DACSS 601 August 2021: Saulo's Homeworks

Saulo DePaula

Homework Two

eggs <- read.csv(file="../../_data/eggs_tidy.csv")
head(eggs)

     month year large_half_dozen large_dozen extra_large_half_dozen
1  January 2004            126.0     230.000                  132.0
2 February 2004            128.5     226.250                  134.5
3    March 2004            131.0     225.000                  137.0
4    April 2004            131.0     225.000                  137.0
5      May 2004            131.0     225.000                  137.0
6     June 2004            133.5     231.375                  137.0
  extra_large_dozen
1             230.0
2             230.0
3             230.0
4             234.5
5             236.0
6             241.0

Homework Three

Select

library(tidyverse)
select(eggs, "month")

        month
1     January
2    February
3       March
4       April
5         May
6        June
7        July
8      August
9   September
10    October
11   November
12   December
13    January
14   February
15      March
16      April
17        May
18       June
19       July
20     August
21  September
22    October
23   November
24   December
25    January
26   February
27      March
28      April
29        May
30       June
31       July
32     August
33  September
34    October
35   November
36   December
37    January
38   February
39      March
40      April
41        May
42       June
43       July
44     August
45  September
46    October
47   November
48   December
49    January
50   February
51      March
52      April
53        May
54       June
55       July
56     August
57  September
58    October
59   November
60   December
61    January
62   February
63      March
64      April
65        May
66       June
67       July
68     August
69  September
70    October
71   November
72   December
73    January
74   February
75      March
76      April
77        May
78       June
79       July
80     August
81  September
82    October
83   November
84   December
85    January
86   February
87      March
88      April
89        May
90       June
91       July
92     August
93  September
94    October
95   November
96   December
97    January
98   February
99      March
100     April
101       May
102      June
103      July
104    August
105 September
106   October
107  November
108  December
109   January
110  February
111     March
112     April
113       May
114      June
115      July
116    August
117 September
118   October
119  November
120  December

Filter

library(tidyverse)
filter(eggs, `month` == "January")

     month year large_half_dozen large_dozen extra_large_half_dozen
1  January 2004            126.0       230.0                 132.00
2  January 2005            128.5       233.5                 135.50
3  January 2006            128.5       233.5                 135.50
4  January 2007            128.5       233.5                 135.50
5  January 2008            132.0       237.0                 139.00
6  January 2009            174.5       277.5                 185.50
7  January 2010            174.5       271.5                 185.50
8  January 2011            174.5       267.5                 185.50
9  January 2012            174.5       267.5                 185.50
10 January 2013            178.0       267.5                 188.13
   extra_large_dozen
1              230.0
2              241.0
3              241.0
4              241.5
5              245.0
6              285.5
7              285.5
8              285.5
9              285.5
10             290.0

Arrange

library(tidyverse)
filter(eggs, `large_half_dozen` > 130) %>%
  arrange(`large_half_dozen`)

       month year large_half_dozen large_dozen extra_large_half_dozen
1      March 2004          131.000     225.000                137.000
2      April 2004          131.000     225.000                137.000
3        May 2004          131.000     225.000                137.000
4   February 2007          131.125     236.125                138.125
5      March 2007          132.000     237.000                139.000
6      April 2007          132.000     237.000                139.000
7        May 2007          132.000     237.000                139.000
8       June 2007          132.000     237.000                139.000
9       July 2007          132.000     237.000                139.000
10    August 2007          132.000     237.000                139.000
11 September 2007          132.000     237.000                139.000
12   October 2007          132.000     237.000                139.000
13  November 2007          132.000     237.000                139.000
14  December 2007          132.000     237.000                139.000
15   January 2008          132.000     237.000                139.000
16  February 2008          132.000     237.000                139.000
17     March 2008          132.000     237.000                139.000
18     April 2008          132.000     237.000                139.000
19       May 2008          132.000     237.000                139.000
20      June 2004          133.500     231.375                137.000
21      July 2004          133.500     233.500                137.000
22    August 2004          133.500     233.500                137.000
23       May 2012          173.250     267.500                185.500
24      June 2012          173.250     267.500                185.500
25      July 2012          173.250     267.500                185.500
26    August 2012          173.250     267.500                185.500
27 September 2012          173.250     267.500                185.500
28   October 2012          173.250     267.500                185.500
29      June 2008          174.500     277.500                185.500
30      July 2008          174.500     277.500                185.500
31    August 2008          174.500     277.500                185.500
32 September 2008          174.500     277.500                185.500
33   October 2008          174.500     277.500                185.500
34  November 2008          174.500     277.500                185.500
35  December 2008          174.500     277.500                185.500
36   January 2009          174.500     277.500                185.500
37  February 2009          174.500     277.500                185.500
38     March 2009          174.500     277.500                185.500
39     April 2009          174.500     277.500                185.500
40       May 2009          174.500     277.500                185.500
41      June 2009          174.500     277.500                185.500
42      July 2009          174.500     277.500                185.500
43    August 2009          174.500     271.500                185.500
44 September 2009          174.500     271.500                185.500
45   October 2009          174.500     271.500                185.500
46  November 2009          174.500     271.500                185.500
47  December 2009          174.500     271.500                185.500
48   January 2010          174.500     271.500                185.500
49  February 2010          174.500     271.500                185.500
50     March 2010          174.500     268.000                185.500
51     April 2010          174.500     268.000                185.500
52       May 2010          174.500     268.000                185.500
53      June 2010          174.500     268.000                185.500
54      July 2010          174.500     268.000                185.500
55    August 2010          174.500     268.000                185.500
56 September 2010          174.500     268.000                185.500
57   October 2010          174.500     267.500                185.500
58  November 2010          174.500     267.500                185.500
59  December 2010          174.500     267.500                185.500
60   January 2011          174.500     267.500                185.500
61  February 2011          174.500     267.500                185.500
62     March 2011          174.500     267.500                185.500
63     April 2011          174.500     267.500                185.500
64       May 2011          174.500     267.500                185.500
65      June 2011          174.500     270.000                185.500
66      July 2011          174.500     270.000                185.500
67    August 2011          174.500     270.000                185.500
68 September 2011          174.500     270.000                185.500
69   October 2011          174.500     270.000                185.500
70  November 2011          174.500     270.000                185.500
71  December 2011          174.500     270.000                185.500
72   January 2012          174.500     267.500                185.500
73  February 2012          174.500     267.500                185.500
74     March 2012          174.500     267.500                185.500
75     April 2012          174.500     267.500                185.500
76  November 2012          178.000     267.500                188.130
77  December 2012          178.000     267.500                188.130
78   January 2013          178.000     267.500                188.130
79  February 2013          178.000     267.500                188.130
80     March 2013          178.000     267.500                188.130
81     April 2013          178.000     267.500                188.130
82       May 2013          178.000     267.500                188.130
83      June 2013          178.000     267.500                188.130
84      July 2013          178.000     267.500                188.130
85    August 2013          178.000     267.500                188.130
86 September 2013          178.000     267.500                188.130
87   October 2013          178.000     267.500                188.130
88  November 2013          178.000     267.500                188.130
89  December 2013          178.000     267.500                188.130
   extra_large_dozen
1            230.000
2            234.500
3            236.000
4            244.125
5            245.000
6            245.000
7            245.000
8            245.000
9            245.000
10           245.000
11           245.000
12           245.000
13           245.000
14           245.000
15           245.000
16           245.000
17           245.000
18           245.000
19           245.000
20           241.000
21           241.000
22           241.000
23           288.500
24           288.500
25           288.500
26           288.500
27           288.500
28           288.500
29           285.500
30           285.500
31           285.500
32           285.500
33           285.500
34           285.500
35           285.500
36           285.500
37           285.500
38           285.500
39           285.500
40           285.500
41           285.500
42           285.500
43           285.500
44           285.500
45           285.500
46           285.500
47           285.500
48           285.500
49           285.500
50           285.500
51           285.500
52           285.500
53           285.500
54           285.500
55           285.500
56           285.500
57           285.500
58           285.500
59           285.500
60           285.500
61           285.500
62           285.500
63           285.500
64           285.500
65           285.500
66           285.500
67           285.500
68           285.500
69           285.500
70           285.500
71           285.500
72           285.500
73           288.500
74           288.500
75           288.500
76           290.000
77           290.000
78           290.000
79           290.000
80           290.000
81           290.000
82           290.000
83           290.000
84           290.000
85           290.000
86           290.000
87           290.000
88           290.000
89           290.000

Summarize

library(tidyverse)
summarize(eggs, mean(`large_half_dozen`))

  mean(large_half_dozen)
1               155.1656

Homework Four

Egg Data for Large Half Dozens

The following is a brief set of summary statistics from the eggs_tidy dataset, specifically looking at the price (in cents) per Large Half Dozen Eggs from January 2004 to December 2013. I have provided the mean, median, min, and max for this variable, along with a basic visualization. No data cleaning or recoding was necessary, given the provided dataset was sufficiently clean.

library(tidyverse)
summarize(eggs, mean(`large_half_dozen`))

  mean(large_half_dozen)
1               155.1656

library(tidyverse)
summarize(eggs, median(`large_half_dozen`))

  median(large_half_dozen)
1                    174.5

library(tidyverse)
summarize(eggs, min(`large_half_dozen`))

  min(large_half_dozen)
1                   126

library(tidyverse)
summarize(eggs, max(`large_half_dozen`))

  max(large_half_dozen)
1                   178

library(tidyverse)
ggplot(eggs, aes(`large_half_dozen`)) + geom_histogram() +
  theme_minimal() +
  labs(title = "Large Half Dozen Egg Prices (in cents) | Jan. 2004 to Dec. 2013", y = "Count of Occurances", x= "Count of Eggs")

Egg Data for Large Dozens

The following is a brief set of summary statistics from the eggs_tidy dataset, specifically looking at the price (in cents) per Large Dozen Eggs from January 2004 to December 2013. I have provided the mean, median, min, and max for this variable, along with a basic visualization. No data cleaning or recoding was necessary, given the provided dataset was sufficiently clean.

library(tidyverse)
summarize(eggs, mean(`large_dozen`))

  mean(large_dozen)
1          254.1979

library(tidyverse)
summarize(eggs, median(`large_dozen`))

  median(large_dozen)
1               267.5

library(tidyverse)
summarize(eggs, min(`large_dozen`))

  min(large_dozen)
1              225

library(tidyverse)
summarize(eggs, max(`large_dozen`))

  max(large_dozen)
1            277.5

library(tidyverse)
ggplot(eggs, aes(`large_dozen`)) + geom_histogram() +
  theme_minimal() +
  labs(title = "Large Dozen Eggs (in cents) | Jan. 2004 to Dec. 2013", y = "Count of Occurances", x= "Count of Eggs")

Homework Five

library(tidyverse)
ggplot(eggs, aes(x=`year`, y=`large_half_dozen`, col=as_factor(`extra_large_half_dozen`))) + 
  geom_point()

library(tidyverse)
ggplot(eggs, aes(x=`year`, y=`large_dozen`, col=as_factor(`extra_large_dozen`))) + 
  geom_point()

What these visualizations represent: There is an equal relationship between the prices of Large Half Dozen and Extra Large Half Dozen eggs, as well as between the prices of Large Dozen and Extra Large Dozen eggs. Essentially, it appears they go up at the same rate over time; if the Large variation goes up, so too does the Extra Large variation.
Why I chose this visualization approach, and what alternative approaches I considered but decided not to pursue: These visualizations are very straightforward and clearly demonstrate the relationships between the Large and Extra Large egg variations. I attempted a histogram, but received a very lengthy error, which led me to feel content with the geom_point() option.
What I wished, if anything, I could have executed but found limited capability to do: It would have been nice to produce a larger visual that included month and year, to spread the points out even further, but I was unsure of how to do that. I also wish there were more data to utilize, such as the price of chickens, which would be interesting to compare to the price of eggs.

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Saulo’s Homeworks