Программирование на языке Python. Уровень 4. Data Science. Обработка, анализ и визуализация данных на языке Python. Библиотеки pandas, numpy, matplotlib и seaborn
направление:
вендор: Разработка
Даты проведения курса
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[NAME] => Программирование на языке Python. Уровень 4. Data Science. Обработка, анализ и визуализация данных на языке Python. Библиотеки pandas, numpy, matplotlib и seaborn
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[ID] => 186
[IBLOCK_ID] => 24
[NAME] => Подкатегория курса 4
[ACTIVE] => Y
[SORT] => 500
[CODE] => SECTION_CODE
[DEFAULT_VALUE] =>
[PROPERTY_TYPE] => S
[ROW_COUNT] => 1
[COL_COUNT] => 30
[LIST_TYPE] => L
[MULTIPLE] => N
[XML_ID] =>
[FILE_TYPE] =>
[MULTIPLE_CNT] => 5
[LINK_IBLOCK_ID] => 0
[WITH_DESCRIPTION] => N
[SEARCHABLE] => N
[FILTRABLE] => N
[IS_REQUIRED] => N
[VERSION] => 1
[USER_TYPE] =>
[USER_TYPE_SETTINGS] =>
[HINT] =>
[~NAME] => Подкатегория курса 4
[~DEFAULT_VALUE] =>
[VALUE_ENUM] =>
[VALUE_XML_ID] =>
[VALUE_SORT] =>
[VALUE] => 40
[PROPERTY_VALUE_ID] => 4966202
[DESCRIPTION] =>
[~VALUE] => 40
[~DESCRIPTION] =>
)
[SHOW_TO_MAIN] => Array
(
[ID] => 189
[IBLOCK_ID] => 24
[NAME] => Показывать на главной
[ACTIVE] => Y
[SORT] => 500
[CODE] => SHOW_TO_MAIN
[DEFAULT_VALUE] =>
[PROPERTY_TYPE] => L
[ROW_COUNT] => 1
[COL_COUNT] => 30
[LIST_TYPE] => C
[MULTIPLE] => N
[XML_ID] =>
[FILE_TYPE] =>
[MULTIPLE_CNT] => 5
[LINK_IBLOCK_ID] => 0
[WITH_DESCRIPTION] => N
[SEARCHABLE] => N
[FILTRABLE] => N
[IS_REQUIRED] => N
[VERSION] => 1
[USER_TYPE] =>
[USER_TYPE_SETTINGS] =>
[HINT] =>
[~NAME] => Показывать на главной
[~DEFAULT_VALUE] =>
[VALUE_ENUM] =>
[VALUE_XML_ID] =>
[VALUE_SORT] =>
[VALUE] =>
[PROPERTY_VALUE_ID] =>
[DESCRIPTION] =>
[~DESCRIPTION] =>
[~VALUE] =>
[VALUE_ENUM_ID] =>
)
)
[DISPLAY_PROPERTIES] => Array
(
[DATE_TO] => Array
(
[ID] => 102
[IBLOCK_ID] => 24
[NAME] => Окончание курса
[ACTIVE] => Y
[SORT] => 500
[CODE] => DATE_TO
[DEFAULT_VALUE] =>
[PROPERTY_TYPE] => S
[ROW_COUNT] => 1
[COL_COUNT] => 30
[LIST_TYPE] => L
[MULTIPLE] => N
[XML_ID] =>
[FILE_TYPE] =>
[MULTIPLE_CNT] => 5
[LINK_IBLOCK_ID] => 0
[WITH_DESCRIPTION] => N
[SEARCHABLE] => Y
[FILTRABLE] => Y
[IS_REQUIRED] => N
[VERSION] => 1
[USER_TYPE] => DateTime
[USER_TYPE_SETTINGS] =>
[HINT] =>
[~NAME] => Окончание курса
[~DEFAULT_VALUE] =>
[VALUE_ENUM] =>
[VALUE_XML_ID] =>
[VALUE_SORT] =>
[VALUE] => 10.12.2021
[PROPERTY_VALUE_ID] => 4966200
[DESCRIPTION] =>
[~VALUE] => 10.12.2021
[~DESCRIPTION] =>
[DISPLAY_VALUE] => 10.12.2021
)
)
[PRODUCT] => Array
(
[TYPE] => 4
[AVAILABLE] => Y
[MEASURE] =>
[VAT_ID] =>
[VAT_RATE] =>
[VAT_INCLUDED] => N
[QUANTITY] => 0
[QUANTITY_TRACE] => N
[CAN_BUY_ZERO] => N
[SUBSCRIPTION] =>
[BUNDLE] => N
)
[ITEM_PRICE_MODE] => S
[ITEM_PRICES] => Array
(
[0] => Array
(
[UNROUND_BASE_PRICE] => 35000
[UNROUND_PRICE] => 35000
[BASE_PRICE] => 35000
[PRICE] => 35000
[ID] => 63679
[PRICE_TYPE_ID] => 1
[CURRENCY] => RUB
[DISCOUNT] => 0
[PERCENT] => 0
[VAT] => 0
[QUANTITY_FROM] =>
[QUANTITY_TO] =>
[QUANTITY_HASH] => ZERO-INF
[MEASURE_RATIO_ID] =>
[PRINT_BASE_PRICE] => 35 000 руб.
[RATIO_BASE_PRICE] => 35000
[PRINT_RATIO_BASE_PRICE] => 35 000 руб.
[PRINT_PRICE] => 35 000 руб.
[RATIO_PRICE] => 35000
[PRINT_RATIO_PRICE] => 35 000 руб.
[PRINT_DISCOUNT] => 0 руб.
[RATIO_DISCOUNT] => 0
[PRINT_RATIO_DISCOUNT] => 0 руб.
[PRINT_VAT] => 0 руб.
[RATIO_VAT] => 0
[PRINT_RATIO_VAT] => 0 руб.
[MIN_QUANTITY] => 1
)
)
[ITEM_QUANTITY_RANGES] => Array
(
[ZERO-INF] => Array
(
[HASH] => ZERO-INF
[QUANTITY_FROM] =>
[QUANTITY_TO] =>
[SORT_FROM] => 0
[SORT_TO] => INF
)
)
[ITEM_MEASURE_RATIOS] => Array
(
[0] => Array
(
[ID] => 0
[RATIO] => 1
[IS_DEFAULT] => Y
)
)
[ITEM_MEASURE] => Array
(
[ID] =>
[TITLE] => место
[~TITLE] => место
)
[ITEM_MEASURE_RATIO_SELECTED] => 0
[ITEM_QUANTITY_RANGE_SELECTED] => ZERO-INF
[ITEM_PRICE_SELECTED] => 0
[CHECK_QUANTITY] =>
[CATALOG_MEASURE_NAME] => место
[~CATALOG_MEASURE_NAME] => место
[CAN_BUY] => 1
[ITEM_PRICES_CAN_BUY] => 1
[~BUY_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=BUY&id=61273
[BUY_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=BUY&id=61273
[~ADD_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=ADD2BASKET&id=61273
[ADD_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=ADD2BASKET&id=61273
[~SUBSCRIBE_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=SUBSCRIBE_PRODUCT&id=61273
[SUBSCRIBE_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=SUBSCRIBE_PRODUCT&id=61273
[~COMPARE_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=ADD_TO_COMPARE_LIST&id=61273
[COMPARE_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=ADD_TO_COMPARE_LIST&id=61273
[~COMPARE_DELETE_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=DELETE_FROM_COMPARE_LIST&id=61273
[COMPARE_DELETE_URL] => /courses/Python_4/?ELEMENT_CODE=Python_4&action=DELETE_FROM_COMPARE_LIST&id=61273
[CATALOG_MEASURE_RATIO] => 1
[OFFER_GROUP] =>
[RATIO_PRICE] => Array
(
[VALUE] => 35000
[DISCOUNT_VALUE] => 35000
[PRINT_VALUE] => 35 000 руб.
[PRINT_DISCOUNT_VALUE] => 35 000 руб.
[DISCOUNT_DIFF] => 0
[PRINT_DISCOUNT_DIFF] => 0 руб.
[DISCOUNT_DIFF_PERCENT] => 0
[CURRENCY] => RUB
)
[MORE_PHOTO] => Array
(
[0] => Array
(
[SRC] => /bitrix/templates/.default/components/bitrix/catalog.element/course/images/no_photo.png
[WIDTH] => 150
[HEIGHT] => 150
)
)
[MORE_PHOTO_COUNT] => 1
)
)
- 06.12.2021 Москва записаться
Преподаватель курса - Рулев Сергей
1. Установка и настройка программного обеспечения. Базовый инструментарий работы в Jupyter notebook (4 ак.ч.)
• Принципы организации и управления вычислениями
• Используемые языки программирования и взаимосвязь между ними
• Обзор библиотек и инструментов
• Необходимые пакеты Python: numpy, pandas, matplotlib, seaborn, Jupyter и другие
• Дистрибутив Anaconda, его преимущества и недостатки
• Установка пакетов в Linux
• Установка пакетов в Windows. Возможные проблемы и методы их решения
• Методы и функции
• Основные команды и методы работы в Jupyter notebook
2. Библиотека numpy. Вычислительные задачи. (6 ак.ч.)
• Структура библиотеки
• Типы данных библиотеки numpy
• Векторы и массивы, специальные типы данных
• Понятие массива и его основные характеристики
• Принципы вычислений
• Универсальные функции
• Важнейшие стандартные функции
• Работа с массивами и матрицами
3. Библиотека pandas и анализ данных (6 ак.ч.)
• Объект Series
• Объект DataFrame
• Загрузка данных
• Выгрузка данных
• Чтение и запись данных в формате Excel
• Чтение и запись JSON-файлов
• Загрузка данных из интернета и из базы данных SQL
• Загрузка CSV-файлов из Интернета
• Основы работы с датафреймами
• Организация колонок и строчек
• Создание срезов объекта Series
• Выравнивание данных по меткам индекса
• Выполнение логического отбора
• Переиндексация объекта Series
4. Первичная обработка данных. (8 ак.ч.)
• Сбор данных
• Очистка данных
• Подготовка данных
• Объединение данных
• Сцепление и наложение
• Слияние данных
• Замена значений
• Работа с пропущенными значениями и их заполнение
• Повторы в данных
• Объединение и переформирование данных
5. Статистика и анализ (8 ак.ч.)
• Фильтрация
• Группировка
• Агрегация
• Описательные статистики
• Получение итоговых описательных статистик
• Измерение центральной тенденции: среднее, медиана и мода
• Вычисление дисперсии и стандартного отклонения
• Вычисление ковариации и корреляции
• Распределения
• Разведывательный анализ
• Постановка гипотезы
6. Библиотека matplotlib. Визуализация данных. (4 ак.ч.)
• Основные элементы диаграммы
• Создание диаграммы
• Виды графиков и диаграмм
• Оформление и кастомизация графиков
• Форматы изображений
7. Библиотека seaborn. Наглядная визуализация сложных данных. (4 ак.ч.)
• Виды графиков, их корректное использование и интерпретация
• Принципы хорошей визуализации, основные ошибки при визуализации данных
• График функции
• Гистограмма
• Визуализации отфильтрованных и сгруппированных данных
• Принципы организации и управления вычислениями
• Используемые языки программирования и взаимосвязь между ними
• Обзор библиотек и инструментов
• Необходимые пакеты Python: numpy, pandas, matplotlib, seaborn, Jupyter и другие
• Дистрибутив Anaconda, его преимущества и недостатки
• Установка пакетов в Linux
• Установка пакетов в Windows. Возможные проблемы и методы их решения
• Методы и функции
• Основные команды и методы работы в Jupyter notebook
2. Библиотека numpy. Вычислительные задачи. (6 ак.ч.)
• Структура библиотеки
• Типы данных библиотеки numpy
• Векторы и массивы, специальные типы данных
• Понятие массива и его основные характеристики
• Принципы вычислений
• Универсальные функции
• Важнейшие стандартные функции
• Работа с массивами и матрицами
3. Библиотека pandas и анализ данных (6 ак.ч.)
• Объект Series
• Объект DataFrame
• Загрузка данных
• Выгрузка данных
• Чтение и запись данных в формате Excel
• Чтение и запись JSON-файлов
• Загрузка данных из интернета и из базы данных SQL
• Загрузка CSV-файлов из Интернета
• Основы работы с датафреймами
• Организация колонок и строчек
• Создание срезов объекта Series
• Выравнивание данных по меткам индекса
• Выполнение логического отбора
• Переиндексация объекта Series
4. Первичная обработка данных. (8 ак.ч.)
• Сбор данных
• Очистка данных
• Подготовка данных
• Объединение данных
• Сцепление и наложение
• Слияние данных
• Замена значений
• Работа с пропущенными значениями и их заполнение
• Повторы в данных
• Объединение и переформирование данных
5. Статистика и анализ (8 ак.ч.)
• Фильтрация
• Группировка
• Агрегация
• Описательные статистики
• Получение итоговых описательных статистик
• Измерение центральной тенденции: среднее, медиана и мода
• Вычисление дисперсии и стандартного отклонения
• Вычисление ковариации и корреляции
• Распределения
• Разведывательный анализ
• Постановка гипотезы
6. Библиотека matplotlib. Визуализация данных. (4 ак.ч.)
• Основные элементы диаграммы
• Создание диаграммы
• Виды графиков и диаграмм
• Оформление и кастомизация графиков
• Форматы изображений
7. Библиотека seaborn. Наглядная визуализация сложных данных. (4 ак.ч.)
• Виды графиков, их корректное использование и интерпретация
• Принципы хорошей визуализации, основные ошибки при визуализации данных
• График функции
• Гистограмма
• Визуализации отфильтрованных и сгруппированных данных