14.6 Moving Averages (Python)

GDP File data:

Year	GDP
1980	2788.1
1981	3126.8
1982	3253.2
1983	3534.6
1984	3930.9
1985	4217.5
1986	4460.1
1987	4736.4
1988	5100.4
1989	5482.1
1990	5800.5
1991	5992.1
1992	6342.3
1993	6667.4
1994	7085.2
1995	7414.7
1996	7838.5
1997	8332.4
1998	8793.5
1999	9353.5
2000	9951.5
2001	10286.2
2002	10642.3
2003	11142.2
2004	11853.3
2005	12623
2006	13377.2
2007	14028.7
2008	14291.5
2009	13973.7
2010	14498.9
2011	15075.7
2012	15684.8
2013	16768
2014	17419

The GDP file contains GDP for an unspecified country from 1980 to 2014. Use the pandas rolling() method to forecast GDP with moving averages for the specified time period taken as input. Add the moving average forecast to the data frame in a new column called mov_avgtime period. Print off the head of the data frame. Then calculate the mean absolute error and the mean squared error for the actual GDP and the forecasted GDP for 2014 If the input is 2 Then the output should be: Year GDP mov_avg2 0 1980 2788.1 NaN 1 1981 3126.8 2957.45 2 1982 3253.2 3190.00 3 1983 3534.6 3393.90 4 1984 3930.9 3732.75 The mean absolute error for 2014 is 325.5 The mean squared error for 2014 is 105950.25 LAB ACTIVITY 14.6.1: Moving Averages 0/2 Downloadable files GDP.csv Download Load default template. 4 main.py 1 # Load necessary modules 2 import pandas as pd 3 from sklearn.metrics import mean_absolute_error, mean_squared_error 5 # Import dataset using pandas 6 GDP = pd.read_csv('GDP.CSW') 7 print(GDP) 9 # Get input 10 window int(input) 12 # calculate moving average and store it as a new column in existing data frame 8 11 13 14 15 #print data frame head 16 print(GDP.head() 17 | 18 # create variables for actual and forecasted values of GDP for 2014 19 #gdp_2014 = #store the actual GDP for 2014 here 22 #gdp_forecast_2014 = # Store the forecasted value of GDP for 2014 here 22 23 # calculate the mean absolute error of the the actual GDP and forecasted GDP for 2014 24 #mae_2014 = #calculate mean absolute error here 25 #print("The mean absolute error for 2014 is', mae_2014) 26 27 # calculate the mean squared error of the the actual GDP and forecasted GDP for 2014 28 #mse_2014 = #calculate mean squared error here 29 #print('The mean squared error for 2014 is',mse_2014)