Добавили все файлы
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commit
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.gitignore
vendored
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164
.gitignore
vendored
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# ---> Python
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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||||||
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||||||
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# Distribution / packaging
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.Python
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||||||
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build/
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||||||
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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||||||
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# PyInstaller
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# Usually these files are written by a python script from a template
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||||||
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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||||||
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*.spec
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||||||
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||||||
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# Installer logs
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||||||
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pip-log.txt
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||||||
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pip-delete-this-directory.txt
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||||||
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||||||
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# Unit test / coverage reports
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||||||
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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||||||
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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||||||
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# Translations
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*.mo
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||||||
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*.pot
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||||||
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||||||
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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||||||
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||||||
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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||||||
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docs/_build/
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||||||
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||||||
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# PyBuilder
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.pybuilder/
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target/
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||||||
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# Jupyter Notebook
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.ipynb_checkpoints
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||||||
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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||||||
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# pipenv
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||||||
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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||||||
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
||||||
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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||||||
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# install all needed dependencies.
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||||||
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#Pipfile.lock
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||||||
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||||||
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# poetry
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||||||
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
||||||
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# This is especially recommended for binary packages to ensure reproducibility, and is more
|
||||||
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# commonly ignored for libraries.
|
||||||
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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||||||
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#poetry.lock
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||||||
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||||||
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# pdm
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||||||
|
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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||||||
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#pdm.lock
|
||||||
|
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
||||||
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# in version control.
|
||||||
|
# https://pdm.fming.dev/#use-with-ide
|
||||||
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.pdm.toml
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||||||
|
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||||||
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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||||||
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__pypackages__/
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||||||
|
|
||||||
|
# Celery stuff
|
||||||
|
celerybeat-schedule
|
||||||
|
celerybeat.pid
|
||||||
|
|
||||||
|
# SageMath parsed files
|
||||||
|
*.sage.py
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||||||
|
|
||||||
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# Environments
|
||||||
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.env
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.venv
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env/
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venv/
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ENV/
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||||||
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env.bak/
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||||||
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venv.bak/
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||||||
|
|
||||||
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# Spyder project settings
|
||||||
|
.spyderproject
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||||||
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.spyproject
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||||||
|
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||||||
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# Rope project settings
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||||||
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.ropeproject
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||||||
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||||||
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# mkdocs documentation
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||||||
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/site
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||||||
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# mypy
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.mypy_cache/
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||||||
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.dmypy.json
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||||||
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dmypy.json
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||||||
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|
||||||
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# Pyre type checker
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||||||
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.pyre/
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||||||
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||||||
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# pytype static type analyzer
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||||||
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.pytype/
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||||||
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# Cython debug symbols
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||||||
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cython_debug/
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||||||
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||||||
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# PyCharm
|
||||||
|
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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||||||
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
|
||||||
|
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
||||||
|
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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||||||
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.idea
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||||||
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.venv
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||||||
|
.ipynb_checkpoints
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||||||
250
22lb/Untitled.ipynb
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250
22lb/Untitled.ipynb
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@ -0,0 +1,250 @@
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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": 1,
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"id": "75d19e99-7e7a-47f6-9e31-537e645d8f3c",
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||||||
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"metadata": {},
|
||||||
|
"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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"Первый взгляд на данные:\n",
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" Имя Возраст Баллы\n",
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"0 Анна 21 89\n",
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"1 Борис 22 76\n",
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"2 Виктор 23 95\n",
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"3 Галина 24 82\n",
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||||||
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"<class 'pandas.DataFrame'>\n",
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||||||
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"RangeIndex: 4 entries, 0 to 3\n",
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||||||
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"Data columns (total 3 columns):\n",
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||||||
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" # Column Non-Null Count Dtype\n",
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||||||
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"--- ------ -------------- -----\n",
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" 0 Имя 4 non-null str \n",
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" 1 Возраст 4 non-null int64\n",
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" 2 Баллы 4 non-null int64\n",
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||||||
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"dtypes: int64(2), str(1)\n",
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"memory usage: 228.0 bytes\n",
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"None\n",
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" Возраст Баллы\n",
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"count 4.000000 4.000000\n",
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||||||
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"mean 22.500000 85.500000\n",
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||||||
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"std 1.290994 8.266398\n",
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||||||
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"min 21.000000 76.000000\n",
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||||||
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"25% 21.750000 80.500000\n",
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||||||
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"50% 22.500000 85.500000\n",
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||||||
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"75% 23.250000 90.500000\n",
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||||||
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"max 24.000000 95.000000\n",
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"Имя 0\n",
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"Возраст 0\n",
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||||||
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"Баллы 0\n",
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||||||
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"dtype: int64\n"
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]
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||||||
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}
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||||||
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],
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"source": [
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"import pandas as pd\n",
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"\n",
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||||||
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"# Создадим DataFrame\n",
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"data = {\n",
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" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
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||||||
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" \"Возраст\": [21, 22, 23, 24],\n",
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" \"Баллы\": [89, 76, 95, 82]\n",
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"}\n",
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"df = pd.DataFrame(data)\n",
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"\n",
|
||||||
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"print(\"Первый взгляд на данные:\")\n",
|
||||||
|
"print(df.head())\n",
|
||||||
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"print(df.info())\n",
|
||||||
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"print(df.describe())\n",
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||||||
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"print(df.isnull().sum())"
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||||||
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]
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||||||
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},
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||||||
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{
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||||||
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"cell_type": "code",
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||||||
|
"execution_count": 2,
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||||||
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"id": "5d78faf3-86e3-4af2-938a-9c49db11ca0b",
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||||||
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"metadata": {},
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||||||
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"outputs": [
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||||||
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{
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||||||
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"data": {
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||||||
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"text/html": [
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||||||
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"<div>\n",
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||||||
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"<style scoped>\n",
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||||||
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" .dataframe tbody tr th:only-of-type {\n",
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||||||
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" vertical-align: middle;\n",
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||||||
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" }\n",
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||||||
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"\n",
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||||||
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" .dataframe tbody tr th {\n",
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||||||
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" vertical-align: top;\n",
|
||||||
|
" }\n",
|
||||||
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"\n",
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||||||
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" .dataframe thead th {\n",
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||||||
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" text-align: right;\n",
|
||||||
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" }\n",
|
||||||
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"</style>\n",
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||||||
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"<table border=\"1\" class=\"dataframe\">\n",
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||||||
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" <thead>\n",
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||||||
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" <tr style=\"text-align: right;\">\n",
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||||||
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" <th></th>\n",
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||||||
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" <th>Имя</th>\n",
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||||||
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" <th>Возраст</th>\n",
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||||||
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" <th>Баллы</th>\n",
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" </tr>\n",
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||||||
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" </thead>\n",
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||||||
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" <tbody>\n",
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||||||
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" <tr>\n",
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||||||
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" <th>0</th>\n",
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||||||
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" <td>Анна</td>\n",
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||||||
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" <td>21</td>\n",
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||||||
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" <td>89</td>\n",
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" </tr>\n",
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||||||
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" <tr>\n",
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||||||
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" <th>1</th>\n",
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||||||
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" <td>Борис</td>\n",
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||||||
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" <td>22</td>\n",
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||||||
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" <td>76</td>\n",
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||||||
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" </tr>\n",
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||||||
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" <tr>\n",
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||||||
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" <th>2</th>\n",
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" <td>Виктор</td>\n",
|
||||||
|
" <td>23</td>\n",
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||||||
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" <td>95</td>\n",
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||||||
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" </tr>\n",
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||||||
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" <tr>\n",
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||||||
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" <th>3</th>\n",
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||||||
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" <td>Галина</td>\n",
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||||||
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" <td>24</td>\n",
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" <td>82</td>\n",
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||||||
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" </tr>\n",
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||||||
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" </tbody>\n",
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||||||
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"</table>\n",
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||||||
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"</div>"
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||||||
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],
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"text/plain": [
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" Имя Возраст Баллы\n",
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"0 Анна 21 89\n",
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||||||
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"1 Борис 22 76\n",
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"2 Виктор 23 95\n",
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||||||
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"3 Галина 24 82"
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]
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||||||
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},
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||||||
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"execution_count": 2,
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||||||
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"metadata": {},
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||||||
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"output_type": "execute_result"
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||||||
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}
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||||||
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],
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||||||
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"source": [
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"df"
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]
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},
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||||||
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{
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||||||
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"cell_type": "code",
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||||||
|
"execution_count": 3,
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||||||
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"id": "1bc4b60e-2c46-4cf7-8da7-08770555c62f",
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||||||
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"metadata": {},
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||||||
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"outputs": [
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{
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||||||
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"data": {
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"text/html": [
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||||||
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"<div>\n",
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||||||
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"<style scoped>\n",
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||||||
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" .dataframe tbody tr th:only-of-type {\n",
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||||||
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" vertical-align: middle;\n",
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||||||
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" }\n",
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||||||
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"\n",
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||||||
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" .dataframe tbody tr th {\n",
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||||||
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" vertical-align: top;\n",
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||||||
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" }\n",
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||||||
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"\n",
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||||||
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" .dataframe thead th {\n",
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||||||
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" text-align: right;\n",
|
||||||
|
" }\n",
|
||||||
|
"</style>\n",
|
||||||
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"<table border=\"1\" class=\"dataframe\">\n",
|
||||||
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" <thead>\n",
|
||||||
|
" <tr style=\"text-align: right;\">\n",
|
||||||
|
" <th></th>\n",
|
||||||
|
" <th>Имя</th>\n",
|
||||||
|
" <th>Возраст</th>\n",
|
||||||
|
" <th>Баллы</th>\n",
|
||||||
|
" <th>Новый столбец</th>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" </thead>\n",
|
||||||
|
" <tbody>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>1</th>\n",
|
||||||
|
" <td>Борис</td>\n",
|
||||||
|
" <td>22</td>\n",
|
||||||
|
" <td>76</td>\n",
|
||||||
|
" <td>83.6</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>2</th>\n",
|
||||||
|
" <td>Виктор</td>\n",
|
||||||
|
" <td>23</td>\n",
|
||||||
|
" <td>95</td>\n",
|
||||||
|
" <td>104.5</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <th>3</th>\n",
|
||||||
|
" <td>Галина</td>\n",
|
||||||
|
" <td>24</td>\n",
|
||||||
|
" <td>82</td>\n",
|
||||||
|
" <td>90.2</td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
" </tbody>\n",
|
||||||
|
"</table>\n",
|
||||||
|
"</div>"
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||||||
|
],
|
||||||
|
"text/plain": [
|
||||||
|
" Имя Возраст Баллы Новый столбец\n",
|
||||||
|
"1 Борис 22 76 83.6\n",
|
||||||
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"2 Виктор 23 95 104.5\n",
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||||||
|
"3 Галина 24 82 90.2"
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||||||
|
]
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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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"source": [
|
||||||
|
"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
|
||||||
|
"df\n",
|
||||||
|
"df.groupby(\"Имя\").agg({\"Баллы\": \"mean\"})\n",
|
||||||
|
"df[df[\"Возраст\"] > 21]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "306c6886-f00d-4317-ad69-f4d9f11220a4",
|
||||||
|
"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": "3.14.3"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
86
22lb/Untitled1.ipynb
Normal file
86
22lb/Untitled1.ipynb
Normal file
@ -0,0 +1,86 @@
|
|||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 1,
|
||||||
|
"id": "fcb09a3f-8f09-442f-9dc0-05087980216c",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"Матрица 2x3:\n",
|
||||||
|
" [[1 2 3]\n",
|
||||||
|
" [4 5 6]]\n",
|
||||||
|
"Форма (shape): (2, 3)\n",
|
||||||
|
"------------------------------\n",
|
||||||
|
"Равномерная шкала (linspace):\n",
|
||||||
|
" [0. 0.55555556 1.11111111 1.66666667 2.22222222 2.77777778\n",
|
||||||
|
" 3.33333333 3.88888889 4.44444444 5. ]\n",
|
||||||
|
"------------------------------\n",
|
||||||
|
"Случайная матрица 2x2:\n",
|
||||||
|
" [[-0.95758367 0.58589362]\n",
|
||||||
|
" [-0.25530405 1.71658099]]\n",
|
||||||
|
"------------------------------\n",
|
||||||
|
"Результат матричного умножения A и B:\n",
|
||||||
|
" [[19 22]\n",
|
||||||
|
" [43 50]]\n",
|
||||||
|
"------------------------------\n",
|
||||||
|
"Сумма по столбцам матрицы: [5 7 9]\n",
|
||||||
|
"Среднее по строкам матрицы: [2. 5.]\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"import numpy as np\n",
|
||||||
|
"matrix = np.array([[1, 2, 3], [4, 5, 6]])\n",
|
||||||
|
"print(\"Матрица 2x3:\\n\", matrix)\n",
|
||||||
|
"print(\"Форма (shape):\", matrix.shape)\n",
|
||||||
|
"print(\"-\" * 30)\n",
|
||||||
|
"linear_space = np.linspace(0, 5, 10)\n",
|
||||||
|
"print(\"Равномерная шкала (linspace):\\n\", linear_space)\n",
|
||||||
|
"print(\"-\" * 30)\n",
|
||||||
|
"random_matrix = np.random.randn(2, 2)\n",
|
||||||
|
"print(\"Случайная матрица 2x2:\\n\", random_matrix)\n",
|
||||||
|
"print(\"-\" * 30)\n",
|
||||||
|
"A = np.array([[1, 2], [3, 4]])\n",
|
||||||
|
"B = np.array([[5, 6], [7, 8]])\n",
|
||||||
|
"dot_product = np.dot(A, B)\n",
|
||||||
|
"print(\"Результат матричного умножения A и B:\\n\", dot_product)\n",
|
||||||
|
"print(\"-\" * 30)\n",
|
||||||
|
"print(\"Сумма по столбцам матрицы:\", matrix.sum(axis=0))\n",
|
||||||
|
"print(\"Среднее по строкам матрицы:\", matrix.mean(axis=1))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "1d0670c4-4ce2-4024-b803-456646dbb94f",
|
||||||
|
"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": "3.14.3"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
79
22lb/Untitled2.ipynb
Normal file
79
22lb/Untitled2.ipynb
Normal file
File diff suppressed because one or more lines are too long
110
22lb/Untitled3.ipynb
Normal file
110
22lb/Untitled3.ipynb
Normal file
@ -0,0 +1,110 @@
|
|||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 6,
|
||||||
|
"id": "f3b57c0d-557d-41fd-9dcb-5bd23450d4d1",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"========== ЭТАП 1: ОБРАБОТКА ==========\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"application/vnd.jupyter.widget-view+json": {
|
||||||
|
"model_id": "4ba14952aa5b44cab19264f1070e2952",
|
||||||
|
"version_major": 2,
|
||||||
|
"version_minor": 0
|
||||||
|
},
|
||||||
|
"text/plain": [
|
||||||
|
"Анализ строк: 0%| | 0/100 [00:00<?, ?строк/s]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"\n",
|
||||||
|
"======================================\n",
|
||||||
|
"\n",
|
||||||
|
"========== ЭТАП 2: НЕЙРОСЕТЬ ==========\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"application/vnd.jupyter.widget-view+json": {
|
||||||
|
"model_id": "3e5da2b4604645d18fa78063105cbc7a",
|
||||||
|
"version_major": 2,
|
||||||
|
"version_minor": 0
|
||||||
|
},
|
||||||
|
"text/plain": [
|
||||||
|
"Загрузка весов: 0%| | 0/100 [00:00<?, ? слоев/s]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "display_data"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"import pandas as pd\n",
|
||||||
|
"import numpy as np\n",
|
||||||
|
"from tqdm.auto import tqdm \n",
|
||||||
|
"import time\n",
|
||||||
|
"\n",
|
||||||
|
"df = pd.DataFrame({\n",
|
||||||
|
" 'ID': range(1, 101),\n",
|
||||||
|
" 'Data': np.random.randn(100)\n",
|
||||||
|
"})\n",
|
||||||
|
"\n",
|
||||||
|
"print(f\"{'='*10} ЭТАП 1: ОБРАБОТКА {'='*10}\")\n",
|
||||||
|
"# Использование tqdm напрямую для итерации по строкам\n",
|
||||||
|
"for _ in tqdm(df.values, desc=\"Анализ строк\", unit=\"строк\"):\n",
|
||||||
|
" time.sleep(0.01) # Ускорил для теста\n",
|
||||||
|
"\n",
|
||||||
|
"print(\"\\n\" + \"=\"*38 + \"\\n\")\n",
|
||||||
|
"print(f\"{'='*10} ЭТАП 2: НЕЙРОСЕТЬ {'='*10}\")\n",
|
||||||
|
"for i in tqdm(range(100), \n",
|
||||||
|
" desc='Загрузка весов', \n",
|
||||||
|
" unit=' слоев', \n",
|
||||||
|
" colour='green'):\n",
|
||||||
|
" time.sleep(0.02)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "fdc92940-7e90-4489-948f-0141f7441baa",
|
||||||
|
"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": "3.14.3"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
100
22lb/Untitled4.ipynb
Normal file
100
22lb/Untitled4.ipynb
Normal file
File diff suppressed because one or more lines are too long
252
22lb/Untitled5.ipynb
Normal file
252
22lb/Untitled5.ipynb
Normal file
File diff suppressed because one or more lines are too long
26
22lb/golden_age_literature.csv
Normal file
26
22lb/golden_age_literature.csv
Normal file
@ -0,0 +1,26 @@
|
|||||||
|
title,popularity,vote_average,vote_count,release_year
|
||||||
|
Евгений Онегин,95.2,9.8,15000,1833
|
||||||
|
Герой нашего времени,88.4,9.5,12000,1840
|
||||||
|
Война и мир,120.1,9.7,18000,1869
|
||||||
|
Преступление и наказание,110.5,9.6,17500,1866
|
||||||
|
Мертвые души,75.3,9.2,10500,1842
|
||||||
|
Отцы и дети,65.8,8.8,9000,1862
|
||||||
|
Анна Каренина,105.2,9.4,14000,1877
|
||||||
|
Идиот,92.7,9.3,13000,1868
|
||||||
|
Капитанская дочка,55.4,8.9,8500,1836
|
||||||
|
Шинель,45.1,8.7,7000,1842
|
||||||
|
Братья Карамазовы,115.8,9.8,16000,1880
|
||||||
|
Ревизор,70.2,9.1,9500,1836
|
||||||
|
Руслан и Людмила,40.5,8.5,6000,1820
|
||||||
|
Обломов,58.9,8.6,8200,1859
|
||||||
|
Горе от ума,62.4,9.0,8800,1825
|
||||||
|
Демон,35.7,8.8,5400,1839
|
||||||
|
Муму,30.2,8.2,4500,1854
|
||||||
|
Бедные люди,25.4,8.4,3800,1846
|
||||||
|
Гроза,48.6,8.3,7200,1859
|
||||||
|
Левша,32.1,8.5,5100,1881
|
||||||
|
Нос,42.8,8.9,6800,1836
|
||||||
|
Пиковая дама,50.3,9.1,7400,1834
|
||||||
|
Вишневый сад,82.5,9.2,11000,1903
|
||||||
|
Борис Годунов,44.2,8.7,5900,1831
|
||||||
|
Бесприданница,38.9,8.4,6100,1878
|
||||||
|
Loading…
Reference in New Issue
Block a user