dplyr Time Series Manipulation

class: center, middle, inverse, title-slide

# dplyr Time Series Manipulation
## Calculate Growth Rates and Ratios
### 2017/12/11

---

class: inverse, center, middle

# Calculating Ratios using dplyr

---

## 6A. Value added and its components by activity, ISIC rev4

- http://stats.oecd.org/Index.aspx?DataSetCode=SNA_TABLE6A
- Location: OECD Countries
- Transaction: VA (B1GA), Output (P1), Intermediate Cons (P2)
- Activity: 21 Sections ISIC Rev. 4 and Total Economy
- Measure: Current prices, Constant Prices (National Base Year)
- Time: 2000-2016
- Value: National Currency (Mio.)

```r
sna_dat <- read.csv("../data/sna_table6a.csv")
```

---

### Create subset with total economy data

Could be any other data set with harmonized dimensions

- rename value column to avoid automatic joining on common names

```r
sna_dat_tot <-
  sna_dat %>% filter(ACTIVITY == "VTOT") %>%
  mutate(value_total = Value) %>%
  select(LOCATION, TRANSACT, MEASURE, TIME, value_total)
```

---

### Calculate activities' share in total economy

- join on common columns (here specified explicitly)
- calculate ratio using two numeric columns (check reusult for `Inf` and `NA`)

```r
sna_dat_share <- sna_dat %>%
  left_join(sna_dat_tot, by = c("LOCATION", "TRANSACT", "MEASURE", "TIME")) %>%
  mutate(share = Value / value_total,
         share_pct = share * 100)
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> LOCATION </th>
   <th style="text-align:left;"> TRANSACT </th>
   <th style="text-align:left;"> ACTIVITY </th>
   <th style="text-align:left;"> MEASURE </th>
   <th style="text-align:right;"> TIME </th>
   <th style="text-align:right;"> Value </th>
   <th style="text-align:right;"> value_total </th>
   <th style="text-align:right;"> share </th>
   <th style="text-align:right;"> share_pct </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2000 </td>
   <td style="text-align:right;"> 38908.35 </td>
   <td style="text-align:right;"> 190624.8 </td>
   <td style="text-align:right;"> 0.204 </td>
   <td style="text-align:right;"> 20.4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2001 </td>
   <td style="text-align:right;"> 40446.71 </td>
   <td style="text-align:right;"> 197076.6 </td>
   <td style="text-align:right;"> 0.205 </td>
   <td style="text-align:right;"> 20.5 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2002 </td>
   <td style="text-align:right;"> 40192.86 </td>
   <td style="text-align:right;"> 202353.4 </td>
   <td style="text-align:right;"> 0.199 </td>
   <td style="text-align:right;"> 19.9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2003 </td>
   <td style="text-align:right;"> 40467.36 </td>
   <td style="text-align:right;"> 207247.7 </td>
   <td style="text-align:right;"> 0.195 </td>
   <td style="text-align:right;"> 19.5 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2004 </td>
   <td style="text-align:right;"> 42014.61 </td>
   <td style="text-align:right;"> 216098.3 </td>
   <td style="text-align:right;"> 0.194 </td>
   <td style="text-align:right;"> 19.4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2005 </td>
   <td style="text-align:right;"> 44228.92 </td>
   <td style="text-align:right;"> 225888.1 </td>
   <td style="text-align:right;"> 0.196 </td>
   <td style="text-align:right;"> 19.6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2006 </td>
   <td style="text-align:right;"> 47735.52 </td>
   <td style="text-align:right;"> 239076.0 </td>
   <td style="text-align:right;"> 0.200 </td>
   <td style="text-align:right;"> 20.0 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2007 </td>
   <td style="text-align:right;"> 51552.36 </td>
   <td style="text-align:right;"> 253604.7 </td>
   <td style="text-align:right;"> 0.203 </td>
   <td style="text-align:right;"> 20.3 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2008 </td>
   <td style="text-align:right;"> 51165.88 </td>
   <td style="text-align:right;"> 262414.8 </td>
   <td style="text-align:right;"> 0.195 </td>
   <td style="text-align:right;"> 19.5 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2009 </td>
   <td style="text-align:right;"> 47129.75 </td>
   <td style="text-align:right;"> 256671.0 </td>
   <td style="text-align:right;"> 0.184 </td>
   <td style="text-align:right;"> 18.4 </td>
  </tr>
</tbody>
</table>

---

### Plot activities' share in total economy (selected countries)

```r
sna_dat_share %>%
  filter(LOCATION%in%c("AUT","BEL") & ACTIVITY!="VTOT" & MEASURE=="C") %>%
  ggplot(aes(x = TIME, y = share, color = ACTIVITY)) + geom_line() +
  facet_grid(Country ~ Transaction) + scale_color_discrete(guide = guide_legend(ncol = 2))
```

![](11-dplyr-time-series/fig-html/data_plot_sna-1.svg)

---
class: inverse, center, middle

# Ratio example: Top 3 activities by country in 2016

---

### Ratio example: Top 3 activities by country in 2016

```r
sna_dat_share_b1ga_2016_top3 <- sna_dat_share %>%
  filter(ACTIVITY != "VTOT", TRANSACT == "B1GA", MEASURE == "C", TIME == "2016") %>%
  group_by(LOCATION) %>%
  top_n(3, wt = share)
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> LOCATION </th>
   <th style="text-align:left;"> TRANSACT </th>
   <th style="text-align:left;"> MEASURE </th>
   <th style="text-align:right;"> TIME </th>
   <th style="text-align:left;"> ACTIVITY </th>
   <th style="text-align:right;"> Value </th>
   <th style="text-align:right;"> value_total </th>
   <th style="text-align:right;"> share </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:right;"> 57258.75 </td>
   <td style="text-align:right;"> 314692.5 </td>
   <td style="text-align:right;"> 0.18 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VG </td>
   <td style="text-align:right;"> 38405.87 </td>
   <td style="text-align:right;"> 314692.5 </td>
   <td style="text-align:right;"> 0.12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUT </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VL </td>
   <td style="text-align:right;"> 30999.79 </td>
   <td style="text-align:right;"> 314692.5 </td>
   <td style="text-align:right;"> 0.10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> BEL </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:right;"> 53858.70 </td>
   <td style="text-align:right;"> 377635.6 </td>
   <td style="text-align:right;"> 0.14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> BEL </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VG </td>
   <td style="text-align:right;"> 46028.20 </td>
   <td style="text-align:right;"> 377635.6 </td>
   <td style="text-align:right;"> 0.12 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> BEL </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VM </td>
   <td style="text-align:right;"> 36101.20 </td>
   <td style="text-align:right;"> 377635.6 </td>
   <td style="text-align:right;"> 0.10 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CHE </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:right;"> 117303.76 </td>
   <td style="text-align:right;"> 638981.4 </td>
   <td style="text-align:right;"> 0.18 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CHE </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VG </td>
   <td style="text-align:right;"> 91272.66 </td>
   <td style="text-align:right;"> 638981.4 </td>
   <td style="text-align:right;"> 0.14 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CHE </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VO </td>
   <td style="text-align:right;"> 68343.49 </td>
   <td style="text-align:right;"> 638981.4 </td>
   <td style="text-align:right;"> 0.11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CZE </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VC </td>
   <td style="text-align:right;"> 1162392.00 </td>
   <td style="text-align:right;"> 4292397.0 </td>
   <td style="text-align:right;"> 0.27 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CZE </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VG </td>
   <td style="text-align:right;"> 471827.00 </td>
   <td style="text-align:right;"> 4292397.0 </td>
   <td style="text-align:right;"> 0.11 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CZE </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:left;"> VL </td>
   <td style="text-align:right;"> 360797.00 </td>
   <td style="text-align:right;"> 4292397.0 </td>
   <td style="text-align:right;"> 0.08 </td>
  </tr>
</tbody>
</table>

---

### Ratio example: Top 3 activities by country in 2016

```r
sna_dat_share_b1ga_2016_top3 %>%
  mutate(act_label = paste(ACTIVITY, Activity)) %>%
  ggplot(aes(x = LOCATION, y = share, fill = act_label)) +
  geom_bar(stat = "identity", position = "stack", width = 0.6) +
  scale_fill_discrete(guide = guide_legend(nrow = 3)) +
  theme(legend.position = "top", legend.direction = "horizontal")
```

![](11-dplyr-time-series/fig-html/plot_top_sna-1.svg)

---
class: inverse, center, middle

# Calculating Growth Rates using dplyr

---

### The `lag` function

- Time dimension must be in `date` format "`yyyy-mm-dd`"

```r
sna_dat2 <- sna_dat %>% mutate(date = as.Date(paste0(TIME, "-01-01")))
head(sna_dat2$date, 5)
```

```
## [1] "2000-01-01" "2001-01-01" "2002-01-01" "2003-01-01" "2004-01-01"
```

```r
class(sna_dat2$date)
```

```
## [1] "Date"
```

```r
dplyr::lag(head(sna_dat2$date, 5))
```

```
## [1] NA           "2000-01-01" "2001-01-01" "2002-01-01" "2003-01-01"
```

```r
stats::lag(head(sna_dat2$date, 5))
```

```
## [1] "2000-01-01" "2001-01-01" "2002-01-01" "2003-01-01" "2004-01-01"
```

```r
## ?lag
```

---

### Calculate Growth Rate

```r
sna_growth <- sna_dat2 %>%
  group_by(LOCATION, TRANSACT, ACTIVITY, MEASURE) %>%
  mutate(value_lag = lag(Value),
         growth = Value / value_lag - 1)
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> LOCATION </th>
   <th style="text-align:left;"> TRANSACT </th>
   <th style="text-align:left;"> ACTIVITY </th>
   <th style="text-align:left;"> MEASURE </th>
   <th style="text-align:right;"> TIME </th>
   <th style="text-align:right;"> Value </th>
   <th style="text-align:right;"> value_lag </th>
   <th style="text-align:right;"> growth </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2000 </td>
   <td style="text-align:right;"> 644959 </td>
   <td style="text-align:right;"> NA </td>
   <td style="text-align:right;"> NA </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2001 </td>
   <td style="text-align:right;"> 690375 </td>
   <td style="text-align:right;"> 644959 </td>
   <td style="text-align:right;"> 0.070 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2002 </td>
   <td style="text-align:right;"> 731107 </td>
   <td style="text-align:right;"> 690375 </td>
   <td style="text-align:right;"> 0.059 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2003 </td>
   <td style="text-align:right;"> 786958 </td>
   <td style="text-align:right;"> 731107 </td>
   <td style="text-align:right;"> 0.076 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2004 </td>
   <td style="text-align:right;"> 847314 </td>
   <td style="text-align:right;"> 786958 </td>
   <td style="text-align:right;"> 0.077 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2005 </td>
   <td style="text-align:right;"> 919054 </td>
   <td style="text-align:right;"> 847314 </td>
   <td style="text-align:right;"> 0.085 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2006 </td>
   <td style="text-align:right;"> 1002660 </td>
   <td style="text-align:right;"> 919054 </td>
   <td style="text-align:right;"> 0.091 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2007 </td>
   <td style="text-align:right;"> 1088972 </td>
   <td style="text-align:right;"> 1002660 </td>
   <td style="text-align:right;"> 0.086 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2008 </td>
   <td style="text-align:right;"> 1175982 </td>
   <td style="text-align:right;"> 1088972 </td>
   <td style="text-align:right;"> 0.080 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> AUS </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2009 </td>
   <td style="text-align:right;"> 1207173 </td>
   <td style="text-align:right;"> 1175982 </td>
   <td style="text-align:right;"> 0.027 </td>
  </tr>
</tbody>
</table>

---
class: inverse, center, middle

# Growth rate example: countries with maximum absolute growth rates

---

### Countries with maximum absolute growth rates

```r
sna_growth_top <- sna_growth %>%
  filter(ACTIVITY == "VTOT" & TRANSACT == "B1GA") %>%
  group_by(LOCATION) %>%
  top_n(n = 1, wt = abs(growth)) %>%
  arrange(desc(growth))
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> LOCATION </th>
   <th style="text-align:left;"> TRANSACT </th>
   <th style="text-align:left;"> ACTIVITY </th>
   <th style="text-align:left;"> MEASURE </th>
   <th style="text-align:right;"> TIME </th>
   <th style="text-align:right;"> Value </th>
   <th style="text-align:right;"> value_lag </th>
   <th style="text-align:right;"> growth </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> TUR </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2002 </td>
   <td style="text-align:right;"> 317199.87 </td>
   <td style="text-align:right;"> 218880.94 </td>
   <td style="text-align:right;"> 0.449 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> IRL </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2015 </td>
   <td style="text-align:right;"> 236813.52 </td>
   <td style="text-align:right;"> 177538.93 </td>
   <td style="text-align:right;"> 0.334 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> LVA </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2007 </td>
   <td style="text-align:right;"> 20069.82 </td>
   <td style="text-align:right;"> 15130.98 </td>
   <td style="text-align:right;"> 0.326 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> EST </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2007 </td>
   <td style="text-align:right;"> 14258.48 </td>
   <td style="text-align:right;"> 11888.96 </td>
   <td style="text-align:right;"> 0.199 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ISL </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2008 </td>
   <td style="text-align:right;"> 1356808.00 </td>
   <td style="text-align:right;"> 1152608.00 </td>
   <td style="text-align:right;"> 0.177 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> HUN </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2001 </td>
   <td style="text-align:right;"> 13335190.00 </td>
   <td style="text-align:right;"> 11395842.00 </td>
   <td style="text-align:right;"> 0.170 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> LUX </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2006 </td>
   <td style="text-align:right;"> 30338.94 </td>
   <td style="text-align:right;"> 26668.19 </td>
   <td style="text-align:right;"> 0.138 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> MEX </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2004 </td>
   <td style="text-align:right;"> 8299895.00 </td>
   <td style="text-align:right;"> 7302821.00 </td>
   <td style="text-align:right;"> 0.137 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> SVK </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2006 </td>
   <td style="text-align:right;"> 50714.29 </td>
   <td style="text-align:right;"> 44744.18 </td>
   <td style="text-align:right;"> 0.133 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> NOR </td>
   <td style="text-align:left;"> B1GA </td>
   <td style="text-align:left;"> VTOT </td>
   <td style="text-align:left;"> C </td>
   <td style="text-align:right;"> 2008 </td>
   <td style="text-align:right;"> 2344746.00 </td>
   <td style="text-align:right;"> 2085049.00 </td>
   <td style="text-align:right;"> 0.125 </td>
  </tr>
</tbody>
</table>

---

### Countries with maximum absolute growth rates

```r
sna_growth %>% filter(LOCATION%in%sna_growth_top$LOCATION[1:8] &
                      ACTIVITY == "VTOT" & TRANSACT == "B1GA") %>%
  ggplot(aes(x = date, y = growth, color = Measure)) +
  geom_line(size = 1) + facet_wrap( ~ LOCATION, ncol = 4) +
  theme(legend.position = "top", legend.direction = "horizontal")
```

![](11-dplyr-time-series/fig-html/sna_growth_plot-1.svg)

---
class: inverse, center, middle

# Introductory Time Series With R

## S P Cowpertwait, Paul & Metcalfe, Andrew (2009)

10.1007/978-0-387-88698-5

---

## Basic Time Series Manipulation

- number of international passenger bookings (in thousands) per month on an
airline (Pan Am) in the United States
- Federal Aviation Administration, 1949–1960
- used to predict future demand before ordering new aircraft and training
  aircrew
- Brown, R. (1963). Smoothing, Forecasting, and Prediction of Discrete Time
Series. Englewood Cliffs, NJ: Prentice-Hall.

```r
data(AirPassengers)
AP <- AirPassengers
head(AP)
```

```
## [1] 112 118 132 129 121 135
```

```r
class(AP)
```

```
## [1] "ts"
```

---

## Methods for `ts` objects

```r
start(AP); end(AP); frequency(AP); summary(AP)
```

```
## [1] 1949    1
```

```
## [1] 1960   12
```

```
## [1] 12
```

```
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   104.0   180.0   265.5   280.3   360.5   622.0
```

---

## Plotting `ts` objects

```r
par(mfrow = c(1, 2)); plot(AP, ylab = "Passengers (1000's)"); plot(aggregate(AP))
```

![](11-dplyr-time-series/fig-html/cw-example-5-1.svg)

---

## Aggregating `ts` objects

- trend analysis: remove seasonal effect  by aggregating to the annual level
- boxplot: summary of the values for each season
- `cycle` function being used to extract the seasons for each item of data

```r
par(mfrow = c(1, 2)); plot(aggregate(AP)); boxplot(AP ~ cycle(AP))
```

![](11-dplyr-time-series/fig-html/cw-example-7-1.svg)

---

```r
## www <- "http://www.massey.ac.nz/~pscowper/ts/USunemp.dat"
www <- "https://raw.githubusercontent.com/AtefOuni/ts/master/Data/USunemp.dat"
US.month <- read.table(www, header = T)
attach(US.month)
US.month.ts <- ts(USun, start=c(1996,1), end=c(2006,10), freq = 12)
plot(US.month.ts, ylab = "unemployed (%)")
```

![](11-dplyr-time-series/fig-html/cw-example-10-1-1.svg)

---

```
##   choc beer elec
## 1 1451 96.3 1497
## 2 2037 84.4 1463
## 3 2477 91.2 1648
## 4 2785 81.9 1595
```

```r
Elec.ts <- ts(CBE[, 3], start = 1958, freq = 12)
Beer.ts <- ts(CBE[, 2], start = 1958, freq = 12)
Choc.ts <- ts(CBE[, 1], start = 1958, freq = 12)
plot(cbind(Elec.ts, Beer.ts, Choc.ts))
```

![](11-dplyr-time-series/fig-html/cw-example-10-3-1.svg)

---
class: inverse, center, middle

# Growth Rate Example: Quarterly Data

---

## Create Example Data

```r
date <- c("2000-01-01","2000-04-01", "2000-07-01",
          "2000-10-01","2001-01-01","2001-04-01",
          "2001-07-01","2001-10-01","2002-01-01",
          "2002-04-01","2002-07-01","2002-10-01")
value <- c(1592,1825,1769,1909,2022,2287,2169,2366,2001,2087,2099,2258)
df <- data.frame(date,value)

## Convert date column to date format
df$date = as.POSIXct(df$date)
```

```
##         date value
## 1 2000-01-01  1592
## 2 2000-04-01  1825
## 3 2000-07-01  1769
## 4 2000-10-01  1909
## 5 2001-01-01  2022
## 6 2001-04-01  2287
```

---

## Growth Rate

Objective: calculate growth rate comparing quarter 1 from one year to quarter 1 for the following year

```r
df_q <- df %>% group_by(month=month(date)) %>%
  arrange(date) %>%
  mutate(yearOverYear=value/lag(value,1))
```

```
## # A tibble: 6 x 4
## # Groups:   month [4]
##         date value month yearOverYear
##       <dttm> <dbl> <dbl>        <dbl>
## 1 2000-01-01  1592     1           NA
## 2 2000-04-01  1825     4           NA
## 3 2000-07-01  1769     7           NA
## 4 2000-10-01  1909    10           NA
## 5 2001-01-01  2022     1     1.270101
## 6 2001-04-01  2287     4     1.253151
```

```r
## value[2001-01-01] / value[2000-01-01]
2022 / 1592
```

```
## [1] 1.270101
```

---

```
## R version 3.4.2 (2017-09-28)
## Platform: x86_64-redhat-linux-gnu (64-bit)
## Running under: Fedora 27 (Workstation Edition)
## 
## Matrix products: default
## BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] methods   stats     graphics  grDevices utils     datasets  base     
## 
## other attached packages:
## [1] bindrcpp_0.2    knitr_1.17      lubridate_1.6.0 tidyr_0.7.1    
## [5] dplyr_0.7.4     ggplot2_2.2.1   rmarkdown_1.6  
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_0.12.13     bindr_0.1        magrittr_1.5     munsell_0.4.3   
##  [5] colorspace_1.3-2 R6_2.2.2         rlang_0.1.2      highr_0.6       
##  [9] stringr_1.2.0    plyr_1.8.4       tools_3.4.2      grid_3.4.2      
## [13] gtable_0.2.0     xaringan_0.3     htmltools_0.3.6  yaml_2.1.14     
## [17] lazyeval_0.2.0   rprojroot_1.2    digest_0.6.12    assertthat_0.2.0
## [21] tibble_1.3.4     reshape2_1.4.2   purrr_0.2.3      glue_1.1.1      
## [25] evaluate_0.10.1  labeling_0.3     stringi_1.1.5    compiler_3.4.2  
## [29] scales_0.5.0     backports_1.1.0  pkgconfig_2.0.1
```