In [1]:

    

library(dplyr)


    

    




Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

In [2]:

    

library(ggplot2)


    

In [3]:

    

head(economics)


    

    
Out[3]:





date
pce
pop
psavert
uempmed
unemploy

	
1
1967-06-30
507.8
198712
9.8
4.5
2944
	
2
1967-07-31
510.9
198911
9.8
4.7
2945
	
3
1967-08-31
516.7
199113
9
4.6
2958
	
4
1967-09-30
513.3
199311
9.8
4.9
3143
	
5
1967-10-31
518.5
199498
9.7
4.7
3066
	
6
1967-11-30
526.2
199657
9.4
4.8
3018

In [4]:

    

a <- ggplot(data = economics, aes(x = date, y = unemploy))
a <- a + geom_line()
a


    

In [5]:

    

a <- ggplot(data = economics, aes(x = date, y = unemploy))
a <- a + geom_line()
a <- a + geom_smooth(method = "loess")
a


    

In [6]:

    

df <- data.frame(birth_state=c("Illinois", "Arizona", NA),
                 data_scientist=c("Kevin", "Matt", "Jonathan"))


    

In [7]:

    

df


    

    
Out[7]:





birth_state
data_scientist

	
1
Illinois
Kevin
	
2
Arizona
Matt
	
3
NA
Jonathan

In [8]:

    

df$birth_state == "Arizona"


    

    
Out[8]:





	
FALSE
	
TRUE
	
NA

In [9]:

    

just_Arizona <- df[df$birth_state=="Arizona",]


    

In [10]:

    

just_Arizona


    

    
Out[10]:





birth_state
data_scientist

	
2
Arizona
Matt
	
NA
NA
NA

In [11]:

    

really_just_Arizona <- df[which(df$birth_state=="Arizona"),]


    

In [12]:

    

really_just_Arizona


    

    
Out[12]:





birth_state
data_scientist

	
2
Arizona
Matt

In [13]:

    

a <- -5


    

In [14]:

    

a


    

    
Out[14]:




-5

In [15]:

    

a<-5


    

In [16]:

    

a


    

    
Out[16]:




5

In [ ]: