Untitled

---
title: "Ramki Danych - praca domowa"
output: 
  pdf_document:
    toc: yes
  rmd_document:
    toc: yes
author: "Zuzanna Piszczatowska"
date: "2025-04-05"
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
#zad1
```{r}
female_names <- read.csv("female_names.csv", stringsAsFactors = FALSE, header = TRUE, sep =";")
colnames(female_names)
```

#zad2
```{r}
names_2013 <- female_names[female_names$"year" == 2013, ]
```
#zad3
```{r}
max <- 0
most_popular_name <- ""
for(i in 1:nrow(names_2013)) {
current <-names_2013$prop[i] 
name <- names_2013$name[i]
if(current > max){
max<-current
most_popular_name <- name}}
answer <- paste("Najpopularniejsze imię w 2013 roku to", most_popular_name,".")
answer
```

#zad4
```{r}
most_popular_in_year <- function(year)
{
all_years <- female_names[female_names$year == year, ]
max_prop <- which.max(all_years$prop)
  return(all_years$name[max_prop])
}
```
#zad5
```{r}
popular_1994 <- most_popular_in_year(1994)
answer <- paste("Najpopularniejsze imię w 1994 to", popular_1994,".")
answer
```


#zad6
```{r}
number_in_million <- function(name, year)
{
name_and_year <- female_names[female_names$name == name & female_names$year == year, ]
  return(name_and_year$prop*1000000)
}

```


#zad7
```{r}
Laura_in_1995 <- number_in_million("Laura", 1995)
answer <- paste("W 1995 imię Laura otrzymało", Laura_in_1995, "dzieci.")
answer
```
#zad8
```{r}
Susan_in_2002 <- number_in_million("Susan", 2002)
answer <- paste("W roku mojego urodzenia moje imię otrzymało", Susan_in_2002, "dzieci.")
answer

```
#zad9
```{r}
number_in_million("Victoria", 2002)
number_in_million("Caroline", 2002)
number_in_million("Julia", 2002)
```
"W porównaniu do osób z innymi imionami, które są bardziej popularne (np. Victoria, Caroline, Julia), zidentyfikowanie mnie nie wydaje się takie trudne."