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Этот метод позволяет удалить строки, содержащие пропущенные значения (NaN) в указанных столбцах или во всех столбцах.\r\n\r\n```python\r\nimport pandas as pd\r\n\r\n# Создаем исходный DataFrame\r\ndata = {'A': [1, 2, None, 4],\r\n 'B': [None, 5, 6, 7],\r\n 'C': [8, 9, 10, 11]}\r\ndf = pd.DataFrame(data)\r\n\r\n# Удаление всех строк с пропущенными значениями\r\ndf_cleaned = df.dropna()\r\n```\r\n\r\nВ результате выполнения данного кода будут удалены строки, в которых хотя бы одно значение равно NaN. Теперь DataFrame df_cleaned будет содержать только строки без пропущенных значений.\r\n\r\nЕсли необходимо удалить только строки, в которых все значения равны NaN, то можно использовать параметр how='all':\r\n\r\n```python\r\n# Удаление только строк, в которых все значения NaN\r\ndf_cleaned = df.dropna(how='all')\r\n```\r\n\r\nТакже можно использовать параметр subset для указания столбцов, в которых нужно проверять наличие пропущенных значений:\r\n\r\n```python\r\n# Удаление строк с пропущенными значениями только в столбцах 'A' и 'B'\r\ndf_cleaned = df.dropna(subset=['A', 'B'])\r\n```\r\n\r\nТеперь DataFrame df_cleaned будет содержать только строки, в которых значения в столбцах 'A' и 'B' не являются NaN.","votes_up_count":0,"votes_down_count":0,"created_at":"2024-05-29T12:41:46.390Z","user_id":294764,"category_slug":"data-analytics"}],"relatedQuestions":[{"creator":{"id":583099,"email":"shade.mailbox@gmail.com","first_name":"Arthur","last_name":"Cheremisin","telegram":"","full_name":"Arthur Cheremisin","removed":false},"category":{"id":13,"title":"Аналитика данных","slug":"data-analytics","questions_count":219,"locale":"ru"},"tags":[{"id":1096,"slug":"analitika","name":"Аналитика"},{"id":1095,"slug":"data-analitika","name":"data-аналитика"}],"id":2699,"answers_count":1,"slug":"chto-takoe-ctr","state":"published","title":"что такое ctr\r","created_at":"2023-03-29T12:39:31.634Z","details":null,"best_answer_id":4289,"related_stacks_count":5},{"creator":{"id":583099,"email":"shade.mailbox@gmail.com","first_name":"Arthur","last_name":"Cheremisin","telegram":"","full_name":"Arthur Cheremisin","removed":false},"category":{"id":13,"title":"Аналитика 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установить\r","created_at":"2023-03-29T12:39:31.811Z","details":null,"best_answer_id":4287,"related_stacks_count":5},{"creator":{"id":583099,"email":"shade.mailbox@gmail.com","first_name":"Arthur","last_name":"Cheremisin","telegram":"","full_name":"Arthur Cheremisin","removed":false},"category":{"id":13,"title":"Аналитика данных","slug":"data-analytics","questions_count":219,"locale":"ru"},"tags":[{"id":1095,"slug":"data-analitika","name":"data-аналитика"},{"id":1096,"slug":"analitika","name":"Аналитика"}],"id":2702,"answers_count":1,"slug":"matplotlib-pyplot-chto-eto","state":"published","title":"matplotlib pyplot что это\r","created_at":"2023-03-29T12:39:31.873Z","details":null,"best_answer_id":4286,"related_stacks_count":5},{"creator":{"id":583099,"email":"shade.mailbox@gmail.com","first_name":"Arthur","last_name":"Cheremisin","telegram":"","full_name":"Arthur Cheremisin","removed":false},"category":{"id":13,"title":"Аналитика 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Этот метод позволяет удалить строки, содержащие пропущенные значения (NaN) в указанных столбцах или во всех столбцах.\r\n\r\n```python\r\nimport pandas as pd\r\n\r\n# Создаем исходный DataFrame\r\ndata = {'A': [1, 2, None, 4],\r\n 'B': [None, 5, 6, 7],\r\n 'C': [8, 9, 10, 11]}\r\ndf = pd.DataFrame(data)\r\n\r\n# Удаление всех строк с пропущенными значениями\r\ndf_cleaned = df.dropna()\r\n```\r\n\r\nВ результате выполнения данного кода будут удалены строки, в которых хотя бы одно значение равно NaN. Теперь DataFrame df_cleaned будет содержать только строки без пропущенных значений.\r\n\r\nЕсли необходимо удалить только строки, в которых все значения равны NaN, то можно использовать параметр how='all':\r\n\r\n```python\r\n# Удаление только строк, в которых все значения NaN\r\ndf_cleaned = df.dropna(how='all')\r\n```\r\n\r\nТакже можно использовать параметр subset для указания столбцов, в которых нужно проверять наличие пропущенных значений:\r\n\r\n```python\r\n# Удаление строк с пропущенными значениями только в столбцах 'A' и 'B'\r\ndf_cleaned = df.dropna(subset=['A', 'B'])\r\n```\r\n\r\nТеперь DataFrame df_cleaned будет содержать только строки, в которых значения в столбцах 'A' и 'B' не являются NaN.","datePublished":"2024-05-29T12:41:46.390Z","upvoteCount":0,"author":{"@type":"Person","name":"Ivan Mamtsev"},"url":"https://ru.hexlet.io/qna/data-analytics/questions/pandas-kak-udalit-pustye-stroki#answer-3789"}]}}</script><div style="--container-size:var(--container-size-lg);margin-top:var(--mantine-spacing-xl);height:100%" class="m_7485cace mantine-Container-root" data-size="lg" data-strategy="block"><script type="application/ld+json">{"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"position":1,"@type":"ListItem","item":{"@id":"/qna","name":"Вопросы и ответы"}},{"position":2,"@type":"ListItem","item":{"@id":"/qna/data-analytics/questions","name":"Аналитика данных"}},{"position":3,"@type":"ListItem","item":{"@id":"/qna/data-analytics/questions/pandas-kak-udalit-pustye-stroki","name":"pandas как удалить пустые строки\r"}}]}</script><div style="margin-bottom:var(--mantine-spacing-xs)" class="m_8b3717df mantine-Breadcrumbs-root"><a style="--text-fz:var(--mantine-font-size-sm);--text-lh:var(--mantine-line-height-sm);white-space:normal;color:inherit" class="mantine-focus-auto m_849cf0da m_f678d540 mantine-Breadcrumbs-breadcrumb m_b6d8b162 mantine-Text-root mantine-Anchor-root" data-size="sm" data-underline="hover" href="/"><div style="color:inherit" class="m_4451eb3a mantine-Center-root"><svg xmlns="http://www.w3.org/2000/svg" width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-home-link "><path d="M20.085 11.085l-8.085 -8.085l-9 9h2v7a2 2 0 0 0 2 2h4.5"></path><path d="M9 21v-6a2 2 0 0 1 2 -2h2a2 2 0 0 1 1.807 1.143"></path><path d="M20 21a1 1 0 1 0 2 0a1 1 0 1 0 -2 0"></path><path d="M20 16a1 1 0 1 0 2 0a1 1 0 1 0 -2 0"></path><path d="M15 19a1 1 0 1 0 2 0a1 1 0 1 0 -2 0"></path><path d="M21 16l-5 3l5 2"></path></svg></div></a><div class="m_3b8f2208 mantine-Breadcrumbs-separator">/</div><a style="--text-fz:var(--mantine-font-size-sm);--text-lh:var(--mantine-line-height-sm);white-space:normal;color:inherit" class="mantine-focus-auto m_849cf0da m_f678d540 mantine-Breadcrumbs-breadcrumb m_b6d8b162 mantine-Text-root mantine-Anchor-root" data-size="sm" data-underline="hover" href="/qna">Вопросы и ответы</a><div class="m_3b8f2208 mantine-Breadcrumbs-separator">/</div><a style="--text-fz:var(--mantine-font-size-sm);--text-lh:var(--mantine-line-height-sm);white-space:normal;color:inherit" class="mantine-focus-auto m_849cf0da m_f678d540 mantine-Breadcrumbs-breadcrumb m_b6d8b162 mantine-Text-root mantine-Anchor-root" data-size="sm" data-underline="hover" href="/qna/data-analytics/questions">Аналитика данных</a><div class="m_3b8f2208 mantine-Breadcrumbs-separator">/</div><p style="--text-fz:var(--mantine-font-size-sm);--text-lh:var(--mantine-line-height-sm);white-space:normal;color:var(--mantine-color-dimmed)" class="mantine-focus-auto m_f678d540 mantine-Breadcrumbs-breadcrumb m_b6d8b162 mantine-Text-root" data-size="sm">pandas как удалить пустые строки
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class="m_347db0ec mantine-Badge-root" data-variant="default" data-size="sm"><span class="m_5add502a mantine-Badge-label">data-аналитика</span></div></a></div><div style="--group-gap:var(--mantine-spacing-md);--group-align:center;--group-justify:flex-start;--group-wrap:wrap;margin-bottom:var(--mantine-spacing-xl);font-size:var(--mantine-font-size-sm)" class="m_4081bf90 mantine-Group-root"><div style="--group-gap:calc(0.25rem * var(--mantine-scale));--group-align:center;--group-justify:flex-start;--group-wrap:wrap;margin-inline-start:auto" class="m_4081bf90 mantine-Group-root"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-calendar "><path d="M4 7a2 2 0 0 1 2 -2h12a2 2 0 0 1 2 2v12a2 2 0 0 1 -2 2h-12a2 2 0 0 1 -2 -2v-12"></path><path d="M16 3v4"></path><path d="M8 3v4"></path><path d="M4 11h16"></path><path d="M11 15h1"></path><path d="M12 15v3"></path></svg><p class="mantine-focus-auto m_b6d8b162 mantine-Text-root" data-inherit="true">3 года назад</p></div><div style="--group-gap:calc(0.25rem * var(--mantine-scale));--group-align:center;--group-justify:flex-start;--group-wrap:wrap" class="m_4081bf90 mantine-Group-root"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-user "><path d="M8 7a4 4 0 1 0 8 0a4 4 0 0 0 -8 0"></path><path d="M6 21v-2a4 4 0 0 1 4 -4h4a4 4 0 0 1 4 4v2"></path></svg><p class="mantine-focus-auto m_b6d8b162 mantine-Text-root" data-inherit="true">Arthur Cheremisin</p></div></div><div role="link" tabindex="0" style="cursor:pointer"><button style="display:block;width:100%" class="mantine-focus-auto m_87cf2631 mantine-UnstyledButton-root" type="button" aria-label="Присоединяйтесь к нашему Telegram-сообществу"><div style="background-color:light-dark(var(--mantine-color-gray-1), var(--mantine-color-dark-6));margin-block:var(--mantine-spacing-xs)" class="m_e615b15f mantine-Card-root m_1b7284a3 mantine-Paper-root"><div style="--group-gap:var(--mantine-spacing-md);--group-align:center;--group-justify:flex-start;--group-wrap:wrap" class="m_4081bf90 mantine-Group-root"><div style="--ti-bg:transparent;--ti-color:var(--mantine-color-indigo-light-color);--ti-bd:calc(0.0625rem * var(--mantine-scale)) solid transparent;margin-inline-end:auto;color:inherit" class="m_7341320d mantine-ThemeIcon-root" data-variant="transparent"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-brand-telegram "><path d="M15 10l-4 4l6 6l4 -16l-18 7l4 2l2 6l3 -4"></path></svg></div>Присоединяйтесь к нашему Telegram-сообществу</div></div></button></div><h2 style="--title-fw:var(--mantine-h2-font-weight);--title-lh:var(--mantine-h2-line-height);--title-fz:var(--mantine-h2-font-size);margin-block:var(--mantine-spacing-xl)" class="m_8a5d1357 mantine-Title-root" data-order="2">Ответы</h2><div style="margin-bottom:var(--mantine-spacing-xl);padding:var(--mantine-spacing-lg)" class="m_e615b15f mantine-Card-root m_1b7284a3 mantine-Paper-root" data-with-border="true" id="answer-3789"><div style="--group-gap:calc(1.125rem * var(--mantine-scale));--group-align:stretch;--group-justify:flex-start;--group-wrap:nowrap" class="m_4081bf90 mantine-Group-root"><div style="--stack-gap:var(--mantine-spacing-md);--stack-align:stretch;--stack-justify:flex-start;font-size:var(--mantine-font-size-h1);font-weight:lighter;text-align:center" class="m_6d731127 mantine-Stack-root">0<a style="color:inherit" class="mantine-focus-auto m_849cf0da m_b6d8b162 mantine-Text-root mantine-Anchor-root" data-underline="hover" href="/qna/data-analytics/questions/pandas-kak-udalit-pustye-stroki/answers/3789/vote"><div style="--ti-bg:transparent;--ti-color:var(--mantine-color-indigo-light-color);--ti-bd:calc(0.0625rem * var(--mantine-scale)) solid transparent;color:inherit" class="m_7341320d mantine-ThemeIcon-root" data-variant="transparent"><svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-thumb-up "><path d="M7 11v8a1 1 0 0 1 -1 1h-2a1 1 0 0 1 -1 -1v-7a1 1 0 0 1 1 -1h3a4 4 0 0 0 4 -4v-1a2 2 0 0 1 4 0v5h3a2 2 0 0 1 2 2l-1 5a2 3 0 0 1 -2 2h-7a3 3 0 0 1 -3 -3"></path></svg></div></a></div><div style="--stack-gap:var(--mantine-spacing-md);--stack-align:stretch;--stack-justify:flex-start;width:100%;min-width:0rem" class="m_6d731127 mantine-Stack-root"><div style="margin-bottom:auto" class="m_d08caa0 mantine-Typography-root"><p>Для удаления пустых строк из DataFrame в библиотеке Pandas можно использовать метод <code style="margin-bottom:var(--mantine-spacing-lg)" class="m_dfe9c588 mantine-InlineCodeHighlight-inlineCodeHighlight m_e597c321 mantine-CodeHighlight-codeHighlight m_dfe9c588 mantine-InlineCodeHighlight-inlineCodeHighlight">dropna()</code>. Этот метод позволяет удалить строки, содержащие пропущенные значения (NaN) в указанных столбцах или во всех столбцах.</p>
<div style="margin-bottom:var(--mantine-spacing-lg)" class="m_e597c321 mantine-CodeHighlight-codeHighlight" dir="ltr"><div class="m_be7e9c9c mantine-CodeHighlight-controls"><button style="--ai-bg:transparent;--ai-hover:transparent;--ai-color:inherit;--ai-bd:none" class="mantine-focus-auto mantine-active m_d498bab7 mantine-CodeHighlight-control m_8d3f4000 mantine-ActionIcon-root m_87cf2631 mantine-UnstyledButton-root" data-variant="none" type="button" aria-label="Copy code"><span class="m_8d3afb97 mantine-ActionIcon-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none"></path><path d="M8 8m0 2a2 2 0 0 1 2 -2h8a2 2 0 0 1 2 2v8a2 2 0 0 1 -2 2h-8a2 2 0 0 1 -2 -2z"></path><path d="M16 8v-2a2 2 0 0 0 -2 -2h-8a2 2 0 0 0 -2 2v8a2 2 0 0 0 2 2h2"></path></svg></span></button></div><div style="--scrollarea-scrollbar-size:calc(0.25rem * var(--mantine-scale));--sa-corner-width:0px;--sa-corner-height:0px" class="m_f744fd40 mantine-CodeHighlight-scrollarea m_d57069b5 mantine-ScrollArea-root" dir="ltr"><div style="overflow-x:hidden;overflow-y:hidden;overscroll-behavior-inline:none" class="m_c0783ff9 mantine-ScrollArea-viewport" data-scrollbars="xy"><div class="m_b1336c6 mantine-ScrollArea-content"><pre class="m_2c47c4fd mantine-CodeHighlight-pre" style="padding:0"><code class="m_5caae6d3 mantine-CodeHighlight-code">import pandas as pd
# Создаем исходный DataFrame
data = {'A': [1, 2, None, 4],
'B': [None, 5, 6, 7],
'C': [8, 9, 10, 11]}
df = pd.DataFrame(data)
# Удаление всех строк с пропущенными значениями
df_cleaned = df.dropna()</code></pre></div></div></div><button class="mantine-focus-auto m_c9378bc2 mantine-CodeHighlight-showCodeButton m_87cf2631 mantine-UnstyledButton-root" data-hidden="true" type="button">Expand code</button></div>
<p>В результате выполнения данного кода будут удалены строки, в которых хотя бы одно значение равно NaN. Теперь DataFrame df_cleaned будет содержать только строки без пропущенных значений.</p>
<p>Если необходимо удалить только строки, в которых все значения равны NaN, то можно использовать параметр how='all':</p>
<div style="margin-bottom:var(--mantine-spacing-lg)" class="m_e597c321 mantine-CodeHighlight-codeHighlight" dir="ltr"><div class="m_be7e9c9c mantine-CodeHighlight-controls"><button style="--ai-bg:transparent;--ai-hover:transparent;--ai-color:inherit;--ai-bd:none" class="mantine-focus-auto mantine-active m_d498bab7 mantine-CodeHighlight-control m_8d3f4000 mantine-ActionIcon-root m_87cf2631 mantine-UnstyledButton-root" data-variant="none" type="button" aria-label="Copy code"><span class="m_8d3afb97 mantine-ActionIcon-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none"></path><path d="M8 8m0 2a2 2 0 0 1 2 -2h8a2 2 0 0 1 2 2v8a2 2 0 0 1 -2 2h-8a2 2 0 0 1 -2 -2z"></path><path d="M16 8v-2a2 2 0 0 0 -2 -2h-8a2 2 0 0 0 -2 2v8a2 2 0 0 0 2 2h2"></path></svg></span></button></div><div style="--scrollarea-scrollbar-size:calc(0.25rem * var(--mantine-scale));--sa-corner-width:0px;--sa-corner-height:0px" class="m_f744fd40 mantine-CodeHighlight-scrollarea m_d57069b5 mantine-ScrollArea-root" dir="ltr"><div style="overflow-x:hidden;overflow-y:hidden;overscroll-behavior-inline:none" class="m_c0783ff9 mantine-ScrollArea-viewport" data-scrollbars="xy"><div class="m_b1336c6 mantine-ScrollArea-content"><pre class="m_2c47c4fd mantine-CodeHighlight-pre" style="padding:0"><code class="m_5caae6d3 mantine-CodeHighlight-code"># Удаление только строк, в которых все значения NaN
df_cleaned = df.dropna(how='all')</code></pre></div></div></div><button class="mantine-focus-auto m_c9378bc2 mantine-CodeHighlight-showCodeButton m_87cf2631 mantine-UnstyledButton-root" data-hidden="true" type="button">Expand code</button></div>
<p>Также можно использовать параметр subset для указания столбцов, в которых нужно проверять наличие пропущенных значений:</p>
<div style="margin-bottom:var(--mantine-spacing-lg)" class="m_e597c321 mantine-CodeHighlight-codeHighlight" dir="ltr"><div class="m_be7e9c9c mantine-CodeHighlight-controls"><button style="--ai-bg:transparent;--ai-hover:transparent;--ai-color:inherit;--ai-bd:none" class="mantine-focus-auto mantine-active m_d498bab7 mantine-CodeHighlight-control m_8d3f4000 mantine-ActionIcon-root m_87cf2631 mantine-UnstyledButton-root" data-variant="none" type="button" aria-label="Copy code"><span class="m_8d3afb97 mantine-ActionIcon-icon"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><path stroke="none" d="M0 0h24v24H0z" fill="none"></path><path d="M8 8m0 2a2 2 0 0 1 2 -2h8a2 2 0 0 1 2 2v8a2 2 0 0 1 -2 2h-8a2 2 0 0 1 -2 -2z"></path><path d="M16 8v-2a2 2 0 0 0 -2 -2h-8a2 2 0 0 0 -2 2v8a2 2 0 0 0 2 2h2"></path></svg></span></button></div><div style="--scrollarea-scrollbar-size:calc(0.25rem * var(--mantine-scale));--sa-corner-width:0px;--sa-corner-height:0px" class="m_f744fd40 mantine-CodeHighlight-scrollarea m_d57069b5 mantine-ScrollArea-root" dir="ltr"><div style="overflow-x:hidden;overflow-y:hidden;overscroll-behavior-inline:none" class="m_c0783ff9 mantine-ScrollArea-viewport" data-scrollbars="xy"><div class="m_b1336c6 mantine-ScrollArea-content"><pre class="m_2c47c4fd mantine-CodeHighlight-pre" style="padding:0"><code class="m_5caae6d3 mantine-CodeHighlight-code"># Удаление строк с пропущенными значениями только в столбцах 'A' и 'B'
df_cleaned = df.dropna(subset=['A', 'B'])</code></pre></div></div></div><button class="mantine-focus-auto m_c9378bc2 mantine-CodeHighlight-showCodeButton m_87cf2631 mantine-UnstyledButton-root" data-hidden="true" type="button">Expand code</button></div>
<p>Теперь DataFrame df_cleaned будет содержать только строки, в которых значения в столбцах 'A' и 'B' не являются NaN.</p></div><div class="m_3eebeb36 mantine-Divider-root" data-orientation="horizontal" role="separator"></div><div style="--group-gap:var(--mantine-spacing-md);--group-align:center;--group-justify:flex-start;--group-wrap:wrap;font-size:var(--mantine-font-size-sm)" class="m_4081bf90 mantine-Group-root"><div style="--group-gap:var(--mantine-spacing-xs);--group-align:center;--group-justify:flex-start;--group-wrap:wrap;margin-inline-start:auto" class="m_4081bf90 mantine-Group-root"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-calendar "><path d="M4 7a2 2 0 0 1 2 -2h12a2 2 0 0 1 2 2v12a2 2 0 0 1 -2 2h-12a2 2 0 0 1 -2 -2v-12"></path><path d="M16 3v4"></path><path d="M8 3v4"></path><path d="M4 11h16"></path><path d="M11 15h1"></path><path d="M12 15v3"></path></svg><p class="mantine-focus-auto m_b6d8b162 mantine-Text-root" data-inherit="true">2 года назад</p></div><div style="--group-gap:var(--mantine-spacing-xs);--group-align:center;--group-justify:flex-start;--group-wrap:wrap" class="m_4081bf90 mantine-Group-root"><svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.2" stroke-linecap="round" stroke-linejoin="round" class="tabler-icon tabler-icon-user "><path d="M8 7a4 4 0 1 0 8 0a4 4 0 0 0 -8 0"></path><path d="M6 21v-2a4 4 0 0 1 4 -4h4a4 4 0 0 1 4 4v2"></path></svg><p class="mantine-focus-auto m_b6d8b162 mantine-Text-root" data-inherit="true">Ivan Mamtsev</p></div></div></div></div></div><style data-mantine-styles="inline">.__m__-_R_4bbdiub_{--carousel-slide-gap:var(--mantine-spacing-xs);--carousel-slide-size:70%;}@media(min-width: 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style="cursor:pointer;height:100%"><a style="text-decoration:none" class="mantine-focus-auto m_849cf0da m_b6d8b162 mantine-Text-root mantine-Anchor-root" data-underline="hover" href="/programs/flask?promo_name=programs_list&promo_position=qna_question&promo_creative=catalog_card&promo_type=card" target="_blank"><div style="height:100%" class="m_e615b15f mantine-Card-root m_1b7284a3 mantine-Paper-root" data-with-border="true"><div style="--group-gap:calc(0.25rem * var(--mantine-scale));--group-align:center;--group-justify:flex-start;--group-wrap:nowrap" class="m_4081bf90 mantine-Group-root"><span style="font-size:var(--mantine-font-size-sm)" class="mantine-focus-auto m_b6d8b162 mantine-Text-root">1 месяц</span><span class="mantine-focus-auto m_b6d8b162 mantine-Text-root">·</span><span style="font-size:var(--mantine-font-size-sm)" class="mantine-focus-auto m_b6d8b162 mantine-Text-root">С нуля</span></div><p 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