Publications by Your name here
Salaries of Professors Compared to Years of Service
Import data ## # A tibble: 397 × 6 ## rank discipline yrs.since.phd yrs.service sex salary ## <chr> <chr> <dbl> <dbl> <chr> <dbl> ## 1 Prof B 19 18 Male 139750 ## 2 Prof B 20 16 Male 173200 ## 3 AsstProf B 4 ...
249 sym 1 img
Data For Science
Welcome Ch1 Introduction The data science project workflow Prerequisites R RStudio r packages Install the tidyverse package Running R code 1+2 ## [1] 3 Getting help Google Stackoverflow Ch2 Introduction to Data Exploration Ch3 Data Visualization Set up data library(tidyverse) mpg ## # A tibble: 234 × 11 ## manufacturer model d...
1398 sym R (4884 sym/30 pcs) 7 img
Free and Fair Elections
Import data # excel file data <- read_excel("data/myData9.xlsx") data ## # A tibble: 14,784 × 45 ## country_name country_code year regime_category_index regime_category ## <chr> <chr> <dbl> <chr> <chr> ## 1 Afghanistan AFG 1950 5 Royal dictatorship ## 2 Afg...
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Test Publishing
Do your work here. library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.4 ...
26 sym R (1648 sym/4 pcs)
Presentacion series de tiempo
Series de Tiempo Integrantes Johan Caicedo. Carlos Rincon. Santiago Guitierrez. Jhon Diaz. ÍNDICE Introducción. Presentación de la variable. Adecuación de la serie. Modelo SARIMA Analisis de resultados. Conclusiones INTRODUCCIÓN Como parte de un análisis exhaustivo del mercado automotriz del Reino Unido, se ha recopilado una serie tempo...
3561 sym Python (590 sym/4 pcs) 6 img 2 tbl
Code Along 6
Introduction Question 2 Variation Visualizing distributions diamonds %>% ggplot(aes(x = cut)) + geom_bar() diamonds %>% ggplot(mapping = aes(x = carat)) + geom_histogram(binwidth = 0.5) diamonds %>% filter(carat < 3) %>% ggplot(aes(x = carat)) + geom_histogram(binwidth = 0.5) diamonds %>% ggplot(aes(x...
887 sym R (2313 sym/25 pcs) 16 img
Code Along 5 Ch5
Import data flights ## # A tibble: 336,776 × 19 ## year month day dep_time sched_dep_time dep_delay arr_time sched_arr_time ## <int> <int> <int> <int> <int> <dbl> <int> <int> ## 1 2013 1 1 517 515 2 830 819 ## 2 2013 1 1 533 529 ...
512 sym Python (20200 sym/51 pcs) 1 img
Apply 5 test run
Import data Apply the following dplyr verbs to your data rank, discipline, yrs.since.phd, yrs.service, sex, salary Filter rows Arrange rows Select columns Add columns Summarize by groups...
211 sym
Code Along 5 ch4
Coding basics R as a calculator 1000 / 10 ## [1] 100 x <- 1000 / 10 # x assignment symbol What’s in a name? Calling functions Use of TAB seq(from = 1, to = 10, by = 1) ## [1] 1 2 3 4 5 6 7 8 9 10 continuation character, + #seq(from = 1, to 10) Printing to screen y <- seq(from = 1, to = 10) y ## [1] 1 2 3 4 5 6 7 8 9 1...
170 sym Python (193 sym/8 pcs)