March 2018
Intermediate to advanced
528 pages
13h 2m
Portuguese (Portugal, Brazil)
Content preview from R para Data Science
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Resumos Agrupados com summarize() | 63
Por exemplo, vamos observar os aviões (identificados pelo número de cauda) que têm
os maiores atrasos médios:
delays <- not_cancelled %>%
group_by( tailnum ) %>%
summarize(
delay = mean( arr_delay)
)
ggplo
t( data = delays, mapping = aes( x = delay))
+
geom_freqpoly
( binwidth
= 10
)
Nossa, alguns aviões têm um atraso médio de 5 horas (300 minutos)!
A história é, na verdade, um pouquinho diferente. Podemos obter mais insight se de-
senharmos um diagrama de dispersão do número de voos versus atraso médio:
delays <- not_cancelled %>%
group_by( tailnum ) %>%
summarize(
delay = mean( arr_delay, na.rm = TRUE ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.