#Overview

The article I choose is about the temperature across the United States in a 12-months period from July 2014 through June 2015. It provided graphics about the range of temperature of different U.S. cities, including Los Angeles, Chicago, New York, Houston, etc. I select the dataset about NYC.

Article

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   3.5.2     ✔ tibble    3.3.0
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.1.0     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
url <- "https://raw.githubusercontent.com/fivethirtyeight/data/master/us-weather-history/KNYC.csv"
df <- read.csv(url)
df_new <- df %>%
  select(date, 
         mean_temp = actual_mean_temp, 
         min_temp = actual_min_temp, 
         max_temp = actual_max_temp, 
         record_precipitation)
head(df_new)
##       date mean_temp min_temp max_temp record_precipitation
## 1 2014-7-1        81       72       89                 2.17
## 2 2014-7-2        82       72       91                 1.79
## 3 2014-7-3        78       69       87                 2.80
## 4 2014-7-4        70       65       74                 1.76
## 5 2014-7-5        72       63       81                 3.07
## 6 2014-7-6        75       66       84                 1.97

#Conclusion

The article stated that climate change affected cities in United States differently. In the future assignment I may also include more datasets about the other cities. I modified some column names and removed some columns because they are too long or redundant.