---
title: "Inflation explorer: showing the change in price for various goods and services"
format:
1  dashboard:
2    logo: images/logo.png
    nav-buttons:
    - icon: github
      href: "https://github.com/ivelasq/inflation-explorer"
    theme:
    - pulse
    - custom.scss
3resource_files:
- custom.scss
- images/logo.png
---

4```{r}
#| label: setup
#| include: false
library(pins)
library(lubridate)
library(dplyr)
library(tidyr)
library(ggplot2)
library(RColorBrewer)
library(gt)
library(plotly)

5board 
  mutate(year_month = as.Date(year_month, format = "%Y-%m-%d"))

# Value for last updated date
last_updated_date 
  summarise(last_updated_date = max(year_month)) |>
  pull(last_updated_date)

# Value for the percentage change from the previous month
cpi_df  
  filter(seriesID == "CUUR0000SA0")

latest_cpi_value 
  summarise(latest_value = last(value)) |>
  pull(latest_value)

latest_cpi_percent_change 
  filter(year_month == last_updated_date) |>
  pull(jan_2018_pct_change)

# Data for table
pivot_df  
  select(category_label, year_month, percent_change_from_previous_month) |>
  pivot_wider(names_from = year_month, 
              values_from = percent_change_from_previous_month) %>%
  select(category_label, tail(names(.), 5)) |> 
  arrange(desc(category_label))
```

## Row {height=20%}

```{r} 
#| label: valuebox1
#| content: valuebox
#| title: "Last updated"
#| color: #fff
6last_updated_date
```

```{r} 
#| label: valuebox2
#| content: valuebox
#| title: "Consumer Price Index (CPI)"
#| icon: basket
7list(
  value = round(latest_cpi_value, 2),
  icon = "basket",
  color = "primary"
)
```

```{r}
#| label: valuebox3
#| content: valuebox
#| title: "Increase from previous month"
#| icon: percent
#| color: primary
value = round(latest_cpi_percent_change, 2)
```

## Row {height=80%}

### Column {width=20%}

The **Consumer Price Index (CPI)** is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. 

Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available.

**Source: Bureau of Labor Statistics**

### Column {.tabset width=80%}

```{r}
#| label: pct-change-jan-2018-code
#| include: false
8df %
  arrange(desc(category_label), desc(year_month))

p1 %
  filter(year_month == max(year_month)) %>%
  arrange(desc(percent_change_from_previous_month))

top_six_categories %
  slice_head(n = 6)

p2 % 
9  gt() %>%
  tab_header(
    title = "Monthly Percent Change by Category",
    subtitle = "Last four months"
  ) %>%
  fmt_number(
    columns = 2:5,
    decimals = 2,
  ) %>%
  tab_style(
    style = cell_text(weight = "bold", align = "center"),
    locations = cells_column_labels(everything())
  ) |> 
  data_color(
    method = "numeric",
    palette = "BuPu"
  )

pivot_gt
```