Step No.1

Let’s take a look at, for example, the exchange rate history of the US dollar against the euro. FRED collects this data series on a daily basis under ID DEXUSEU.

The FRED data set has two columns that interest us most: date and value.

## # A tibble: 6 x 3
##   date       series_id value
##   <date>     <chr>     <dbl>
## 1 2022-02-04 DEXUSEU    1.15
## 2 2022-02-07 DEXUSEU    1.14
## 3 2022-02-08 DEXUSEU    1.14
## 4 2022-02-09 DEXUSEU    1.14
## 5 2022-02-10 DEXUSEU    1.15
## 6 2022-02-11 DEXUSEU    1.14

Now, let’s plot the data. See below.

Non-Farm Payroll

Let’s

  1. grab the non-farm payroll employment data from BLS (ID: CES0000000001),
  2. then derive the NFP change in the most recent period and
  3. graph the whole data set.
## [1] "January 2022"
## [1] 467

Consumer Price Index

Let’s grab the most recent inflation data from BLS and graph it. I am interested in

  1. the general consumer price index, which is CPI-All items (ID: CUUR0000SA0),
  2. the price index of CPI-Used cars and trucks (ID: CUUR0000SETA02),
  3. and the price index of CPI-Meats (ID: CUUR0000SAF11211).

Now, let’s derive and plot the year-on-year changes in the CPI indexes:

## [1] "% year-on-year change of CUUR0000SA0 , All items"
##       Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
## 2017 2.50 2.74 2.38 2.20 1.87 1.63 1.73 1.94 2.23 2.04 2.20 2.11
## 2018 2.07 2.21 2.36 2.46 2.80 2.87 2.95 2.70 2.28 2.52 2.18 1.91
## 2019 1.55 1.52 1.86 2.00 1.79 1.65 1.81 1.75 1.71 1.76 2.05 2.29
## 2020 2.49 2.33 1.54 0.33 0.12 0.65 0.99 1.31 1.37 1.18 1.17 1.36
## 2021 1.40 1.68 2.62 4.16 4.99 5.39 5.37 5.25 5.39 6.22 6.81 7.04
## 2022 7.48                                                       
## [1] "% year-on-year change of CUUR0000SETA02 , Used cars and trucks"
##        Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec
## 2017 -3.69 -4.25 -4.66 -4.63 -4.31 -4.30 -4.08 -3.80 -3.75 -2.89 -2.10 -0.99
## 2018 -0.61 -0.09  0.37 -0.91 -1.68 -0.66  0.84  1.25 -1.47  0.43  2.30  1.43
## 2019  1.64  1.11  0.44  0.78  0.28  1.25  1.47  2.08  2.61  1.43 -0.44 -0.68
## 2020 -1.97 -1.33  0.13 -0.75 -0.36 -2.78 -0.88  3.98 10.27 11.54 10.86 10.04
## 2021  9.99  9.29  9.37 20.97 29.74 45.24 41.65 31.90 24.41 26.45 31.44 37.29
## 2022 40.51                                                                  
## [1] "% year-on-year change of CUUR0000SAF11211 , Meats"
##        Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec
## 2017 -3.63 -3.02 -2.31 -2.75 -2.20 -0.96  1.10  0.70  0.80  1.54  1.60  2.35
## 2018  2.36  1.49  1.38  2.43  1.42  0.08 -0.74 -0.28 -0.53 -1.20 -0.46 -0.87
## 2019  0.12  0.38  0.16 -0.25  1.62  1.32  1.60  0.76  1.33  2.47  2.49  3.58
## 2020  3.36  3.67  3.25  6.58 11.74 16.71 10.22  8.14  6.79  6.64  6.08  5.20
## 2021  5.53  5.62  5.84  4.00 -0.07 -0.48  5.89  8.62 12.63 14.51 15.97 14.75
## 2022 13.64