2hz
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c1b71a853a
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.idea/.gitignore
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vendored
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.idea/.gitignore
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vendored
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# Default ignored files
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/shelf/
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/workspace.xml
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.idea/1xz.iml
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.idea/1xz.iml
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<?xml version="1.0" encoding="UTF-8"?>
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||||
<module type="PYTHON_MODULE" version="4">
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||||
<component name="NewModuleRootManager">
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||||
<content url="file://$MODULE_DIR$">
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||||
<excludeFolder url="file://$MODULE_DIR$/.venv" />
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||||
</content>
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<orderEntry type="jdk" jdkName="Python 3.13 (2xz)" jdkType="Python SDK" />
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<orderEntry type="sourceFolder" forTests="false" />
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</component>
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</module>
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.idea/inspectionProfiles/profiles_settings.xml
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<component name="InspectionProjectProfileManager">
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<settings>
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<option name="USE_PROJECT_PROFILE" value="false" />
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<version value="1.0" />
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</settings>
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</component>
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.idea/misc.xml
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.idea/misc.xml
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="Black">
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.idea/modules.xml
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="ProjectModuleManager">
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<modules>
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<module fileurl="file://$PROJECT_DIR$/.idea/1xz.iml" filepath="$PROJECT_DIR$/.idea/1xz.iml" />
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</component>
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.idea/vcs.xml
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.idea/vcs.xml
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<?xml version="1.0" encoding="UTF-8"?>
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<project version="4">
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<component name="VcsDirectoryMappings">
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<mapping directory="" vcs="Git" />
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0
.ipynb_checkpoints/README-checkpoint.md
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0
.ipynb_checkpoints/README-checkpoint.md
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.ipynb_checkpoints/drygoe-checkpoint.ipynb
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.ipynb_checkpoints/drygoe-checkpoint.ipynb
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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.ipynb_checkpoints/main-checkpoint.py
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.ipynb_checkpoints/main-checkpoint.py
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# This is a sample Python script.
|
||||
|
||||
# Press Shift+F10 to execute it or replace it with your code.
|
||||
# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
|
||||
|
||||
|
||||
def print_hi(name):
|
||||
# Use a breakpoint in the code line below to debug your script.
|
||||
print(f'Hi, {name}') # Press Ctrl+F8 to toggle the breakpoint.
|
||||
|
||||
|
||||
# Press the green button in the gutter to run the script.
|
||||
if __name__ == '__main__':
|
||||
print_hi('PyCharm')
|
||||
|
||||
# See PyCharm help at https://www.jetbrains.com/help/pycharm/
|
||||
6
.ipynb_checkpoints/matplotlib-checkpoint.ipynb
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6
.ipynb_checkpoints/matplotlib-checkpoint.ipynb
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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.ipynb_checkpoints/numpy-checkpoint.ipynb
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6
.ipynb_checkpoints/numpy-checkpoint.ipynb
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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.ipynb_checkpoints/pandas-checkpoint.ipynb
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.ipynb_checkpoints/pandas-checkpoint.ipynb
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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.ipynb_checkpoints/seaborn-checkpoint.ipynb
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.ipynb_checkpoints/seaborn-checkpoint.ipynb
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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.ipynb_checkpoints/tqdm-checkpoint.ipynb
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.ipynb_checkpoints/tqdm-checkpoint.ipynb
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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clothing_sizes.csv
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clothing_sizes.csv
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id,height,weight,age,chest_size,waist_size,hip_size,size,brand,category,price,rating,purchase_count
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1,165,55,25,85,68,92,S,Zara,Dress,45.99,4.5,120
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2,170,65,30,95,78,100,M,H&M,Jeans,59.99,4.2,85
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3,175,75,28,100,85,105,L,Adidas,T-shirt,29.99,4.7,200
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4,160,50,22,80,65,88,XS,Mango,Blouse,39.99,4.3,95
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5,180,85,35,110,92,110,XL,Nike,Jacket,89.99,4.6,150
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6,168,60,27,88,72,94,S,Uniqlo,Sweater,49.99,4.4,110
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7,172,70,32,98,82,102,M,Zara,Pants,54.99,4.1,75
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8,178,80,29,105,88,108,L,H&M,Hoodie,44.99,4.5,130
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9,162,52,24,82,66,90,XS,Mango,Dress,64.99,4.8,90
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10,175,72,31,102,86,106,L,Adidas,Shorts,34.99,4.3,105
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11,167,58,26,87,70,93,S,Uniqlo,T-shirt,24.99,4.6,180
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12,173,68,33,96,80,101,M,Nike,Leggings,39.99,4.4,95
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13,182,90,36,112,95,112,XXL,Puma,Jacket,99.99,4.2,65
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14,158,48,21,78,63,86,XXS,Zara,Blouse,42.99,4.7,88
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15,169,62,29,90,74,96,S,H&M,Jeans,55.99,4.3,115
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16,176,76,34,103,87,107,L,Mango,Coat,129.99,4.5,70
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17,164,54,23,84,67,91,S,Adidas,Sneakers,79.99,4.8,220
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18,171,66,30,94,77,99,M,Uniqlo,Polo,34.99,4.4,100
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19,177,78,28,104,89,109,L,Nike,Tracksuit,89.99,4.6,85
|
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20,163,53,25,83,68,90,XS,Zara,Skirt,37.99,4.2,92
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389
drygoe.ipynb
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389
drygoe.ipynb
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main.py
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main.py
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||||
# This is a sample Python script.
|
||||
|
||||
# Press Shift+F10 to execute it or replace it with your code.
|
||||
# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
|
||||
|
||||
|
||||
def print_hi(name):
|
||||
# Use a breakpoint in the code line below to debug your script.
|
||||
print(f'Hi, {name}') # Press Ctrl+F8 to toggle the breakpoint.
|
||||
|
||||
|
||||
# Press the green button in the gutter to run the script.
|
||||
if __name__ == '__main__':
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||||
print_hi('PyCharm')
|
||||
|
||||
# See PyCharm help at https://www.jetbrains.com/help/pycharm/
|
||||
124
matplotlib.ipynb
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124
matplotlib.ipynb
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numpy.ipynb
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numpy.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "3af2cc9d-8792-4968-972a-cdfed0d85dce",
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"metadata": {},
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||||
"outputs": [
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{
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||||
"name": "stdout",
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"output_type": "stream",
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"text": [
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"Моя матрица 2x2:\n",
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||||
"[[ 5 7]\n",
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||||
" [ 9 10]]\n",
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||||
"\n",
|
||||
"Тестирую linspace:\n",
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||||
"Массив от 0 до 10 с 5 элементами:\n",
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||||
"[ 0. 2.5 5. 7.5 10. ]\n",
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"\n",
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"Случайные числа из randn:\n",
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||||
"[ 0.04269067 0.9476501 -0.05281896]\n",
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||||
"\n",
|
||||
"Умножаю матрицу на саму себя через dot:\n",
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||||
"Результат:\n",
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||||
"[[ 88 105]\n",
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||||
" [135 163]]\n",
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||||
"\n",
|
||||
"Сумма всех элементов матрицы:\n",
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||||
"31\n",
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||||
"Среднее арифметическое:\n",
|
||||
"7.75\n"
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||||
]
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||||
},
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||||
{
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||||
"data": {
|
||||
"text/plain": [
|
||||
"array([[ 5, 7],\n",
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" [ 9, 10]])"
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},
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||||
"execution_count": 3,
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||||
"metadata": {},
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||||
"output_type": "execute_result"
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||||
}
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||||
],
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||||
"source": [
|
||||
"import numpy as np\n",
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||||
"matrix = np.array([[5, 7], [9, 10]])\n",
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||||
"\n",
|
||||
"print(\"Моя матрица 2x2:\")\n",
|
||||
"print(matrix)\n",
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||||
"\n",
|
||||
"print(\"\\nТестирую linspace:\")\n",
|
||||
"arr = np.linspace(0, 10, 5)\n",
|
||||
"print(\"Массив от 0 до 10 с 5 элементами:\")\n",
|
||||
"print(arr)\n",
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||||
"\n",
|
||||
"print(\"\\nСлучайные числа из randn:\")\n",
|
||||
"random_arr = np.random.randn(3)\n",
|
||||
"print(random_arr)\n",
|
||||
"\n",
|
||||
"print(\"\\nУмножаю матрицу на саму себя через dot:\")\n",
|
||||
"result = np.dot(matrix, matrix)\n",
|
||||
"print(\"Результат:\")\n",
|
||||
"print(result)\n",
|
||||
"\n",
|
||||
"print(\"\\nСумма всех элементов матрицы:\")\n",
|
||||
"summa = np.sum(matrix)\n",
|
||||
"print(summa)\n",
|
||||
"\n",
|
||||
"print(\"Среднее арифметическое:\")\n",
|
||||
"srednee = np.mean(matrix)\n",
|
||||
"print(srednee)\n",
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||||
"\n",
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||||
"matrix"
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||||
]
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||||
},
|
||||
{
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||||
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||||
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||||
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"kernelspec": {
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||||
},
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||||
"nbformat": 4,
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||||
"nbformat_minor": 5
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||||
}
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||||
200
pandas.ipynb
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||||
{
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||||
"cells": [
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||||
{
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||||
"cell_type": "code",
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"execution_count": 13,
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"id": "e49a4fbc-f85f-47c0-b3a0-4af25468faa3",
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"metadata": {
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||||
"scrolled": true
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||||
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"outputs": [
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||||
{
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||||
"name": "stdout",
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||||
"output_type": "stream",
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||||
"text": [
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||||
"Основная таблица с бонусами:\n",
|
||||
" Имя Возраст Баллы Результат с бонусом Категория\n",
|
||||
"0 Анна 21 89 102.35 Младше\n",
|
||||
"1 Борис 22 76 87.40 Младше\n",
|
||||
"2 Виктор 23 95 109.25 Старше\n",
|
||||
"3 Галина 24 82 94.30 Старше\n",
|
||||
"4 Дмитрий 21 91 104.65 Младше\n",
|
||||
"\n",
|
||||
"Статистика по группам:\n",
|
||||
" Баллы Имя\n",
|
||||
" mean max min count\n",
|
||||
"Категория \n",
|
||||
"Младше 85.33 91 76 3\n",
|
||||
"Старше 88.50 95 82 2\n",
|
||||
"\n",
|
||||
"Отфильтрованные студенты:\n",
|
||||
" Имя Возраст Баллы Результат с бонусом Категория\n",
|
||||
"2 Виктор 23 95 109.25 Старше\n",
|
||||
"4 Дмитрий 21 91 104.65 Младше\n",
|
||||
"0 Анна 21 89 102.35 Младше\n",
|
||||
"3 Галина 24 82 94.30 Старше\n",
|
||||
"1 Борис 22 76 87.40 Младше\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",
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||||
"\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",
|
||||
" <th>Результат с бонусом</th>\n",
|
||||
" <th>Категория</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",
|
||||
" <td>102.35</td>\n",
|
||||
" <td>Младше</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>Борис</td>\n",
|
||||
" <td>22</td>\n",
|
||||
" <td>76</td>\n",
|
||||
" <td>87.40</td>\n",
|
||||
" <td>Младше</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>Виктор</td>\n",
|
||||
" <td>23</td>\n",
|
||||
" <td>95</td>\n",
|
||||
" <td>109.25</td>\n",
|
||||
" <td>Старше</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>Галина</td>\n",
|
||||
" <td>24</td>\n",
|
||||
" <td>82</td>\n",
|
||||
" <td>94.30</td>\n",
|
||||
" <td>Старше</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>Дмитрий</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" <td>91</td>\n",
|
||||
" <td>104.65</td>\n",
|
||||
" <td>Младше</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Имя Возраст Баллы Результат с бонусом Категория\n",
|
||||
"0 Анна 21 89 102.35 Младше\n",
|
||||
"1 Борис 22 76 87.40 Младше\n",
|
||||
"2 Виктор 23 95 109.25 Старше\n",
|
||||
"3 Галина 24 82 94.30 Старше\n",
|
||||
"4 Дмитрий 21 91 104.65 Младше"
|
||||
]
|
||||
},
|
||||
"execution_count": 13,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import pandas as pd\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"students_info = {\n",
|
||||
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\", \"Дмитрий\"],\n",
|
||||
" \"Возраст\": [21, 22, 23, 24, 21],\n",
|
||||
" \"Баллы\": [89, 76, 95, 82, 91]\n",
|
||||
"}\n",
|
||||
"df = pd.DataFrame(students_info)\n",
|
||||
"\n",
|
||||
"df[\"Результат с бонусом\"] = df[\"Баллы\"].apply(lambda x: round(x * 1.15, 2))\n",
|
||||
"\n",
|
||||
"df[\"Категория\"] = df[\"Возраст\"].apply(lambda age: \"Младше\" if age < 23 else \"Старше\")\n",
|
||||
"\n",
|
||||
"grouped_stats = df.groupby(\"Категория\").agg({\n",
|
||||
" \"Баллы\": [\"mean\", \"max\", \"min\"],\n",
|
||||
" \"Имя\": \"count\"\n",
|
||||
"}).round(2)\n",
|
||||
"\n",
|
||||
"filtered_df = df[(df[\"Возраст\"] > 21) | (df[\"Баллы\"] > 80)]\n",
|
||||
"\n",
|
||||
"filtered_df = filtered_df.sort_values(\"Баллы\", ascending=False)\n",
|
||||
"\n",
|
||||
"print(\"Основная таблица с бонусами:\")\n",
|
||||
"print(df)\n",
|
||||
"\n",
|
||||
"print(\"\\nСтатистика по группам:\")\n",
|
||||
"print(grouped_stats)\n",
|
||||
"\n",
|
||||
"print(\"\\nОтфильтрованные студенты:\")\n",
|
||||
"print(filtered_df)\n",
|
||||
"\n",
|
||||
"df"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "3edb05fc-37ae-44df-b4a2-9abdc9c8f541",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f808c922-f97c-4d19-aab9-5447d932cc71",
|
||||
"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": "3.13.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
192
seaborn.ipynb
Normal file
192
seaborn.ipynb
Normal file
File diff suppressed because one or more lines are too long
144
tqdm.ipynb
Normal file
144
tqdm.ipynb
Normal file
@ -0,0 +1,144 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "1b768852-5883-4ca4-86e7-d4a93c9a1a55",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Таблица создана:\n",
|
||||
" ID Data\n",
|
||||
"0 0 -1.082938\n",
|
||||
"1 1 -0.374716\n",
|
||||
"2 2 0.609893\n",
|
||||
"3 3 0.032177\n",
|
||||
"4 4 1.138623\n",
|
||||
"\n",
|
||||
"Запускаю цикл с прогресс-баром...\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Загрузка: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:02<00:00, 19.56it/s]\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Первый цикл готов!\n",
|
||||
"\n",
|
||||
"Обрабатываю строки таблицы...\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Обработка: 100it [00:00, 20892.13it/s]\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Обработано строк: 100\n",
|
||||
"\n",
|
||||
"Запускаю второй прогресс-бар...\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Вычисления: 100%|\u001b[34m████████████████████████████████████████████████████████████████████████████████████████████████████████\u001b[0m| 20/20 [00:02<00:00, 9.86it/s]\u001b[0m"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Все вычисления завершены!\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import pandas as pd\n",
|
||||
"import numpy as np\n",
|
||||
"from tqdm import tqdm\n",
|
||||
"import time\n",
|
||||
"\n",
|
||||
"df = pd.DataFrame({\n",
|
||||
" 'ID': range(100),\n",
|
||||
" 'Data': np.random.randn(100)\n",
|
||||
"})\n",
|
||||
"\n",
|
||||
"print(\"Таблица создана:\")\n",
|
||||
"print(df.head())\n",
|
||||
"\n",
|
||||
"print(\"\\nЗапускаю цикл с прогресс-баром...\")\n",
|
||||
"for i in tqdm(range(50), desc='Загрузка'):\n",
|
||||
" time.sleep(0.05)\n",
|
||||
"\n",
|
||||
"print(\"Первый цикл готов!\")\n",
|
||||
"\n",
|
||||
"print(\"\\nОбрабатываю строки таблицы...\")\n",
|
||||
"schetchik = 0\n",
|
||||
"for index, row in tqdm(df.iterrows(), desc=\"Обработка\"):\n",
|
||||
" vremya = row['Data'] ** 2\n",
|
||||
" schetchik = schetchik + 1\n",
|
||||
"\n",
|
||||
"print(f\"Обработано строк: {schetchik}\")\n",
|
||||
"\n",
|
||||
"print(\"\\nЗапускаю второй прогресс-бар...\")\n",
|
||||
"for i in tqdm(range(20), desc='Вычисления', colour='blue'):\n",
|
||||
" result = i * 2\n",
|
||||
" time.sleep(0.1)\n",
|
||||
"\n",
|
||||
"print(\"Все вычисления завершены!\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "fe6502c6-7248-4a62-9d1c-38fd51c85549",
|
||||
"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": "3.13.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user