3\n",
|
||
"Обработка строки 46: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 1.5\n",
|
||
"Обработка строки 47: Группа: ИНБб-2301-02-00, Зачет: неявка, КР1: 0.3\n",
|
||
"Обработка строки 48: Группа: ИНБб-2301-02-00, Зачет: неявка, КР1: nan\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 56%|████████████████████████████████████████████████████████████████████████████████████████████████ | 50/89 [00:00<00:00, 89.84it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 49: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: nan\n",
|
||
"Обработка строки 50: Группа: ИНБб-2301-02-00, Зачет: не зачтено, КР1: 0.0\n",
|
||
"Обработка строки 51: Группа: ИНБб-2301-02-00, Зачет: неявка, КР1: nan\n",
|
||
"Обработка строки 52: Группа: ИНБб-2301-02-00, Зачет: неявка, КР1: 0.0\n",
|
||
"Обработка строки 53: Группа: ИНБб-2301-02-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 54: Группа: ИНБб-2301-02-00, Зачет: не зачтено, КР1: 0.0\n",
|
||
"Обработка строки 55: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 1.3\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 66%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎ | 59/89 [00:00<00:00, 88.13it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 56: Группа: ИНБб-2301-02-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 57: Группа: ИНБб-2301-02-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 58: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 1.0\n",
|
||
"Обработка строки 59: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 2.7\n",
|
||
"Обработка строки 60: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 2.0\n",
|
||
"Обработка строки 61: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 3.0\n",
|
||
"Обработка строки 62: Группа: ИКБб-2301-04-00, Зачет: неявка, КР1: 0.0\n",
|
||
"Обработка строки 63: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 0.5\n",
|
||
"Обработка строки 64: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: 1.5\n",
|
||
"Обработка строки 65: Группа: ИНБб-2301-02-00, Зачет: зачет, КР1: nan\n",
|
||
"Обработка строки 66: Группа: ИНБс-2301-01-00, Зачет: неявка, КР1: nan\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋ | 68/89 [00:00<00:00, 86.98it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 67: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.0\n",
|
||
"Обработка строки 68: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.9\n",
|
||
"Обработка строки 69: Группа: ИНБс-2301-01-00, Зачет: зачет, КР1: 0.0\n",
|
||
"Обработка строки 70: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.0\n",
|
||
"Обработка строки 71: Группа: ИНБс-2301-01-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 72: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.0\n",
|
||
"Обработка строки 73: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.5\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 87%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉ | 77/89 [00:00<00:00, 87.20it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 74: Группа: ИНБс-2301-01-00, Зачет: nan, КР1: nan\n",
|
||
"Обработка строки 75: Группа: ИНБс-2301-01-00, Зачет: зачет, КР1: 0.5\n",
|
||
"Обработка строки 76: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.4\n",
|
||
"Обработка строки 77: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.7\n",
|
||
"Обработка строки 78: Группа: ИНБс-2301-01-00, Зачет: зачет, КР1: 1.0\n",
|
||
"Обработка строки 79: Группа: ИНБб-2301-01-00, Зачет: зачет, КР1: 1.0\n",
|
||
"Обработка строки 80: Группа: ИНБс-2301-01-00, Зачет: неявка, КР1: 0.8\n",
|
||
"Обработка строки 81: Группа: ИНБс-2301-01-00, Зачет: неявка, КР1: 1.0\n",
|
||
"Обработка строки 82: Группа: ИНБс-2301-01-00, Зачет: зачет, КР1: 0.0\n",
|
||
"Обработка строки 83: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.0\n",
|
||
"Обработка строки 84: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.9\n",
|
||
"Обработка строки 85: Группа: ИНБс-2301-01-00, Зачет: не зачтено, КР1: 0.4\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 89/89 [00:01<00:00, 87.89it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строки 86: Группа: ИНБс-2301-01-00, Зачет: зачет, КР1: 2.5\n",
|
||
"Обработка строки 87: Группа: ИНБс-2301-01-00, Зачет: неявка, КР1: nan\n",
|
||
"Обработка строки 88: Группа: ИНБс-2301-01-00, Зачет: nan, КР1: nan\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"import seaborn as sns\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"from tqdm import tqdm # Импортируем tqdm\n",
|
||
"import time # Для имитации долгого процесса\n",
|
||
"\n",
|
||
"try:\n",
|
||
" # Загрузка данных\n",
|
||
" print(\"Загрузка данных...\")\n",
|
||
" df = pd.read_excel(\n",
|
||
" r'C:\\Users\\admin\\Desktop\\Практика 2.2\\2024-2025_Успеваемость_ТЭЦ_ЭиС.xlsx', \n",
|
||
" sheet_name='ТЭЦ', \n",
|
||
" engine='openpyxl' # Используем openpyxl для чтения .xlsx\n",
|
||
" )\n",
|
||
" print(\"\\nДанные успешно загружены!\")\n",
|
||
" \n",
|
||
" # Вывод первых строк данных\n",
|
||
" print(\"\\nПервые строки данных:\")\n",
|
||
" print(df.head())\n",
|
||
" \n",
|
||
" # Базовый анализ\n",
|
||
" print(\"\\nИнформация о данных (df.info()):\")\n",
|
||
" print(df.info())\n",
|
||
" \n",
|
||
" print(\"\\nСтатистика по числовым столбцам (df.describe()):\")\n",
|
||
" print(df.describe())\n",
|
||
" \n",
|
||
" # Гистограмма по группам\n",
|
||
" print(\"\\nПостроение гистограммы...\")\n",
|
||
" plt.figure(figsize=(8, 6))\n",
|
||
" sns.histplot(df['Группа'], bins=3, kde=False, color='blue')\n",
|
||
" plt.title('Количество человек в каждой группе')\n",
|
||
" plt.xlabel('Группа')\n",
|
||
" plt.ylabel('Количество человек')\n",
|
||
" plt.show()\n",
|
||
" \n",
|
||
" # Scatterplot по статусу зачета\n",
|
||
" print(\"\\nПодсчет процентов для scatterplot...\")\n",
|
||
" зачет_статус = df['Зачет'].value_counts(normalize=True) * 100\n",
|
||
" plt.figure(figsize=(8, 6))\n",
|
||
" sns.scatterplot(x=зачет_статус.index, y=зачет_статус.values, s=100, color='red')\n",
|
||
" plt.title('Процент людей с зачетом, неявкой и перезачетом')\n",
|
||
" plt.xlabel('Статус зачета')\n",
|
||
" plt.ylabel('Процент')\n",
|
||
" plt.show()\n",
|
||
" \n",
|
||
" # Преобразование столбца 'КР1 пост. ток' в числовой формат\n",
|
||
" print(\"\\nПреобразование данных в числовой формат...\")\n",
|
||
" df['КР1 пост. ток'] = pd.to_numeric(df['КР1 пост. ток'], errors='coerce')\n",
|
||
" \n",
|
||
" # Boxplot по КР1\n",
|
||
" print(\"\\nПостроение boxplot...\")\n",
|
||
" plt.figure(figsize=(8, 6))\n",
|
||
" sns.boxplot(x=df['КР1 пост. ток'], color='green')\n",
|
||
" plt.title('Распределение баллов за КР1')\n",
|
||
" plt.xlabel('Баллы за КР1')\n",
|
||
" plt.show()\n",
|
||
" \n",
|
||
" # Подсчет завалов за КР1\n",
|
||
" print(\"\\nПодсчет количества завалов...\")\n",
|
||
" количество_завалов = df[df['КР1 пост. ток'] < 1].shape[0]\n",
|
||
" print(f\"Количество человек, получивших меньше 1 балла за КР1: {количество_завалов}\")\n",
|
||
" \n",
|
||
" # Постепенная обработка данных с прогресс-баром\n",
|
||
" print(\"\\nПостепенная обработка данных...\")\n",
|
||
" for index, row in tqdm(df.iterrows(), total=len(df), desc=\"Обработка строк\"):\n",
|
||
" # Имитация долгого процесса\n",
|
||
" time.sleep(0.01) # Задержка для наглядности\n",
|
||
" \n",
|
||
" # Пример обработки строки\n",
|
||
" print(f\"Обработка строки {index}: Группа: {row['Группа']}, Зачет: {row['Зачет']}, КР1: {row['КР1 пост. ток']}\")\n",
|
||
" \n",
|
||
"except FileNotFoundError:\n",
|
||
" print(\"Ошибка: Файл не найден. Проверьте путь.\")\n",
|
||
"except Exception as e:\n",
|
||
" print(f\"Произошла ошибка: {e}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c24f0ecf-f69e-496e-a623-a94f45b6fd8c",
|
||
"metadata": {},
|
||
"source": [
|
||
"загружена xl таблица - по предмету ТЭЦ \n",
|
||
"Проведен базовый анализ\n",
|
||
"Построены 3 графика (. Каждая строка DataFrame обрабатывается с выводом информации о группе - сколько человек в группе, статусе зачета и баллах за КР1 - у кого меньше 1 балла.)\n",
|
||
"Добавлена загруск а с данными о КР1 "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "47e57ed6-40dd-45c0-a533-532136980b21",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.13.2"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|