This is a sample distill article post using RMarkdown
I will be looking at the dataset nycflights13. First, I will show a table of the first 5 rows of data on airports, and then I will provide some descriptive statistics about the altitudes of the airports, with the code shown alongside. Because the distribution of altitudes is highly skewed, the median and interquartile range are far more useful than the mean and standard deviation, though I have included both.
| faa | name | lat | lon | alt | tz | dst | tzone |
|---|---|---|---|---|---|---|---|
| 04G | Lansdowne Airport | 41.13047 | -80.61958 | 1044 | -5 | A | America/New_York |
| 06A | Moton Field Municipal Airport | 32.46057 | -85.68003 | 264 | -6 | A | America/Chicago |
| 06C | Schaumburg Regional | 41.98934 | -88.10124 | 801 | -6 | A | America/Chicago |
| 06N | Randall Airport | 41.43191 | -74.39156 | 523 | -5 | A | America/New_York |
| 09J | Jekyll Island Airport | 31.07447 | -81.42778 | 11 | -5 | A | America/New_York |
nycflights13::airports %>% summarise(
mean_alt=mean(alt),
median_alt=median(alt),
iqr_alt=IQR(alt),
sd_alt=sd(alt)
)
# A tibble: 1 × 4
mean_alt median_alt iqr_alt sd_alt
<dbl> <dbl> <dbl> <dbl>
1 1001. 473 992. 1524.Text and figures are licensed under Creative Commons Attribution CC BY-NC 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
Mendum (2022, June 7). Data Analytics and Computational Social Science: Homework 1. Retrieved from https://github.com/DACSS/dacss_course_website/posts/httprpubscomamendum911241/
BibTeX citation
@misc{mendum2022homework,
author = {Mendum, Annabel},
title = {Data Analytics and Computational Social Science: Homework 1},
url = {https://github.com/DACSS/dacss_course_website/posts/httprpubscomamendum911241/},
year = {2022}
}