R Notebook

Try to use the Quandl API. It is free. If you want to make more than 50 calls in a day you need to request an API key.

Here is the link to the webpage to learn about the Quandl R package.

The example on this page uses data from FRED about the GDP. Take a look at the FRED website and all of the data available. Also try out the visualization tools.

# install.packages("Quandl")
library(Quandl)
mydata <- Quandl("FRED/GDP")
mydata

plot(mydata)

mydata <- Quandl("FRED/GDP", start_date="2001-12-31", end_date="2005-12-31")
plot(mydata)

mydata <- Quandl("FRED/GDP", collapse="annual")
plot(mydata)

Note that there are different ways to download data from FRED. When downloading time series data it is best to download it in a time series R format, such as ts.

mydata <- Quandl("FRED/GDP", type="ts")
mydata

          Qtr1      Qtr2      Qtr3      Qtr4
1947   243.164   245.968   249.585   259.745
1948   265.742   272.567   279.196   280.366
1949   275.034   271.351   272.889   270.627
1950   280.828   290.383   308.153   319.945
1951   336.000   344.090   351.385   356.178
1952   359.820   361.030   367.701   380.812
1953   387.980   391.749   391.171   385.970
1954   385.345   386.121   390.996   399.734
1955   413.073   421.532   430.221   437.092
1956   439.746   446.010   451.191   460.463
1957   469.779   472.025   479.490   474.864
1958   467.540   471.978   485.841   499.555
1959   510.330   522.653   525.034   528.600
1960   542.648   541.080   545.604   540.197
1961   545.018   555.545   567.664   580.612
1962   594.013   600.366   609.027   612.280
1963   621.672   629.752   644.444   653.938
1964   669.822   678.674   692.031   697.319
1965   717.790   730.191   749.323   771.857
1966   795.734   804.981   819.638   833.302
1967   844.170   848.983   865.233   881.439
1968   909.387   934.344   950.825   968.030
1969   993.337  1009.020  1029.956  1038.147
1970  1051.200  1067.375  1086.059  1088.608
1971  1135.156  1156.271  1177.675  1190.297
1972  1230.609  1266.369  1290.566  1328.904
1973  1377.490  1413.887  1433.838  1476.289
1974  1491.209  1530.056  1560.026  1599.679
1975  1616.116  1651.853  1709.820  1761.831
1976  1820.487  1852.332  1886.558  1934.273
1977  1988.648  2055.909  2118.473  2164.270
1978  2202.760  2331.633  2395.053  2476.949
1979  2526.610  2591.247  2667.565  2723.883
1980  2789.842  2797.352  2856.483  2985.557
1981  3124.206  3162.532  3260.609  3280.818
1982  3274.302  3331.972  3366.322  3402.561
1983  3473.413  3578.848  3689.179  3794.706
1984  3908.054  4009.601  4084.250  4148.551
1985  4230.168  4294.887  4386.773  4444.094
1986  4507.894  4545.340  4607.669  4657.627
1987  4722.156  4806.160  4884.555  5007.994
1988  5073.372  5190.036  5282.835  5399.509
1989  5511.253  5612.463  5695.365  5747.237
1990  5872.701  5960.028  6015.116  6004.733
1991  6035.178  6126.862  6205.937  6264.540
1992  6363.102  6470.763  6566.641  6680.803
1993  6729.459  6808.939  6882.098  7013.738
1994  7115.652  7246.931  7331.075  7455.288
1995  7522.289  7580.997  7683.125  7772.586
1996  7868.468  8032.840  8131.408  8259.771
1997  8362.655  8518.825  8662.823  8765.907
1998  8866.480  8969.699  9121.097  9293.991
1999  9417.264  9524.152  9681.856  9899.378
2000 10002.857 10247.679 10319.825 10439.025
2001 10472.879 10597.822 10596.294 10660.294
2002 10788.952 10893.207 10992.051 11071.463
2003 11183.507 11312.875 11567.326 11769.275
2004 11920.169 12108.987 12303.340 12522.425
2005 12761.337 12910.022 13142.873 13332.316
2006 13603.933 13749.806 13867.469 14037.228
2007 14208.569 14382.363 14535.003 14681.501
2008 14651.039 14805.611 14835.187 14559.543
2009 14394.547 14352.850 14420.312 14628.021
2010 14721.350 14926.098 15079.917 15240.843
2011 15285.828 15496.189 15591.850 15796.460
2012 16019.758 16152.257 16257.151 16358.863
2013 16569.591 16637.926 16848.748 17083.137
2014 17102.932 17425.766 17719.836 17838.454
2015 17970.422 18221.299 18331.093 18354.372
2016 18409.130 18640.732 18799.648 18979.245
2017 19162.550 19359.123 19588.074 19831.829
2018 20041.047 20411.924                    

ts.plot(mydata)

mydata <- Quandl("FRED/GDP", type="ts", start_date="2001-12-31", end_date="2005-12-31")
ts.plot(mydata)

mydata <- Quandl("FRED/GDP", type="ts", collapse="annual")
mydata

Time Series:
Start = 1947 
End = 2018 
Frequency = 1 
 [1]   259.745   280.366   270.627   319.945   356.178   380.812   385.970
 [8]   399.734   437.092   460.463   474.864   499.555   528.600   540.197
[15]   580.612   612.280   653.938   697.319   771.857   833.302   881.439
[22]   968.030  1038.147  1088.608  1190.297  1328.904  1476.289  1599.679
[29]  1761.831  1934.273  2164.270  2476.949  2723.883  2985.557  3280.818
[36]  3402.561  3794.706  4148.551  4444.094  4657.627  5007.994  5399.509
[43]  5747.237  6004.733  6264.540  6680.803  7013.738  7455.288  7772.586
[50]  8259.771  8765.907  9293.991  9899.378 10439.025 10660.294 11071.463
[57] 11769.275 12522.425 13332.316 14037.228 14681.501 14559.543 14628.021
[64] 15240.843 15796.460 16358.863 17083.137 17838.454 18354.372 18979.245
[71] 19831.829 20411.924

ts.plot(mydata)

Look up the unemployment rate on FRED.

mydata <- Quandl("FRED/UNRATE", type="ts")
mydata

      Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
1948  3.4  3.8  4.0  3.9  3.5  3.6  3.6  3.9  3.8  3.7  3.8  4.0
1949  4.3  4.7  5.0  5.3  6.1  6.2  6.7  6.8  6.6  7.9  6.4  6.6
1950  6.5  6.4  6.3  5.8  5.5  5.4  5.0  4.5  4.4  4.2  4.2  4.3
1951  3.7  3.4  3.4  3.1  3.0  3.2  3.1  3.1  3.3  3.5  3.5  3.1
1952  3.2  3.1  2.9  2.9  3.0  3.0  3.2  3.4  3.1  3.0  2.8  2.7
1953  2.9  2.6  2.6  2.7  2.5  2.5  2.6  2.7  2.9  3.1  3.5  4.5
1954  4.9  5.2  5.7  5.9  5.9  5.6  5.8  6.0  6.1  5.7  5.3  5.0
1955  4.9  4.7  4.6  4.7  4.3  4.2  4.0  4.2  4.1  4.3  4.2  4.2
1956  4.0  3.9  4.2  4.0  4.3  4.3  4.4  4.1  3.9  3.9  4.3  4.2
1957  4.2  3.9  3.7  3.9  4.1  4.3  4.2  4.1  4.4  4.5  5.1  5.2
1958  5.8  6.4  6.7  7.4  7.4  7.3  7.5  7.4  7.1  6.7  6.2  6.2
1959  6.0  5.9  5.6  5.2  5.1  5.0  5.1  5.2  5.5  5.7  5.8  5.3
1960  5.2  4.8  5.4  5.2  5.1  5.4  5.5  5.6  5.5  6.1  6.1  6.6
1961  6.6  6.9  6.9  7.0  7.1  6.9  7.0  6.6  6.7  6.5  6.1  6.0
1962  5.8  5.5  5.6  5.6  5.5  5.5  5.4  5.7  5.6  5.4  5.7  5.5
1963  5.7  5.9  5.7  5.7  5.9  5.6  5.6  5.4  5.5  5.5  5.7  5.5
1964  5.6  5.4  5.4  5.3  5.1  5.2  4.9  5.0  5.1  5.1  4.8  5.0
1965  4.9  5.1  4.7  4.8  4.6  4.6  4.4  4.4  4.3  4.2  4.1  4.0
1966  4.0  3.8  3.8  3.8  3.9  3.8  3.8  3.8  3.7  3.7  3.6  3.8
1967  3.9  3.8  3.8  3.8  3.8  3.9  3.8  3.8  3.8  4.0  3.9  3.8
1968  3.7  3.8  3.7  3.5  3.5  3.7  3.7  3.5  3.4  3.4  3.4  3.4
1969  3.4  3.4  3.4  3.4  3.4  3.5  3.5  3.5  3.7  3.7  3.5  3.5
1970  3.9  4.2  4.4  4.6  4.8  4.9  5.0  5.1  5.4  5.5  5.9  6.1
1971  5.9  5.9  6.0  5.9  5.9  5.9  6.0  6.1  6.0  5.8  6.0  6.0
1972  5.8  5.7  5.8  5.7  5.7  5.7  5.6  5.6  5.5  5.6  5.3  5.2
1973  4.9  5.0  4.9  5.0  4.9  4.9  4.8  4.8  4.8  4.6  4.8  4.9
1974  5.1  5.2  5.1  5.1  5.1  5.4  5.5  5.5  5.9  6.0  6.6  7.2
1975  8.1  8.1  8.6  8.8  9.0  8.8  8.6  8.4  8.4  8.4  8.3  8.2
1976  7.9  7.7  7.6  7.7  7.4  7.6  7.8  7.8  7.6  7.7  7.8  7.8
1977  7.5  7.6  7.4  7.2  7.0  7.2  6.9  7.0  6.8  6.8  6.8  6.4
1978  6.4  6.3  6.3  6.1  6.0  5.9  6.2  5.9  6.0  5.8  5.9  6.0
1979  5.9  5.9  5.8  5.8  5.6  5.7  5.7  6.0  5.9  6.0  5.9  6.0
1980  6.3  6.3  6.3  6.9  7.5  7.6  7.8  7.7  7.5  7.5  7.5  7.2
1981  7.5  7.4  7.4  7.2  7.5  7.5  7.2  7.4  7.6  7.9  8.3  8.5
1982  8.6  8.9  9.0  9.3  9.4  9.6  9.8  9.8 10.1 10.4 10.8 10.8
1983 10.4 10.4 10.3 10.2 10.1 10.1  9.4  9.5  9.2  8.8  8.5  8.3
1984  8.0  7.8  7.8  7.7  7.4  7.2  7.5  7.5  7.3  7.4  7.2  7.3
1985  7.3  7.2  7.2  7.3  7.2  7.4  7.4  7.1  7.1  7.1  7.0  7.0
1986  6.7  7.2  7.2  7.1  7.2  7.2  7.0  6.9  7.0  7.0  6.9  6.6
1987  6.6  6.6  6.6  6.3  6.3  6.2  6.1  6.0  5.9  6.0  5.8  5.7
1988  5.7  5.7  5.7  5.4  5.6  5.4  5.4  5.6  5.4  5.4  5.3  5.3
1989  5.4  5.2  5.0  5.2  5.2  5.3  5.2  5.2  5.3  5.3  5.4  5.4
1990  5.4  5.3  5.2  5.4  5.4  5.2  5.5  5.7  5.9  5.9  6.2  6.3
1991  6.4  6.6  6.8  6.7  6.9  6.9  6.8  6.9  6.9  7.0  7.0  7.3
1992  7.3  7.4  7.4  7.4  7.6  7.8  7.7  7.6  7.6  7.3  7.4  7.4
1993  7.3  7.1  7.0  7.1  7.1  7.0  6.9  6.8  6.7  6.8  6.6  6.5
1994  6.6  6.6  6.5  6.4  6.1  6.1  6.1  6.0  5.9  5.8  5.6  5.5
1995  5.6  5.4  5.4  5.8  5.6  5.6  5.7  5.7  5.6  5.5  5.6  5.6
1996  5.6  5.5  5.5  5.6  5.6  5.3  5.5  5.1  5.2  5.2  5.4  5.4
1997  5.3  5.2  5.2  5.1  4.9  5.0  4.9  4.8  4.9  4.7  4.6  4.7
1998  4.6  4.6  4.7  4.3  4.4  4.5  4.5  4.5  4.6  4.5  4.4  4.4
1999  4.3  4.4  4.2  4.3  4.2  4.3  4.3  4.2  4.2  4.1  4.1  4.0
2000  4.0  4.1  4.0  3.8  4.0  4.0  4.0  4.1  3.9  3.9  3.9  3.9
2001  4.2  4.2  4.3  4.4  4.3  4.5  4.6  4.9  5.0  5.3  5.5  5.7
2002  5.7  5.7  5.7  5.9  5.8  5.8  5.8  5.7  5.7  5.7  5.9  6.0
2003  5.8  5.9  5.9  6.0  6.1  6.3  6.2  6.1  6.1  6.0  5.8  5.7
2004  5.7  5.6  5.8  5.6  5.6  5.6  5.5  5.4  5.4  5.5  5.4  5.4
2005  5.3  5.4  5.2  5.2  5.1  5.0  5.0  4.9  5.0  5.0  5.0  4.9
2006  4.7  4.8  4.7  4.7  4.6  4.6  4.7  4.7  4.5  4.4  4.5  4.4
2007  4.6  4.5  4.4  4.5  4.4  4.6  4.7  4.6  4.7  4.7  4.7  5.0
2008  5.0  4.9  5.1  5.0  5.4  5.6  5.8  6.1  6.1  6.5  6.8  7.3
2009  7.8  8.3  8.7  9.0  9.4  9.5  9.5  9.6  9.8 10.0  9.9  9.9
2010  9.8  9.8  9.9  9.9  9.6  9.4  9.4  9.5  9.5  9.4  9.8  9.3
2011  9.1  9.0  9.0  9.1  9.0  9.1  9.0  9.0  9.0  8.8  8.6  8.5
2012  8.3  8.3  8.2  8.2  8.2  8.2  8.2  8.1  7.8  7.8  7.7  7.9
2013  8.0  7.7  7.5  7.6  7.5  7.5  7.3  7.2  7.2  7.2  6.9  6.7
2014  6.6  6.7  6.7  6.3  6.3  6.1  6.2  6.2  5.9  5.7  5.8  5.6
2015  5.7  5.5  5.5  5.4  5.5  5.3  5.2  5.1  5.0  5.0  5.0  5.0
2016  4.9  4.9  5.0  5.0  4.7  4.9  4.9  4.9  5.0  4.9  4.6  4.7
2017  4.8  4.7  4.5  4.4  4.3  4.3  4.3  4.4  4.2  4.1  4.1  4.1
2018  4.1  4.1  4.1  3.9  3.8  4.0  3.9  3.9  3.7               

ts.plot(mydata)