indexing: Indexing a Series

In JavierMtzRdz/presupuestoR: Paquete para análisis del presupuesto federal de México

Indexing a Series

Description

The 'indexing()' function enables the creation of an index from a numeric variable, using specified observations as reference points.

Usage

indexing(.x, col_from, ..., col_to = index, n_base = 100)

Arguments

.x	Tidy dataset.
col_from	Column containing the numeric variable to be indexed.
...	Components to select the base observation(s).
col_to	Column to store the result (default is 'index').
n_base	Base value for the index (default is 100).

Value

Returns the tidy dataset with the indexed column

Examples

# Example 1: ---------------------------------------------------------------------
# In this example, the function generated a time series and established an
# index using the `values` column. The base observation is set at
# `2023-01-01`.

## Load packages
library(dplyr)
library(ggplot2)

## Generating toy dataset
set.seed(545)

df <- data.frame(date = seq(as.Date("2023-01-01"),
                        as.Date("2025-12-01"),
                        "month"),
             values = runif(12*3, 50, 150)*
               (2 + cumsum(runif(12*3, 0, 0.15))))

head(df)

#> # A tibble: 6 × 2
#>   date       values
#>   <date>      <dbl>
#> 1 2023-01-01   283.
#> 2 2023-02-01   129.
#> 3 2023-03-01   235.
#> 4 2023-04-01   298.
#> 5 2023-05-01   189.
#> 6 2023-06-01   354.

## Index generation

df2 <- indexing(df,
                values,
                date == as.Date("2023-01-01"))

head(df2)

#> # A tibble: 6 × 3
#>   date       values index
#>   <date>      <dbl> <dbl>
#> 1 2023-01-01   283. 100
#> 2 2023-02-01   129.  45.6
#> 3 2023-03-01   235.  83.2
#> 4 2023-04-01   298. 105.
#> 5 2023-05-01   189.  66.8
#> 6 2023-06-01   354. 125.

# Comparing original variable vs. indexed variable.

df2 %>%
  ggplot(aes(x = date)) +
  geom_hline(yintercept = 100,
             linetype = "dashed") +
  geom_line(aes(y = values,
                color = "values")) +
  geom_line(aes(y = index,
                color = "index")) +
  theme_minimal()

# Example 3: ---------------------------------------------------------------------
# Using the toy dataset from earlier, this code chunk generates an indexed
# variable taking the average values of multiple observations as reference.
# Specifically, it computes the average for the year 2023. A warning is issued
# in case this operation was not intended.

## Index generation

df2 <- indexing(df,
                values,
                lubridate::year(date) == 2023)

#> Warning: More than one row is being used as a reference.

head(df2)

## Comparing original variable vs. indexed variable.

#> # A tibble: 6 × 3
#>   date       values index
#>   <date>      <dbl> <dbl>
#> 1 2023-01-01   283. 116.
#> 2 2023-02-01   129.  52.7
#> 3 2023-03-01   235.  96.3
#> 4 2023-04-01   298. 122.
#> 5 2023-05-01   189.  77.3
#> 6 2023-06-01   354. 145.

# Comparing original variable vs. indexed variable.
df2 %>%
  ggplot(aes(x = date)) +
  geom_hline(yintercept = 100,
             linetype = "dashed") +
  geom_line(aes(y = values,
                color = "values")) +
  geom_line(aes(y = index,
                color = "index")) +
  theme_minimal()

# Example 3: ---------------------------------------------------------------------
# In this section, we indexed the GDP per capita for Oceania countries taking
# the year 1952 as the base.


## Grouped index generation

library(gapminder)

idx_gap <- gapminder::gapminder %>%
  filter(continent == "Oceania") %>%
  group_by(country) %>%
  indexing(gdpPercap,
           year == 1952)

head(idx_gap)

#> # A tibble: 6 × 7
#> # Groups:   country [1]
#>   country   continent  year lifeExp      pop gdpPercap index
#>   <fct>     <fct>     <int>   <dbl>    <int>     <dbl> <dbl>
#> 1 Australia Oceania    1952    69.1  8691212    10040.  100
#> 2 Australia Oceania    1957    70.3  9712569    10950.  109.
#> 3 Australia Oceania    1962    70.9 10794968    12217.  122.
#> 4 Australia Oceania    1967    71.1 11872264    14526.  145.
#> 5 Australia Oceania    1972    71.9 13177000    16789.  167.
#> 6 Australia Oceania    1977    73.5 14074100    18334.  183.

## Ploting generated index
idx_gap %>%
  ggplot2::ggplot(aes(x = year,
             y = index,
             color = country)) +
  geom_line() +
  theme_minimal()

JavierMtzRdz/presupuestoR documentation built on June 11, 2024, 11:38 a.m.