September 2018
Beginner to intermediate
140 pages
2h 52m
English
Content preview from Applied Data Visualization with R and ggplot2
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Analyzing Different Datasets
We all love to talk about the weather. So, let's work with some weather-related datasets. The datasets contain approximately five years' worth of high-temporal resolution (hourly measurements) data for various weather attributes, such as temperature, humidity, air pressure, and so on. We'll analyze and compare the humidity and weather datasets.
Read more about weather datasets at: https://www.kaggle.com/selfishgene/historical-hourly-weather-data.
Let's begin by implementing the following steps:
- Load the humidity dataset by using the following command:
df_hum <- read.csv("data/historical-hourly-weather-data/humidity.csv")
- Load the weather description dataset by using the following command:
df_desc <- read.csv("data/historical-hourly-weather-data/weather_description.csv") ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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