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--- a/verina_daria_lab_3/README.md
+++ b/verina_daria_lab_3/README.md
@ -1,41 +0,0 @@
 # Лабораторная работа 3. Деревья решений
 ### Задание на лабораторную:
 Часть 1. По данным о пассажирах Титаника решите задачу классификации (с  помощью  дерева  решений),  в  которой  по  различным  характеристикам пассажиров требуется найти у выживших пассажиров два наиболее важных признака  из  трех  рассматриваемых  (по  варианту).
 **Вариант 7.**
 Ticket,Fare,Cabin
 Часть 2. Решите с помощью библиотечной реализации дерева решений задачу из лабораторной работы «Веб-сервис «Дерево решений» по предмету «Методы  искусственного  интеллекта» на  99%  ваших  данных.  Проверьте работу модели на оставшемся проценте, сделайте вывод.
 ***
 ### Как запустить лабораторную работу:
 Для запуска первой части лабораторной работы необходимо открыть файл `laba3_titanic.py`, нажать на ПКМ и в выпадающем списке выбрать опцию "Run". Для запуска второй части - то же самое, но файл "laba3_economica"
 ***
 ### Технологии:
 **NumPy (Numerical Python)** - это библиотека для научных вычислений в Python, которая обеспечивает эффективные вычисления и манипуляции с данными.
 **Pandas** - это библиотека на языке Python, которая предоставляет удобные и эффективные инструменты для обработки и анализа данных. Она предоставляет высокоуровневые структуры данных, такие как DataFrame, которые позволяют легко и гибко работать с табличными данными.
 **Scikit-learn (Sklearn)** - это библиотека для языка программирования Python, которая предоставляет инструменты для разработки и применения различных алгоритмов машинного обучения, включая классификацию, регрессию, кластеризацию, снижение размерности и многое другое. Scikit-learn также предлагает функции для предобработки данных, оценки моделей и выбора наилучших параметров.
 ***
 ### Что делает лабораторная работа:
 Часть 1: 
 - Загружается выборка из файла titanic_data.csv с помощью пакета
 Pandas
 - Отбирается в выборку 3 признака: Ticket,Fare,Cabin
 - Определяется целевая переменная (Survived)
 - Обучается решающее дерево 
 - Выводятся важности признаков
 Часть 2:
 Код использует дерево решений для прогнозирования цены на нефть на основе страны и года. Данные разделены на тренировочный (99%) и тестовый (1%) наборы. Модель обучается на тренировочных данных и оценивается на тестовых данных. Затем модель применяется к оставшимся 1% данных для дополнительной оценки. Результаты выражены в процентах ошибки относительно среднего значения цены на нефть.
 ***
 ### Пример выходных данных:
 ***Часть 1:*** 
 ![result1.png](result1.png)
 ***Часть 2:***
 ![result2.png](result2.png)
 ***
 **Вывод**: результаты первой части лабораторной работы показали, что у выживших пассажиров наиболее важными признаками являются *Fare* и Ticket.
 Во второй части лаб. работы ошибка составила 3.1554436208840472e-30 (очень близка к нулю), это означает, что модель идеально соответствует тестовым данным. Она абсолютно точно предсказывает цены на нефть на тестовом наборе. 
--- a/verina_daria_lab_3/economica.csv
+++ b/verina_daria_lab_3/economica.csv
@ -1,370 +0,0 @@
 stock_index,country,year,index_price,log_indexprice,inflationrate,oil_prices,exchange_rate,gdppercent,percapitaincome,unemploymentrate,manufacturingoutput,tradebalance,USTreasury
 NASDAQ,United States of America,1980.00,168.61,2.23,0.14,21.59,1.00,0.09,12575.00,0.07,,-13.06,0.11
 NASDAQ,United States of America,1981.00,203.15,2.31,0.10,31.77,1.00,0.12,13976.00,0.08,,-12.52,0.14
 NASDAQ,United States of America,1982.00,188.98,2.28,0.06,28.52,1.00,0.04,14434.00,0.10,,-19.97,0.13
 NASDAQ,United States of America,1983.00,285.43,2.46,0.03,26.19,1.00,0.09,15544.00,0.10,,-51.64,0.11
 NASDAQ,United States of America,1984.00,248.89,2.40,0.04,25.88,1.00,0.11,17121.00,0.08,,-102.73,0.12
 NASDAQ,United States of America,1985.00,290.25,2.46,0.04,24.09,1.00,0.07,18237.00,0.07,,-114.02,0.11
 NASDAQ,United States of America,1986.00,366.97,2.56,0.02,12.51,1.00,0.06,19071.00,0.07,,-131.87,0.08
 NASDAQ,United States of America,1987.00,402.57,2.60,0.04,15.40,1.00,0.06,20039.00,0.06,,-144.77,0.08
 NASDAQ,United States of America,1988.00,374.43,2.57,0.04,12.58,1.00,0.08,21417.00,0.05,,-109.39,0.09
 NASDAQ,United States of America,1989.00,437.80,2.64,0.05,15.86,1.00,0.08,22857.00,0.05,,-86.74,0.08
 NASDAQ,United States of America,1990.00,409.18,2.61,0.05,27.28,1.00,0.02,23889.00,0.06,182.19,-77.85,0.09
 NASDAQ,United States of America,1991.00,491.69,2.69,0.04,19.50,1.00,,24342.00,0.07,185.83,-28.61,0.08
 NASDAQ,United States of America,1992.00,599.26,2.78,0.03,19.41,1.00,0.04,25419.00,0.07,189.27,-34.74,0.07
 NASDAQ,United States of America,1993.00,715.16,2.85,0.03,14.52,1.00,0.03,26387.00,0.07,166.43,-65.17,0.06
 NASDAQ,United States of America,1994.00,751.65,2.88,0.03,17.16,1.00,0.04,27695.00,0.06,187.05,-92.49,0.07
 NASDAQ,United States of America,1995.00,925.19,2.97,0.03,19.03,1.00,0.03,28691.00,0.06,208.44,-89.76,0.07
 NASDAQ,United States of America,1996.00,1164.95,3.07,0.03,25.23,1.00,0.04,29968.00,0.05,216.82,-96.38,0.06
 NASDAQ,United States of America,1997.00,1469.49,3.17,0.02,18.33,1.00,0.04,31459.00,0.05,235.67,-101.97,0.06
 NASDAQ,United States of America,1998.00,1794.91,3.25,0.02,11.35,1.00,0.05,32854.00,0.05,240.04,-162.71,0.05
 NASDAQ,United States of America,1999.00,2728.15,3.44,0.02,26.10,1.00,0.05,34514.00,0.04,234.62,-255.83,0.06
 NASDAQ,United States of America,2000.00,3783.67,3.58,0.03,28.44,1.00,0.04,36335.00,0.04,223.42,-375.05,0.06
 NASDAQ,United States of America,2001.00,2035.00,3.31,0.03,19.39,1.00,0.01,37133.00,0.05,205.70,-367.93,0.05
 NASDAQ,United States of America,2002.00,1539.73,3.19,0.02,29.46,1.00,0.02,38023.00,0.06,217.95,-425.40,0.05
 NASDAQ,United States of America,2003.00,1647.17,3.22,0.02,32.13,1.00,0.03,39496.00,0.06,240.22,-503.13,0.04
 NASDAQ,United States of America,2004.00,1986.53,3.30,0.03,43.15,1.00,0.04,41713.00,0.06,267.20,-619.08,0.04
 NASDAQ,United States of America,2005.00,2099.32,3.32,0.03,59.41,1.00,0.04,44115.00,0.05,268.36,-721.19,0.04
 NASDAQ,United States of America,2006.00,2263.41,3.35,0.03,61.96,1.00,0.03,46299.00,0.05,277.32,-770.93,0.05
 NASDAQ,United States of America,2007.00,2578.47,3.41,0.03,91.69,1.00,0.02,47976.00,0.05,299.29,-718.43,0.05
 NASDAQ,United States of America,2008.00,2161.65,3.33,0.04,41.12,1.00,,48383.00,0.06,278.83,-723.09,0.04
 NASDAQ,United States of America,2009.00,1845.38,3.27,,74.47,1.00,-0.03,47100.00,0.09,221.24,-396.45,0.03
 NASDAQ,United States of America,2010.00,2349.89,3.37,0.02,89.15,1.00,0.03,48467.00,0.10,236.41,-513.90,0.03
 NASDAQ,United States of America,2011.00,2677.44,3.43,0.03,98.56,1.00,0.02,49883.00,0.09,249.95,-579.46,0.03
 NASDAQ,United States of America,2012.00,2965.56,3.47,0.02,87.86,1.00,0.02,51603.00,0.08,252.36,-568.57,0.02
 NASDAQ,United States of America,2013.00,3541.29,3.55,0.01,97.63,1.00,0.02,53107.00,0.07,265.61,-490.78,0.02
 NASDAQ,United States of America,2014.00,4375.10,3.64,0.02,59.29,1.00,0.02,55050.00,0.06,287.86,-507.66,0.03
 NASDAQ,United States of America,2015.00,4945.55,3.69,,37.19,1.00,0.03,56863.00,0.05,274.30,-526.57,0.02
 NASDAQ,United States of America,2016.00,4987.79,3.70,0.01,51.97,1.00,0.02,58021.00,0.05,245.73,-512.51,0.02
 NASDAQ,United States of America,2017.00,6235.30,3.79,0.02,57.88,1.00,0.02,60110.00,0.04,242.59,-555.53,0.02
 NASDAQ,United States of America,2018.00,7425.96,3.87,0.02,49.52,1.00,0.03,63064.00,0.04,256.36,-609.46,0.03
 NASDAQ,United States of America,2019.00,7940.36,3.90,0.02,59.88,1.00,0.02,65280.00,0.04,245.75,-610.47,0.02
 NASDAQ,United States of America,2020.00,10201.51,4.01,0.01,47.02,1.00,-0.03,63544.00,0.08,227.14,,0.01
 FTSE 100,United Kingdom,1980.00,,3.33,0.18,21.59,2.32,-0.02,10032.00,0.05,,12.30,0.11
 FTSE 100,United Kingdom,1981.00,,3.33,0.12,31.77,2.02,-0.01,9599.00,0.04,,15.24,0.14
 FTSE 100,United Kingdom,1982.00,,3.33,0.09,28.52,1.75,0.02,9145.00,0.04,,9.77,0.13
 FTSE 100,United Kingdom,1983.00,,3.33,0.05,26.19,1.52,0.04,8691.00,0.04,,4.69,0.11
 FTSE 100,United Kingdom,1984.00,,3.33,0.05,25.88,1.34,0.02,8179.00,0.04,,-0.30,0.12
 FTSE 100,United Kingdom,1985.00,,3.33,0.06,24.09,1.30,0.04,8652.00,0.05,,5.39,0.11
 FTSE 100,United Kingdom,1986.00,,3.33,0.03,12.51,1.47,0.03,10611.00,0.04,,-3.63,0.08
 FTSE 100,United Kingdom,1987.00,,3.33,0.04,15.40,1.64,0.05,13118.00,0.05,,-7.00,0.08
 FTSE 100,United Kingdom,1988.00,,3.33,0.04,12.58,1.78,0.06,15988.00,0.05,,-29.79,0.09
 FTSE 100,United Kingdom,1989.00,,3.33,0.06,15.86,1.64,0.03,16240.00,0.05,,-33.87,0.08
 FTSE 100,United Kingdom,1990.00,2143.50,3.33,0.08,27.28,1.78,0.01,19096.00,0.07,182.19,-20.30,0.09
 FTSE 100,United Kingdom,1991.00,2493.10,3.40,0.07,19.50,1.77,-0.01,19900.00,0.09,185.83,-4.36,0.08
 FTSE 100,United Kingdom,1992.00,2846.50,3.45,0.05,19.41,1.77,,20488.00,0.10,189.27,-8.49,0.07
 FTSE 100,United Kingdom,1993.00,3418.40,3.53,0.03,14.52,1.50,0.02,18390.00,0.10,166.43,-3.90,0.06
 FTSE 100,United Kingdom,1994.00,3065.50,3.49,0.02,17.16,1.53,0.04,19708.00,0.10,187.05,-0.31,0.07
 FTSE 100,United Kingdom,1995.00,3689.30,3.57,0.03,19.03,1.58,0.03,23125.00,0.09,208.44,3.66,0.07
 FTSE 100,United Kingdom,1996.00,4118.50,3.61,0.03,25.23,1.56,0.02,24335.00,0.08,216.82,2.38,0.06
 FTSE 100,United Kingdom,1997.00,5135.50,3.71,0.02,18.33,1.64,0.05,26718.00,0.07,235.67,6.97,0.06
 FTSE 100,United Kingdom,1998.00,5882.58,3.77,0.02,11.35,1.66,0.04,28238.00,0.06,240.04,-11.17,0.05
 FTSE 100,United Kingdom,1999.00,6930.20,3.84,0.02,26.10,1.62,0.03,28668.00,0.06,234.62,-24.12,0.06
 FTSE 100,United Kingdom,2000.00,6222.46,3.79,0.01,28.44,1.52,0.04,28155.00,0.06,223.42,-29.59,0.06
 FTSE 100,United Kingdom,2001.00,5217.35,3.72,0.02,19.39,1.44,0.03,27719.00,0.05,205.70,-37.30,0.05
 FTSE 100,United Kingdom,2002.00,3940.36,3.60,0.02,29.46,1.50,0.02,29982.00,0.05,217.95,-47.84,0.05
 FTSE 100,United Kingdom,2003.00,4476.87,3.65,0.01,32.13,1.63,0.03,34385.00,0.05,240.22,-45.90,0.04
 FTSE 100,United Kingdom,2004.00,4814.30,3.68,0.01,43.15,1.83,0.02,40210.00,0.05,267.20,-61.87,0.04
 FTSE 100,United Kingdom,2005.00,5618.76,3.75,0.02,59.41,1.82,0.03,41933.00,0.05,268.36,-61.73,0.04
 FTSE 100,United Kingdom,2006.00,6220.81,3.79,0.02,61.96,1.84,0.03,44474.00,0.05,277.32,-57.48,0.05
 FTSE 100,United Kingdom,2007.00,6456.91,3.81,0.02,91.69,2.00,0.02,50448.00,0.05,299.29,-63.22,0.05
 FTSE 100,United Kingdom,2008.00,4434.17,3.65,0.04,41.12,1.85,,47270.00,0.06,278.83,-63.77,0.04
 FTSE 100,United Kingdom,2009.00,5412.88,3.73,0.02,74.47,1.57,-0.04,38736.00,0.08,221.24,-38.74,0.03
 FTSE 100,United Kingdom,2010.00,5899.94,3.77,0.02,89.15,1.55,0.02,39537.00,0.08,236.41,-48.09,0.03
 FTSE 100,United Kingdom,2011.00,5572.28,3.75,0.04,98.56,1.60,0.01,42048.00,0.08,249.95,-25.37,0.03
 FTSE 100,United Kingdom,2012.00,5897.81,3.77,0.03,87.86,1.59,0.01,42449.00,0.08,252.36,-33.47,0.02
 FTSE 100,United Kingdom,2013.00,6749.09,3.83,0.02,97.63,1.56,0.02,43401.00,0.08,265.61,-39.09,0.02
 FTSE 100,United Kingdom,2014.00,6566.09,3.82,0.01,59.29,1.65,0.03,47452.00,0.06,287.86,-47.61,0.03
 FTSE 100,United Kingdom,2015.00,6242.32,3.80,,37.19,1.53,0.02,45039.00,0.05,274.30,-43.19,0.02
 FTSE 100,United Kingdom,2016.00,7142.83,3.85,0.01,51.97,1.36,0.02,41048.00,0.05,245.73,-48.76,0.02
 FTSE 100,United Kingdom,2017.00,7687.77,3.89,0.03,57.88,1.29,0.02,40306.00,0.04,242.59,-38.47,0.02
 FTSE 100,United Kingdom,2018.00,6728.13,3.83,0.02,49.52,1.34,0.01,42996.00,0.04,256.36,-34.00,0.03
 FTSE 100,United Kingdom,2019.00,7542.44,3.88,0.02,59.88,1.28,0.01,42354.00,0.04,245.75,-35.06,0.02
 FTSE 100,United Kingdom,2020.00,6460.52,3.81,0.01,47.02,1.28,-0.10,40285.00,0.04,227.14,-9.69,0.01
 Nifty 50,India,1980.00,,3.02,0.11,21.59,7.89,0.07,267.00,0.03,31.21,-5.79,0.11
 Nifty 50,India,1981.00,,3.02,0.13,31.77,8.68,0.06,270.00,0.03,32.45,-5.10,0.14
 Nifty 50,India,1982.00,,3.02,0.08,28.52,9.48,0.03,274.00,0.03,32.86,-4.33,0.13
 Nifty 50,India,1983.00,,3.02,0.12,26.19,10.10,0.07,291.00,0.03,36.37,-4.40,0.11
 Nifty 50,India,1984.00,,3.02,0.08,25.88,11.35,0.04,277.00,0.03,35.45,-3.06,0.12
 Nifty 50,India,1985.00,,3.02,0.06,24.09,12.33,0.05,296.00,0.03,38.17,-5.56,0.11
 Nifty 50,India,1986.00,,3.02,0.09,12.51,12.60,0.05,310.00,0.03,40.39,-4.55,0.08
 Nifty 50,India,1987.00,,3.02,0.09,15.40,12.95,0.04,340.00,0.03,45.23,-3.84,0.08
 Nifty 50,India,1988.00,,3.02,0.09,12.58,13.90,0.10,354.00,0.03,47.76,-4.21,0.09
 Nifty 50,India,1989.00,,3.02,0.07,15.86,16.21,0.06,346.00,0.03,50.04,-3.36,0.08
 Nifty 50,India,1990.00,1048.29,3.02,0.09,27.28,17.49,0.06,368.00,0.06,53.27,-4.49,0.09
 Nifty 50,India,1991.00,1908.85,3.28,0.14,19.50,22.71,0.01,303.00,0.06,42.34,,0.08
 Nifty 50,India,1992.00,2615.37,3.42,0.12,19.41,28.16,0.05,317.00,0.06,45.54,-2.15,0.07
 Nifty 50,India,1993.00,3346.06,3.52,0.06,14.52,31.29,0.05,301.00,0.06,44.45,0.05,0.06
 Nifty 50,India,1994.00,3926.90,3.59,0.10,17.16,31.39,0.07,346.00,0.06,54.86,-0.99,0.07
 Nifty 50,India,1995.00,3110.49,3.49,0.10,19.03,32.42,0.08,374.00,0.06,64.37,-4.25,0.07
 Nifty 50,India,1996.00,3085.20,3.49,0.09,25.23,35.51,0.08,400.00,0.06,69.14,-4.55,0.06
 Nifty 50,India,1997.00,3658.98,3.56,0.07,18.33,36.36,0.04,415.00,0.06,68.70,-5.15,0.06
 Nifty 50,India,1998.00,3055.41,3.49,0.13,11.35,41.36,0.06,413.00,0.06,66.23,-7.01,0.05
 Nifty 50,India,1999.00,5005.82,3.70,0.05,26.10,43.13,0.09,442.00,0.06,69.65,-8.77,0.06
 Nifty 50,India,2000.00,3972.12,3.60,0.04,28.44,45.00,0.04,443.00,0.06,74.60,-4.25,0.06
 Nifty 50,India,2001.00,3262.33,3.51,0.04,19.39,47.22,0.05,452.00,0.06,74.31,-4.25,0.05
 Nifty 50,India,2002.00,3377.28,3.53,0.04,29.46,48.63,0.04,471.00,0.06,80.12,-5.05,0.05
 Nifty 50,India,2003.00,5838.96,3.77,0.04,32.13,46.59,0.08,547.00,0.06,94.72,-4.23,0.04
 Nifty 50,India,2004.00,6602.69,3.82,0.04,43.15,45.26,0.08,628.00,0.06,112.24,-12.66,0.04
 Nifty 50,India,2005.00,9397.93,3.97,0.04,59.41,44.00,0.08,715.00,0.06,131.04,-22.90,0.04
 Nifty 50,India,2006.00,13786.91,4.14,0.06,61.96,45.19,0.08,807.00,0.05,162.70,-29.98,0.05
 Nifty 50,India,2007.00,20286.99,4.31,0.06,91.69,41.18,0.08,1028.00,0.05,205.20,-49.73,0.05
 Nifty 50,India,2008.00,9647.31,3.98,0.08,41.12,43.39,0.03,999.00,0.06,205.00,-62.02,0.04
 Nifty 50,India,2009.00,17464.81,4.24,0.11,74.47,48.33,0.08,1102.00,0.06,230.05,-73.43,0.03
 Nifty 50,India,2010.00,20509.09,4.31,0.12,89.15,45.65,0.08,1358.00,0.06,285.36,-74.62,0.03
 Nifty 50,India,2011.00,15454.92,4.19,0.09,98.56,46.58,0.05,1458.00,0.06,294.23,-119.28,0.03
 Nifty 50,India,2012.00,19426.71,4.29,0.09,87.86,53.37,0.05,1444.00,0.06,289.08,-122.91,0.02
 Nifty 50,India,2013.00,21170.68,4.33,0.11,97.63,58.51,0.06,1450.00,0.06,283.21,-55.38,0.02
 Nifty 50,India,2014.00,27499.42,4.44,0.07,59.29,61.00,0.07,1574.00,0.06,307.21,-60.89,0.03
 Nifty 50,India,2015.00,26117.54,4.42,0.05,37.19,64.11,0.08,1606.00,0.06,327.82,-48.31,0.02
 Nifty 50,India,2016.00,26626.46,4.43,0.05,51.97,67.16,0.08,1733.00,0.05,347.94,-40.53,0.02
 Nifty 50,India,2017.00,34056.83,4.53,0.03,57.88,65.07,0.07,1981.00,0.05,398.20,-83.76,0.02
 Nifty 50,India,2018.00,36068.33,4.56,0.04,49.52,68.37,0.07,1997.00,0.05,401.20,-100.38,0.03
 Nifty 50,India,2019.00,41253.74,4.62,0.04,59.88,70.38,0.04,2101.00,0.07,382.56,-72.57,0.02
 Nifty 50,India,2020.00,47751.33,4.68,0.07,47.02,74.14,-0.08,1901.00,0.06,339.98,-8.31,0.01
 Nikkei 225,Japan,1980.00,6867.86,3.84,0.08,21.59,226.58,0.03,9463.00,0.02,71.01,-10.76,0.11
 Nikkei 225,Japan,1981.00,7518.55,3.88,0.05,31.77,220.45,0.04,10360.00,0.02,71.70,7.48,0.14
 Nikkei 225,Japan,1982.00,7397.27,3.87,0.03,28.52,249.05,0.03,9576.00,0.02,71.96,6.22,0.13
 Nikkei 225,Japan,1983.00,8816.24,3.95,0.02,26.19,237.45,0.04,10421.00,0.03,74.24,19.08,0.11
 Nikkei 225,Japan,1984.00,10567.53,4.02,0.02,25.88,237.59,0.05,10979.00,0.03,81.16,32.25,0.12
 Nikkei 225,Japan,1985.00,12557.45,4.10,0.02,24.09,238.47,0.05,11577.00,0.03,84.14,44.63,0.11
 Nikkei 225,Japan,1986.00,16392.74,4.21,0.01,12.51,168.50,0.03,17113.00,0.03,83.98,76.37,0.08
 Nikkei 225,Japan,1987.00,23232.14,4.37,,15.40,144.62,0.05,20749.00,0.03,86.87,70.12,0.08
 Nikkei 225,Japan,1988.00,27048.26,4.43,0.01,12.58,128.14,0.07,25059.00,0.03,94.91,60.32,0.09
 Nikkei 225,Japan,1989.00,34050.78,4.53,0.02,15.86,137.99,0.05,24823.00,0.02,100.40,41.28,0.08
 Nikkei 225,Japan,1990.00,29437.18,4.47,0.03,27.28,144.82,0.05,25371.00,0.02,104.65,24.33,0.09
 Nikkei 225,Japan,1991.00,24295.57,4.39,0.03,19.50,134.51,0.03,28915.00,0.02,106.64,53.70,0.08
 Nikkei 225,Japan,1992.00,18109.08,4.26,0.02,19.41,126.75,0.01,31415.00,0.02,100.55,80.30,0.07
 Nikkei 225,Japan,1993.00,19100.00,4.28,0.01,14.52,111.23,-0.01,35682.00,0.03,97.13,95.40,0.06
 Nikkei 225,Japan,1994.00,19935.83,4.30,0.01,17.16,102.20,0.01,39200.00,0.03,98.35,93.37,0.07
 Nikkei 225,Japan,1995.00,17329.70,4.24,,19.03,94.11,0.03,43429.00,0.03,101.34,68.88,0.07
 Nikkei 225,Japan,1996.00,21094.61,4.32,,25.23,108.80,0.03,38437.00,0.03,103.53,20.96,0.06
 Nikkei 225,Japan,1997.00,18397.52,4.26,0.02,18.33,121.09,0.01,35022.00,0.04,107.66,46.66,0.06
 Nikkei 225,Japan,1998.00,15355.99,4.19,0.01,11.35,130.82,-0.01,31903.00,0.04,100.48,73.27,0.05
 Nikkei 225,Japan,1999.00,16823.41,4.23,,26.10,113.71,,36027.00,0.05,101.07,70.92,0.06
 Nikkei 225,Japan,2000.00,17145.01,4.23,-0.01,28.44,107.82,0.03,38532.00,0.05,106.05,69.86,0.06
 Nikkei 225,Japan,2001.00,12093.56,4.08,-0.01,19.39,121.52,,33846.00,0.05,99.62,28.41,0.05
 Nikkei 225,Japan,2002.00,10123.14,4.01,-0.01,29.46,125.27,,32289.00,0.06,98.45,55.59,0.05
 Nikkei 225,Japan,2003.00,9311.42,3.97,,32.13,115.92,0.02,34808.00,0.05,102.29,75.37,0.04
 Nikkei 225,Japan,2004.00,11179.25,4.05,,43.15,108.16,0.02,37689.00,0.05,107.12,97.35,0.04
 Nikkei 225,Japan,2005.00,12422.58,4.09,,59.41,110.14,0.02,37218.00,0.05,108.86,71.78,0.04
 Nikkei 225,Japan,2006.00,16110.38,4.21,,61.96,116.35,0.01,35434.00,0.04,113.30,64.06,0.05
 Nikkei 225,Japan,2007.00,17002.24,4.23,,91.69,117.77,0.02,35275.00,0.04,116.60,85.46,0.05
 Nikkei 225,Japan,2008.00,12165.35,4.09,0.01,41.12,103.38,-0.01,39339.00,0.04,112.83,22.62,0.04
 Nikkei 225,Japan,2009.00,9346.11,3.97,-0.01,74.47,93.60,-0.05,40855.00,0.05,89.39,28.82,0.03
 Nikkei 225,Japan,2010.00,10006.49,4.00,-0.01,89.15,87.75,0.04,44508.00,0.05,102.78,83.25,0.03
 Nikkei 225,Japan,2011.00,9425.42,3.97,,98.56,79.71,,48168.00,0.05,99.93,-33.44,0.03
 Nikkei 225,Japan,2012.00,9102.56,3.96,,87.86,79.81,0.01,48603.00,0.05,100.06,-95.94,0.02
 Nikkei 225,Japan,2013.00,13577.87,4.13,,97.63,97.56,0.02,40454.00,0.04,99.46,-119.44,0.02
 Nikkei 225,Japan,2014.00,15460.43,4.19,0.03,59.29,105.86,,38109.00,0.04,101.24,-119.57,0.03
 Nikkei 225,Japan,2015.00,19203.77,4.28,0.01,37.19,121.02,0.01,34524.00,0.04,100.00,-18.39,0.02
 Nikkei 225,Japan,2016.00,16920.48,4.23,,51.97,108.76,0.01,38762.00,0.03,100.22,48.78,0.02
 Nikkei 225,Japan,2017.00,20209.03,4.31,,57.88,112.14,0.02,38387.00,0.03,102.84,45.27,0.02
 Nikkei 225,Japan,2018.00,22310.73,4.35,0.01,49.52,110.43,,39159.00,0.03,103.91,11.56,0.03
 Nikkei 225,Japan,2019.00,21697.23,4.34,,59.88,109.03,,40113.00,0.02,101.19,8.66,0.02
 Nikkei 225,Japan,2020.00,22705.02,4.36,,47.02,106.76,-0.05,,0.03,90.94,,0.01
 HSI,Hong Kong,1980.00,,3.46,,21.59,,0.10,5700.00,,,-0.15,0.11
 HSI,Hong Kong,1981.00,,3.46,,31.77,5.59,0.09,5991.00,,,-0.47,0.14
 HSI,Hong Kong,1982.00,,3.46,0.11,28.52,6.07,0.03,6134.00,,,0.18,0.13
 HSI,Hong Kong,1983.00,,3.46,0.10,26.19,7.26,0.06,5595.00,,,0.54,0.11
 HSI,Hong Kong,1984.00,,3.46,0.09,25.88,7.82,0.10,6208.00,,,2.68,0.12
 HSI,Hong Kong,1985.00,,3.46,0.04,24.09,7.79,0.01,6543.00,,,3.58,0.11
 HSI,Hong Kong,1986.00,,3.46,0.03,12.51,7.80,0.11,7435.00,,,3.74,0.08
 HSI,Hong Kong,1987.00,,3.46,0.06,15.40,7.80,0.13,9071.00,,,5.27,0.08
 HSI,Hong Kong,1988.00,2884.51,3.46,0.08,12.58,7.81,0.09,10610.00,,,5.33,0.09
 HSI,Hong Kong,1989.00,2556.72,3.41,0.10,15.86,7.80,0.02,12098.00,,,7.89,0.08
 HSI,Hong Kong,1990.00,2781.05,3.44,0.10,27.28,7.79,0.04,13486.00,,,6.57,0.09
 HSI,Hong Kong,1991.00,3027.13,3.48,0.11,19.50,7.77,0.06,15466.00,0.02,,6.05,0.08
 HSI,Hong Kong,1992.00,3829.37,3.58,0.10,19.41,7.74,0.06,17976.00,0.02,,5.42,0.07
 HSI,Hong Kong,1993.00,5545.98,3.74,0.09,14.52,7.74,0.06,20396.00,0.02,,8.12,0.06
 HSI,Hong Kong,1994.00,7695.99,3.89,0.09,17.16,7.73,0.06,22503.00,0.02,,1.57,0.07
 HSI,Hong Kong,1995.00,9453.52,3.98,0.09,19.03,7.74,0.02,23497.00,0.03,,-6.48,0.07
 HSI,Hong Kong,1996.00,9098.46,3.96,0.06,25.23,7.73,0.04,24818.00,0.03,,-2.37,0.06
 HSI,Hong Kong,1997.00,11646.54,4.07,0.06,18.33,7.74,0.05,27330.00,0.02,,-5.95,0.06
 HSI,Hong Kong,1998.00,13294.70,4.12,0.03,11.35,7.75,-0.06,25809.00,0.05,,0.91,0.05
 HSI,Hong Kong,1999.00,9484.47,3.98,-0.04,26.10,7.76,0.03,25092.00,0.06,,8.56,0.06
 HSI,Hong Kong,2000.00,12859.93,4.11,-0.04,28.44,7.79,0.08,25757.00,0.05,7.88,7.57,0.06
 HSI,Hong Kong,2001.00,15838.33,4.20,-0.02,19.39,7.80,0.01,25230.00,0.05,6.87,7.95,0.05
 HSI,Hong Kong,2002.00,12446.85,4.10,-0.03,29.46,7.80,0.02,24666.00,0.07,5.87,13.57,0.05
 HSI,Hong Kong,2003.00,10321.22,4.01,-0.03,32.13,7.79,0.03,23977.00,0.08,5.01,14.68,0.04
 HSI,Hong Kong,2004.00,10346.25,4.01,,43.15,7.79,0.09,24928.00,0.07,5.07,14.73,0.04
 HSI,Hong Kong,2005.00,12988.18,4.11,0.01,59.41,7.78,0.07,26650.00,0.06,5.10,22.18,0.04
 HSI,Hong Kong,2006.00,14402.00,4.16,0.02,61.96,7.77,0.07,28224.00,0.05,5.11,21.60,0.05
 HSI,Hong Kong,2007.00,17118.31,4.23,0.02,91.69,7.80,0.06,30594.00,0.04,4.15,22.59,0.05
 HSI,Hong Kong,2008.00,23700.45,4.37,0.04,41.12,7.79,0.02,31516.00,0.04,4.05,22.31,0.04
 HSI,Hong Kong,2009.00,20606.72,4.31,0.01,74.47,7.75,-0.02,30697.00,0.05,3.70,16.85,0.03
 HSI,Hong Kong,2010.00,18203.01,4.26,0.02,89.15,7.77,0.07,32550.00,0.04,3.91,13.43,0.03
 HSI,Hong Kong,2011.00,21336.42,4.33,0.05,98.56,7.78,0.05,35142.00,0.03,3.93,9.57,0.03
 HSI,Hong Kong,2012.00,21414.34,4.33,0.04,87.86,7.76,0.02,36731.00,0.03,3.95,2.97,0.02
 HSI,Hong Kong,2013.00,20686.69,4.32,0.04,97.63,7.76,0.03,38404.00,0.03,3.89,1.65,0.02
 HSI,Hong Kong,2014.00,22654.24,4.36,0.04,59.29,7.75,0.03,40315.00,0.03,3.60,0.60,0.03
 HSI,Hong Kong,2015.00,23287.69,4.37,0.03,37.19,7.75,0.02,42432.00,0.03,3.45,7.39,0.02
 HSI,Hong Kong,2016.00,24145.21,4.38,0.02,51.97,7.76,0.02,43731.00,0.03,3.46,7.33,0.02
 HSI,Hong Kong,2017.00,21511.54,4.33,0.01,57.88,7.79,0.04,46166.00,0.03,3.50,3.44,0.02
 HSI,Hong Kong,2018.00,26453.67,4.42,0.02,49.52,7.84,0.03,48543.00,0.03,3.52,-0.77,0.03
 HSI,Hong Kong,2019.00,28804.14,4.46,0.03,59.88,7.84,-0.02,48354.00,0.03,3.75,5.64,0.02
 HSI,Hong Kong,2020.00,27650.63,4.44,,47.02,7.76,-0.06,46324.00,0.06,,6.32,0.01
 SZCOMP,China,1980.00,,3.07,,21.59,,0.08,195.00,0.05,,-1.15,0.11
 SZCOMP,China,1981.00,,3.07,,31.77,1.71,0.05,197.00,0.05,,,0.14
 SZCOMP,China,1982.00,,3.07,,28.52,1.90,0.09,203.00,0.05,,4.81,0.13
 SZCOMP,China,1983.00,,3.07,,26.19,1.98,0.11,225.00,0.04,,2.57,0.11
 SZCOMP,China,1984.00,,3.07,,25.88,2.33,0.15,251.00,0.03,,0.05,0.12
 SZCOMP,China,1985.00,,3.07,,24.09,2.94,0.13,294.00,0.02,,-12.50,0.11
 SZCOMP,China,1986.00,,3.07,,12.51,3.46,0.09,282.00,0.02,,-7.39,0.08
 SZCOMP,China,1987.00,,3.07,0.07,15.40,3.73,0.12,252.00,0.02,,0.29,0.08
 SZCOMP,China,1988.00,,3.07,0.19,12.58,3.73,0.11,284.00,0.02,,-4.06,0.09
 SZCOMP,China,1989.00,,3.07,0.18,15.86,3.77,0.04,311.00,0.02,,-4.93,0.08
 SZCOMP,China,1990.00,,3.07,0.03,27.28,4.79,0.04,318.00,0.02,,10.67,0.09
 SZCOMP,China,1991.00,,3.07,0.04,19.50,5.33,0.09,333.00,0.03,,11.60,0.08
 SZCOMP,China,1992.00,,3.07,0.06,19.41,5.52,0.14,366.00,0.03,,5.00,0.07
 SZCOMP,China,1993.00,,3.07,0.15,14.52,5.78,0.14,377.00,0.02,,-11.79,0.06
 SZCOMP,China,1994.00,,3.07,0.24,17.16,8.64,0.13,473.00,0.02,,7.36,0.07
 SZCOMP,China,1995.00,,3.07,0.17,19.03,8.37,0.11,610.00,0.03,,11.96,0.07
 SZCOMP,China,1996.00,,3.07,0.08,25.23,8.34,0.10,709.00,0.03,,17.55,0.06
 SZCOMP,China,1997.00,1166.51,3.07,0.03,18.33,8.32,0.09,782.00,0.03,,42.82,0.06
 SZCOMP,China,1998.00,1257.32,3.10,-0.01,11.35,8.30,0.08,829.00,0.03,,43.84,0.05
 SZCOMP,China,1999.00,1381.49,3.14,-0.01,26.10,8.28,0.08,873.00,0.03,,30.64,0.06
 SZCOMP,China,2000.00,1897.42,3.28,,28.44,8.28,0.08,959.00,0.03,,28.79,0.06
 SZCOMP,China,2001.00,1940.96,3.29,0.01,19.39,8.28,0.08,1053.00,0.03,,28.09,0.05
 SZCOMP,China,2002.00,1561.31,3.19,-0.01,29.46,8.28,0.09,1149.00,0.03,,37.38,0.05
 SZCOMP,China,2003.00,1467.88,3.17,0.01,32.13,8.28,0.10,1289.00,0.04,,35.82,0.04
 SZCOMP,China,2004.00,1467.57,3.17,0.04,43.15,8.28,0.10,1509.00,0.04,625.22,51.17,0.04
 SZCOMP,China,2005.00,1144.54,3.06,0.02,59.41,8.19,0.11,1753.00,0.04,733.66,124.63,0.04
 SZCOMP,China,2006.00,1687.14,3.23,0.02,61.96,7.97,0.13,2099.00,0.04,893.13,208.92,0.05
 SZCOMP,China,2007.00,4329.44,3.64,0.05,91.69,7.61,0.14,2694.00,0.04,1149.72,308.04,0.05
 SZCOMP,China,2008.00,2912.90,3.46,0.06,41.12,6.95,0.10,3468.00,0.04,1475.66,348.83,0.04
 SZCOMP,China,2009.00,2737.01,3.44,-0.01,74.47,6.83,0.09,3832.00,0.04,1611.95,220.13,0.03
 SZCOMP,China,2010.00,2795.88,3.45,0.03,89.15,6.77,0.11,4550.00,0.04,1924.32,222.40,0.03
 SZCOMP,China,2011.00,2639.19,3.42,0.06,98.56,6.46,0.10,5618.00,0.04,2421.37,180.89,0.03
 SZCOMP,China,2012.00,2211.11,3.34,0.03,87.86,6.31,0.08,6317.00,0.04,2690.09,231.87,0.02
 SZCOMP,China,2013.00,2182.52,3.34,0.03,97.63,6.15,0.08,7051.00,0.05,2935.34,234.87,0.02
 SZCOMP,China,2014.00,2279.75,3.36,0.02,59.29,6.16,0.07,7679.00,0.05,3184.24,221.55,0.03
 SZCOMP,China,2015.00,3657.40,3.56,0.01,37.19,6.28,0.07,8067.00,0.05,3202.50,358.84,0.02
 SZCOMP,China,2016.00,2978.14,3.47,0.02,51.97,6.64,0.07,8148.00,0.05,3153.12,255.48,0.02
 SZCOMP,China,2017.00,3257.35,3.51,0.02,57.88,6.76,0.07,8879.00,0.04,3460.33,215.70,0.02
 SZCOMP,China,2018.00,2920.18,3.47,0.02,49.52,6.61,0.07,9977.00,0.04,3868.46,106.71,0.03
 SZCOMP,China,2019.00,2928.94,3.47,0.03,59.88,6.91,0.06,10217.00,0.05,3823.41,164.99,0.02
 SZCOMP,China,2020.00,3109.78,3.49,0.02,47.02,6.90,0.02,10500.00,0.05,3853.81,366.14,0.01
 DAX 30,Germany,1980.00,480.90,2.68,0.05,21.59,1.82,0.01,6206.00,0.03,,-22.41,0.11
 DAX 30,Germany,1981.00,490.40,2.69,0.06,31.77,2.26,0.01,5220.00,0.05,,-16.02,0.14
 DAX 30,Germany,1982.00,552.80,2.74,0.05,28.52,2.43,,5069.00,0.07,,-10.51,0.13
 DAX 30,Germany,1983.00,774.00,2.89,0.03,26.19,2.55,0.02,5044.00,0.08,,-11.79,0.11
 DAX 30,Germany,1984.00,820.90,2.91,0.02,25.88,2.85,0.03,4762.00,0.08,,-10.35,0.12
 DAX 30,Germany,1985.00,1366.20,3.14,0.02,24.09,2.94,0.02,4821.00,0.08,,-7.63,0.11
 DAX 30,Germany,1986.00,1432.30,3.16,,12.51,2.17,0.02,6883.00,0.08,,-1.98,0.08
 DAX 30,Germany,1987.00,1000.00,3.00,,15.40,1.80,0.01,8527.00,0.08,,-2.15,0.08
 DAX 30,Germany,1988.00,1327.87,3.12,0.01,12.58,1.76,0.04,9168.00,0.08,,-2.48,0.09
 DAX 30,Germany,1989.00,1790.37,3.25,0.03,15.86,1.88,0.04,9083.00,0.07,,-4.41,0.08
 DAX 30,Germany,1990.00,1398.20,3.15,0.03,27.28,1.62,0.05,11404.00,0.06,,-1.74,0.09
 DAX 30,Germany,1991.00,1578.00,3.20,0.04,19.50,1.66,0.05,11942.00,0.06,237.43,-4.66,0.08
 DAX 30,Germany,1992.00,1545.10,3.19,0.05,19.41,1.56,0.02,13518.00,0.08,254.79,-5.47,0.07
 DAX 30,Germany,1993.00,2266.70,3.36,0.04,14.52,1.65,-0.01,13049.00,0.09,225.80,0.53,0.06
 DAX 30,Germany,1994.00,2106.60,3.32,0.03,17.16,1.62,0.02,13844.00,0.10,234.55,1.84,0.07
 DAX 30,Germany,1995.00,2253.90,3.35,0.02,19.03,1.43,0.02,16186.00,0.09,271.52,5.38,0.07
 DAX 30,Germany,1996.00,2888.70,3.46,0.01,25.23,1.50,0.01,15588.00,0.10,256.13,9.12,0.06
 DAX 30,Germany,1997.00,4224.30,3.63,0.02,18.33,1.73,0.02,13786.00,0.11,228.78,12.19,0.06
 DAX 30,Germany,1998.00,5002.39,3.70,0.01,11.35,1.76,0.02,13953.00,0.11,233.65,14.07,0.05
 DAX 30,Germany,1999.00,6958.14,3.84,0.01,26.10,1.07,0.02,26735.00,0.11,438.87,12.13,0.06
 DAX 30,Germany,2000.00,6433.61,3.81,0.01,28.44,0.92,0.03,23695.00,0.10,400.23,3.30,0.06
 DAX 30,Germany,2001.00,5160.10,3.71,0.02,19.39,0.90,0.02,23628.00,0.09,395.80,31.65,0.05
 DAX 30,Germany,2002.00,2892.63,3.46,0.01,29.46,0.95,,25197.00,0.10,411.33,88.34,0.05
 DAX 30,Germany,2003.00,3965.16,3.60,0.01,32.13,1.13,-0.01,30310.00,0.11,496.31,94.41,0.04
 DAX 30,Germany,2004.00,4256.08,3.63,0.02,43.15,1.24,0.01,34107.00,0.11,563.82,146.36,0.04
 DAX 30,Germany,2005.00,5408.25,3.73,0.02,59.41,1.24,0.01,34520.00,0.12,571.36,148.05,0.04
 DAX 30,Germany,2006.00,6596.91,3.82,0.02,61.96,1.26,0.04,36354.00,0.11,618.70,162.20,0.05
 DAX 30,Germany,2007.00,8067.31,3.91,0.02,91.69,1.37,0.03,41640.00,0.09,714.38,231.95,0.05
 DAX 30,Germany,2008.00,4810.20,3.68,0.03,41.12,1.47,0.01,45613.00,0.08,750.91,227.47,0.04
 DAX 30,Germany,2009.00,5957.43,3.78,,74.47,1.39,-0.06,41650.00,0.08,603.23,170.94,0.03
 DAX 30,Germany,2010.00,6914.19,3.84,0.01,89.15,1.33,0.04,41572.00,0.08,669.57,178.90,0.03
 DAX 30,Germany,2011.00,5898.35,3.77,0.02,98.56,1.39,0.04,46706.00,0.07,758.60,184.02,0.03
 DAX 30,Germany,2012.00,7612.39,3.88,0.02,87.86,1.29,,43856.00,0.07,710.95,215.16,0.02
 DAX 30,Germany,2013.00,9552.16,3.98,0.02,97.63,1.33,,46299.00,0.07,743.97,215.01,0.02
 DAX 30,Germany,2014.00,9805.55,3.99,0.01,59.29,1.33,0.02,48024.00,0.07,786.55,257.40,0.03
 DAX 30,Germany,2015.00,10743.01,4.03,0.01,37.19,1.11,0.01,41103.00,0.06,683.20,255.02,0.02
 DAX 30,Germany,2016.00,11481.06,4.06,,51.97,1.11,0.02,42136.00,0.06,716.94,255.97,0.02
 DAX 30,Germany,2017.00,12917.64,4.11,0.02,57.88,1.13,0.03,44553.00,0.06,752.02,257.66,0.02
 DAX 30,Germany,2018.00,10558.96,4.02,0.02,49.52,1.18,0.01,47811.00,0.05,795.96,243.72,0.03
 DAX 30,Germany,2019.00,13249.01,4.12,0.01,59.88,1.12,0.01,46468.00,0.05,737.94,223.82,0.02
 DAX 30,Germany,2020.00,13718.78,4.14,0.01,47.02,1.14,-0.05,45724.00,0.06,678.29,221.53,0.01
 CAC 40,France,1980.00,394.44,2.60,0.14,21.59,4.23,0.02,1938.00,,19.77,-1.64,0.11
 CAC 40,France,1981.00,325.88,2.51,0.13,31.77,5.43,0.01,1693.00,,16.94,-1.38,0.14
 CAC 40,France,1982.00,353.24,2.55,0.12,28.52,6.58,0.03,1600.00,,15.58,-2.19,0.13
 CAC 40,France,1983.00,552.60,2.74,0.09,26.19,7.62,0.01,1524.00,0.09,14.93,-0.23,0.11
 CAC 40,France,1984.00,643.20,2.81,0.08,25.88,8.74,0.02,1436.00,0.10,13.97,0.10,0.12
 CAC 40,France,1985.00,930.21,2.97,0.06,24.09,8.99,0.02,1488.00,0.10,14.60,-0.31,0.11
 CAC 40,France,1986.00,1403.64,3.15,0.03,12.51,6.93,0.02,2064.00,0.11,19.92,-0.14,0.08
 CAC 40,France,1987.00,1000.00,3.00,0.03,15.40,6.01,0.03,2485.00,0.11,23.51,-1.56,0.08
 CAC 40,France,1988.00,1573.94,3.20,0.03,12.58,5.96,0.05,2695.00,0.10,25.43,-1.02,0.09
 CAC 40,France,1989.00,2001.08,3.30,0.03,15.86,6.38,0.04,2697.00,0.10,25.28,-1.07,0.08
 CAC 40,France,1990.00,1509.00,3.18,0.03,27.28,5.44,0.03,3322.00,0.09,31.36,-1.52,0.09
 CAC 40,France,1991.00,1765.70,3.25,0.03,19.50,5.64,0.01,3304.00,0.10,30.80,-0.61,0.08
 CAC 40,France,1992.00,1857.80,3.27,0.02,19.41,5.30,0.02,3630.00,0.11,33.31,1.43,0.07
 CAC 40,France,1993.00,2268.20,3.36,0.02,14.52,5.66,-0.01,3412.00,0.12,30.38,3.39,0.06
 CAC 40,France,1994.00,1881.20,3.27,0.02,17.16,5.55,0.02,3582.00,0.12,31.23,3.18,0.07
 CAC 40,France,1995.00,1872.00,3.27,0.02,19.03,4.99,0.02,4099.00,0.12,36.32,3.90,0.07
 CAC 40,France,1996.00,2315.70,3.36,0.02,25.23,5.12,0.01,4097.00,0.12,35.44,4.36,0.06
 CAC 40,France,1997.00,2998.90,3.48,0.01,18.33,5.84,0.02,3694.00,0.12,32.50,6.67,0.06
 CAC 40,France,1998.00,3942.66,3.60,0.01,11.35,5.90,0.04,3807.00,0.12,33.61,6.29,0.05
 CAC 40,France,1999.00,5958.32,3.78,0.01,26.10,1.07,0.03,24682.00,0.11,215.66,35.72,0.06
 CAC 40,France,2000.00,5926.42,3.77,0.02,28.44,0.92,0.04,22420.00,0.10,197.71,18.15,0.06
 CAC 40,France,2001.00,4624.58,3.67,0.02,19.39,0.90,0.02,22453.00,0.09,193.29,21.66,0.05
 CAC 40,France,2002.00,3063.91,3.49,0.02,29.46,0.95,0.01,24293.00,0.09,203.97,29.88,0.05
 CAC 40,France,2003.00,3557.90,3.55,0.02,32.13,1.13,0.01,29634.00,0.09,241.52,26.31,0.04
 CAC 40,France,2004.00,3821.16,3.58,0.02,43.15,1.24,0.03,33803.00,0.09,268.87,21.46,0.04
 CAC 40,France,2005.00,4715.23,3.67,0.02,59.41,1.24,0.02,34773.00,0.09,269.11,1.88,0.04
 CAC 40,France,2006.00,5541.75,3.74,0.02,61.96,1.26,0.02,36474.00,0.09,272.13,-5.41,0.05
 CAC 40,France,2007.00,5614.08,3.75,0.01,91.69,1.37,0.02,41561.00,0.08,309.42,-19.00,0.05
 CAC 40,France,2008.00,3217.97,3.51,0.03,41.12,1.47,,45519.00,0.07,325.40,-33.94,0.04
 CAC 40,France,2009.00,3936.33,3.60,,74.47,1.39,-0.03,41740.00,0.09,286.02,-21.37,0.03
 CAC 40,France,2010.00,3804.78,3.58,0.02,89.15,1.33,0.02,40678.00,0.09,273.17,-34.15,0.03
 CAC 40,France,2011.00,3159.81,3.50,0.02,98.56,1.39,0.02,43848.00,0.09,297.86,-55.81,0.03
 CAC 40,France,2012.00,3641.07,3.56,0.02,87.86,1.29,,40872.00,0.10,278.07,-34.78,0.02
 CAC 40,France,2013.00,4295.95,3.63,0.01,97.63,1.33,0.01,42605.00,0.10,291.15,-29.09,0.02
 CAC 40,France,2014.00,4272.75,3.63,0.01,59.29,1.33,0.01,43069.00,0.10,293.61,-32.71,0.03
 CAC 40,France,2015.00,4637.06,3.67,,37.19,1.11,0.01,36653.00,0.10,254.50,-13.82,0.02
 CAC 40,France,2016.00,4862.31,3.69,,51.97,1.11,0.01,37063.00,0.10,254.30,-14.96,0.02
 CAC 40,France,2017.00,5312.56,3.73,0.01,57.88,1.13,0.02,38781.00,0.09,263.05,-27.63,0.02
 CAC 40,France,2018.00,4730.69,3.67,0.02,49.52,1.18,0.02,41547.00,0.09,275.76,-29.02,0.03
 CAC 40,France,2019.00,5978.06,3.78,0.01,59.88,1.12,0.02,40380.00,0.08,266.63,-26.59,0.02
 CAC 40,France,2020.00,5551.41,3.74,,47.02,1.14,-0.08,38625.00,0.08,241.71,-57.65,0.01
 IEX 35,Spain,1980.00,,3.38,0.16,21.59,71.78,0.02,37.00,,,-0.04,0.11
 IEX 35,Spain,1981.00,,3.38,0.15,31.77,92.33,,32.00,,,-0.03,0.14
 IEX 35,Spain,1982.00,,3.38,0.14,28.52,109.92,0.01,31.00,,,-0.03,0.13
 IEX 35,Spain,1983.00,,3.38,0.12,26.19,143.54,0.02,27.00,,,-0.02,0.11
 IEX 35,Spain,1984.00,,3.38,0.11,25.88,160.91,0.02,27.00,,,0.01,0.12
 IEX 35,Spain,1985.00,,3.38,0.09,24.09,170.20,0.02,28.00,,,0.01,0.11
 IEX 35,Spain,1986.00,,3.38,0.09,12.51,140.14,0.03,39.00,,,0.02,0.08
 IEX 35,Spain,1987.00,2407.10,3.38,0.05,15.40,123.51,0.06,50.00,0.20,,-0.02,0.08
 IEX 35,Spain,1988.00,2727.50,3.44,0.05,12.58,116.49,0.05,58.00,0.19,,-0.05,0.09
 IEX 35,Spain,1989.00,3000.00,3.48,0.07,15.86,118.34,0.05,64.00,0.17,,-0.10,0.08
 IEX 35,Spain,1990.00,2248.80,3.35,0.07,27.28,101.95,0.04,83.00,0.15,,-0.13,0.09
 IEX 35,Spain,1991.00,2603.30,3.42,0.06,19.50,103.87,0.03,89.00,0.16,,-0.14,0.08
 IEX 35,Spain,1992.00,2344.57,3.37,0.06,19.41,102.47,0.01,97.00,0.17,,-0.14,0.07
 IEX 35,Spain,1993.00,3615.22,3.56,0.05,14.52,127.31,-0.01,80.00,0.21,,-0.05,0.06
 IEX 35,Spain,1994.00,3087.68,3.49,0.05,17.16,133.89,0.02,81.00,0.22,,-0.03,0.07
 IEX 35,Spain,1995.00,3630.76,3.56,0.05,19.03,124.68,0.03,93.00,0.21,0.60,-0.04,0.07
 IEX 35,Spain,1996.00,5154.77,3.71,0.04,25.23,126.68,0.03,97.00,0.20,0.63,-0.01,0.06
 IEX 35,Spain,1997.00,7255.40,3.86,0.02,18.33,146.45,0.04,89.00,0.18,0.59,0.01,0.06
 IEX 35,Spain,1998.00,9836.60,3.99,0.02,11.35,149.37,0.04,93.00,0.16,0.62,-0.02,0.05
 IEX 35,Spain,1999.00,11641.40,4.07,0.02,26.10,1.07,0.04,15721.00,0.14,103.49,-12.28,0.06
 IEX 35,Spain,2000.00,9109.80,3.96,0.03,28.44,0.92,0.05,14750.00,0.12,97.13,-17.69,0.06
 IEX 35,Spain,2001.00,8397.60,3.92,0.04,19.39,0.90,0.04,15369.00,0.11,99.40,-14.28,0.05
 IEX 35,Spain,2002.00,6036.90,3.78,0.03,29.46,0.95,0.03,17107.00,0.11,108.02,-14.11,0.05
 IEX 35,Spain,2003.00,7737.20,3.89,0.03,32.13,1.13,0.03,21511.00,0.11,133.45,-20.02,0.04
 IEX 35,Spain,2004.00,9080.80,3.96,0.03,43.15,1.24,0.03,24907.00,0.11,151.49,-39.56,0.04
 IEX 35,Spain,2005.00,10733.90,4.03,0.03,59.41,1.24,0.04,26429.00,0.09,158.16,-55.42,0.04
 IEX 35,Spain,2006.00,14146.50,4.15,0.04,61.96,1.26,0.04,28389.00,0.08,168.08,-71.77,0.05
 IEX 35,Spain,2007.00,15182.29,4.18,0.03,91.69,1.37,0.04,32591.00,0.08,190.13,-85.17,0.05
 IEX 35,Spain,2008.00,9195.80,3.96,0.04,41.12,1.47,0.01,35511.00,0.11,207.17,-77.28,0.04
 IEX 35,Spain,2009.00,11940.00,4.08,,74.47,1.39,-0.04,32170.00,0.18,172.86,-13.00,0.03
 IEX 35,Spain,2010.00,9859.10,3.99,0.02,89.15,1.33,,30532.00,0.20,162.09,-14.57,0.03
 IEX 35,Spain,2011.00,8566.30,3.93,0.03,98.56,1.39,-0.01,31678.00,0.21,170.26,4.10,0.03
 IEX 35,Spain,2012.00,8167.50,3.91,0.02,87.86,1.29,-0.03,28323.00,0.25,147.38,27.36,0.02
 IEX 35,Spain,2013.00,9916.70,4.00,0.01,97.63,1.33,-0.01,29068.00,0.26,151.68,53.24,0.02
 IEX 35,Spain,2014.00,10279.50,4.01,,59.29,1.33,0.01,29501.00,0.24,155.09,42.50,0.03
 IEX 35,Spain,2015.00,9544.20,3.98,-0.01,37.19,1.11,0.04,25742.00,0.22,135.11,36.35,0.02
 IEX 35,Spain,2016.00,9352.10,3.97,,51.97,1.11,0.03,26523.00,0.20,139.01,49.16,0.02
 IEX 35,Spain,2017.00,10043.90,4.00,0.02,57.88,1.13,0.03,28170.00,0.17,148.80,47.33,0.02
 IEX 35,Spain,2018.00,8539.90,3.93,0.02,49.52,1.18,0.02,30389.00,0.15,158.33,38.70,0.03
 IEX 35,Spain,2019.00,9549.20,3.98,0.01,59.88,1.12,0.02,29565.00,0.14,155.49,41.94,0.02
 IEX 35,Spain,2020.00,8073.70,3.91,,47.02,1.14,-0.11,27057.00,0.16,143.05,19.10,0.01
--- a/verina_daria_lab_3/laba3_economica.py
+++ b/verina_daria_lab_3/laba3_economica.py
@ -1,40 +0,0 @@
 import pandas as pd
 from sklearn.model_selection import train_test_split
 from sklearn.tree import DecisionTreeRegressor
 from sklearn.metrics import mean_squared_error
 from sklearn.preprocessing import LabelEncoder
 # Загрузка данных
 data = pd.read_csv('economica.csv')
 # Преобразование строковых значений в числовые
 le = LabelEncoder()
 data['country'] = le.fit_transform(data['country'])
 # Определение признаков и целевой переменной
 X = data[['country', 'year']]
 y = data['oil_prices']
 # Разделение данных на тренировочный и тестовый наборы
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.01, random_state=42)
 # Создание и обучение дерева решений
 clf = DecisionTreeRegressor(random_state=42)
 clf.fit(X_train, y_train)
 # Прогнозирование на тестовом наборе
 y_pred = clf.predict(X_test)
 # Оценка качества модели на тестовом наборе
 mse = mean_squared_error(y_test, y_pred)
 # Прогнозирование на оставшемся проценте данных
 X_remaining = data.drop(X_train.index)
 y_remaining_true = X_remaining['oil_prices']
 X_remaining = X_remaining[['country', 'year']]
 y_remaining_pred = clf.predict(X_remaining)
 # Оценка качества модели на оставшемся проценте данных
 mse_remaining = mean_squared_error(y_remaining_true, y_remaining_pred)
 mse_remaining_percent = (mse_remaining / y.mean()) * 100
 print(f'Среднеквадратичная ошибка на 1%: {mse_remaining}({mse_remaining_percent:.2f}%)')
--- a/verina_daria_lab_3/laba3_titanic.py
+++ b/verina_daria_lab_3/laba3_titanic.py
@ -1,31 +0,0 @@
 import pandas as pd
 from sklearn.tree import DecisionTreeClassifier
 # Загрузка данных
 data = pd.read_csv('titanic_data.csv', index_col='PassengerId')
 # Фильтрация данных
 data = data.dropna(subset=['Ticket', 'Fare', 'Cabin', 'Survived'])
 # Преобразование категориальных признаков в числовые
 data['Ticket'], _ = pd.factorize(data['Ticket'])
 data['Cabin'], _ = pd.factorize(data['Cabin'])
 # Выделение признаков и целевой переменной
 X = data[['Ticket', 'Fare', 'Cabin']]
 y = data['Survived']
 # Создание и обучение дерева решений
 clf = DecisionTreeClassifier(random_state=241)
 clf.fit(X, y)
 # Получение и распечатка важностей признаков
 importances = clf.feature_importances_
 # Связываем важности с именами признаков
 feature_importance = dict(zip(X.columns, importances))
 # Выводим важности признаков
 print("Важности признаков:")
 for feature, importance in feature_importance.items():
    print(f"{feature}: {importance}")
--- a/verina_daria_lab_3/result1.png
+++ b/verina_daria_lab_3/result1.png
--- a/verina_daria_lab_3/result2.png
+++ b/verina_daria_lab_3/result2.png
--- a/verina_daria_lab_3/titanic_data.csv
+++ b/verina_daria_lab_3/titanic_data.csv
@ -1,892 +0,0 @@
 PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked
 1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
 2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C
 3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,STON/O2. 3101282,7.925,,S
 4,1,1,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,1,0,113803,53.1,C123,S
 5,0,3,"Allen, Mr. William Henry",male,35,0,0,373450,8.05,,S
 6,0,3,"Moran, Mr. James",male,,0,0,330877,8.4583,,Q
 7,0,1,"McCarthy, Mr. Timothy J",male,54,0,0,17463,51.8625,E46,S
 8,0,3,"Palsson, Master. Gosta Leonard",male,2,3,1,349909,21.075,,S
 9,1,3,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,0,2,347742,11.1333,,S
 10,1,2,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,1,0,237736,30.0708,,C
 11,1,3,"Sandstrom, Miss. Marguerite Rut",female,4,1,1,PP 9549,16.7,G6,S
 12,1,1,"Bonnell, Miss. Elizabeth",female,58,0,0,113783,26.55,C103,S
 13,0,3,"Saundercock, Mr. William Henry",male,20,0,0,A/5. 2151,8.05,,S
 14,0,3,"Andersson, Mr. Anders Johan",male,39,1,5,347082,31.275,,S
 15,0,3,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,0,350406,7.8542,,S
 16,1,2,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,0,248706,16,,S
 17,0,3,"Rice, Master. Eugene",male,2,4,1,382652,29.125,,Q
 18,1,2,"Williams, Mr. Charles Eugene",male,,0,0,244373,13,,S
 19,0,3,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",female,31,1,0,345763,18,,S
 20,1,3,"Masselmani, Mrs. Fatima",female,,0,0,2649,7.225,,C
 21,0,2,"Fynney, Mr. Joseph J",male,35,0,0,239865,26,,S
 22,1,2,"Beesley, Mr. Lawrence",male,34,0,0,248698,13,D56,S
 23,1,3,"McGowan, Miss. Anna ""Annie""",female,15,0,0,330923,8.0292,,Q
 24,1,1,"Sloper, Mr. William Thompson",male,28,0,0,113788,35.5,A6,S
 25,0,3,"Palsson, Miss. Torborg Danira",female,8,3,1,349909,21.075,,S
 26,1,3,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,1,5,347077,31.3875,,S
 27,0,3,"Emir, Mr. Farred Chehab",male,,0,0,2631,7.225,,C
 28,0,1,"Fortune, Mr. Charles Alexander",male,19,3,2,19950,263,C23 C25 C27,S
 29,1,3,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,0,330959,7.8792,,Q
 30,0,3,"Todoroff, Mr. Lalio",male,,0,0,349216,7.8958,,S
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