Project

Incarcare librarii

Nu uitati de mesajul suppressPackageStartupMessages({})

suppressPackageStartupMessages({library(statnet)
  library(tidyverse)
  library(readr)
  library(igraph)
  library(network)
  library(sna)
  library(dplyr) 
  library(Hmisc)})

unable to reach CRAN

1. Import data

Sfaturi:

• import baza de date

• print- vizualizare baza de date NU SE FOLOSESTE VIEW

data <- read_csv("data.csv")
print(data)

# A tibble: 203 × 98
   CSV1_0 CSV1_1 CSV1_2 CSV1_3 CSV1_4 CSV1_5  CSV2  CSV3 FSV1_0 FSV1_1 FSV1_2
    <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>
 1      1      1      0      0      0      0     4     3      1      1      0
 2      1      1      1      1      1      0     5     5      1      0      0
 3      1      0      1      1      1      0     4     1      1      0      1
 4      1      1      0      1      0      0     3     2      1      0      0
 5      1      1      0      1      1      0     4     2      1      0      0
 6      1      1      1      1      1      1     4     2      1      1      0
 7      1      0      1      1      0      0     2     1      1      0      0
 8      0      0      0      0      0      1     4     3      0      0      0
 9      1      1      0      0      1      0     4     1      1      0      0
10      1      1      1      1      0      0     3     1      1      0      1
# ℹ 193 more rows
# ℹ 87 more variables: FSV1_3 <dbl>, FSV1_4 <dbl>, FSV2 <dbl>, FSV3 <dbl>,
#   FSV4_0 <dbl>, FSV4_1 <dbl>, FSV4_2 <dbl>, FSV4_3 <dbl>, FSV4_4 <dbl>,
#   FSV4_5 <dbl>, FSV4_6 <dbl>, FSV4_7 <dbl>, FSV4_8 <dbl>, ASV1 <dbl>,
#   ASV2_0 <dbl>, ASV2_1 <dbl>, ASV2_2 <dbl>, ASV2_3 <dbl>, ASV2_4 <dbl>,
#   ASV2_5 <dbl>, OSVA1 <dbl>, OSVA2 <dbl>, OSVA3 <dbl>, OSVA4 <dbl>,
#   OSVA5 <dbl>, OSVN1 <dbl>, OSVN2 <dbl>, OSVN3 <dbl>, OSVN4 <dbl>, …

Analiza descriptiva / univariata

Va jucati cu diferitele tabele propuse de dna Puiu plus tabele de frecventa si summary.

library(summarytools)- nu uitati sa incarcati aceasta librarie la inceput

##frequency tables: summarytools::freq(data$CSV1_0)

summary(data$CSV1_0)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 0.0000  1.0000  1.0000  0.9458  1.0000  1.0000 

## Min.   1st Qu. Median   Mean   3rd Qu.  Max. 
##0.0000  0.0000  1.0000  0.5578  1.0000  1.0000 

tabele

date_multiplu <- data%>%
  select(CSV1_0, CSV1_1, CSV1_2, CSV1_3, CSV1_4, CSV1_5) %>%
  summarise(across(everything(), ~sum(. == 1, na.rm = TRUE))) %>%
  pivot_longer(cols = everything(), names_to = "Opțiune", values_to = "Frecvență") %>%
  mutate(Opțiune = reorder(Opțiune, Frecvență))

top_spatii <- data %>%
  select(CSV1_0, CSV1_1, CSV1_2, CSV1_3, CSV1_4, CSV1_5) %>%
  summarise(across(everything(), ~sum(. == 1, na.rm = TRUE))) %>%
  pivot_longer(cols = everything(), names_to = "Varianta", values_to = "Voturi") %>%
  mutate(Denumire = case_when(
    Varianta == "CSV1_0" ~ "Parcuri amenajate",
    Varianta == "CSV1_1" ~ "Grădini dintre blocuri",
    Varianta == "CSV1_2" ~ "Păduri",
    Varianta == "CSV1_3" ~ "Parcuri naturale",
    Varianta == "CSV1_4" ~ "Alveole",
    Varianta == "CSV1_5" ~ "Altele"
  )) %>%
  mutate(Denumire = reorder(Denumire, Voturi)) 

ggplot(top_spatii, aes(x = Voturi, y = Denumire, fill = Voturi)) +
  geom_col() +
  geom_text(aes(label = Voturi), hjust = -0.2, size = 4, fontface = "bold") +
  scale_fill_gradient(low = "#A2CD5A", high = "#458B00") +
  labs(title = "Ce reprezintă un spațiu verde pentru bucureșteni?",
       x = "Număr de alegeri", y = "Variante") +
  theme_minimal() +
  theme(legend.position = "none")

Analiza bivariata

Aceeasi sintaxa se foloseste si pt Pearson si Spearman, la method trebuie schimbat cu testul corespunzator.

cor.test(data\(d1,data\)d23, method = “pearson”, exact = F)

Testare de ipoteze

H0- ipoteza nula, este considerata adevarata pana la proba contrarie

Ha- ipoteza alternativa

respingem H0 daca p<=0,05

acceptam H0 daca p>0,05