Publications by SP
Data analysis first year
Characterizing plant assemblies Identify plant assemblages highlighting dominant and indicator species of the pastoral mountains in Castril, Santiago and Pontones (CSP) pasturelands. We hypothesise that pastoral commons shape plant diversity in CSP. Second, we hypothesise that livestock mobility, referred here to long- or short-transhumance, sh...
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Pulse on the US Economy
Pulse on the US Economy Column_1 Indicator Value Unit Period Freq GDP growth 2.9 % 2022-10-01 quarterly GDP forecast next qtr [a] 0.7 % 2023-01-01 quarterly Productivity 0.8 % 2022-07-01 quarterly Employment cost index 5.0 % 2022-07-01 quarterly Average hourly earnings 4.6 % 2022-12-01 monthly Jobs added 223.0 ...
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Brexit and growth in Europe
Has Brexit Been Good for the UK? Column Countdown to Brexit June 2016: Referendum. Vote in favor of leaving the European Union. March 2017: UK formally triggers Article 50 and begins the two-year countdown to the UK formally leaving the EU. Article 50 extended a couple of times. 31 January 2020: UK leaves the EU and enters a transition perio...
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Plots, plots, plots!
Load packages library(tidyverse) library(gapminder) Make a copy of gapminder df1 <- gapminder Inspect the data: The first 6 rows df1 %>% head() ## # A tibble: 6 × 6 ## country continent year lifeExp pop gdpPercap ## <fct> <fct> <int> <dbl> <int> <dbl> ## 1 Afghanistan Asia 1952 28.8 8425333 77...
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Barplots exercise
Load packages library(tidyverse) Dataset Import the gapminder dataset, in one of two ways: Use library(gapminder) to load the gapminder package, OR Use read_csv("filename.csv") to read the csv file df1 <- read_csv("gapminder-data.csv") # IMPORTANT! The file must be in the working directory Inspect the data head(df1) ## # A tibble: 6 × 6 ## c...
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Intro to ggplot
Install necessary packages We will be using two packages: tidyverse and gapminder install.packages("tidyverse") install.packages("gapminder") # You need to do this step only once. Once the packages are installed on your machine, you can skip this step and go on to load the packages. Load packages library(tidyverse) library(gapminder) Inspect the...
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GDP forecast
Load packages library(curl) library(tidyverse) library(readxl) library(janitor) library(lubridate) library(gt) library(ggpmisc) library(rmarkdown) library(glue) library(ggtext) Get the data url <- "https://www.atlantafed.org/-/media/documents/cqer/researchcq/gdpnow/GDPTrackingModelDataAndForecasts.xlsx" destfile <- "data/GDPTrackingModelDataAndF...
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Incomes of countries
Incomes of Countries Column INDIA’S INCOME IN 2021 Measure Value Units gdp 3.2 $, trillions gdp_per_capita 2277.4 $ gdp_ppp 10.2 $, trillions gdp_per_capita_ppp 7333.5 $ gni_per_capita_2017_ppp 6571.1 $ gni_per_capita_atlas_method 2170.0 $ India’s GNI per capita (Atlas method) of $2,170 places India in the Lower Middl...
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COMPASS Data Pipeline Example
Figure | Flowchart of potential pathways of using compasstools for sapflow sensor data processing Raw file fn <- system.file("PNNL_11_sapflow_1min.dat", package = "compasstools") dat_raw <- readLines(fn) kable(dat_raw) %>% scroll_box(width = "100%") x "TOA5","PNNL_11","CR1000X","29517","CR1000X.Std.05.01","CPU:Tempest_v5_8_1_21.CR1X","45715",...
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State incomes in India
State incomes in India Column_1 Per-capita Nominal Net State Domestic Product in 2020 State/UT Per-capita nominal Net SDP (rupees) Andaman & Nicobar Islands NA Andhra Pradesh 177,000 Arunachal Pradesh 192,000 Assam 87,000 Bihar 44,000 Chandigarh 293,000 Chhattisgarh 105,000 Delhi 344,000 Goa 431,000 Gujarat 213,000 Hary...
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