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# Untitled

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1. # Some vectors of numbers
2. percent_change  <- c(4, -1.91, 3.00, -5.002)
3. income <-  c(72.19, 1030.18, 10291.93, 1189192.18)
4. p_values <- c(0.12, 0.98, 0.0000191, 0.00000000002)
5.
6. # Format c(0.0011, 0.011, 1) with digits = 1
7. format(c(0.0011, 0.011, 1), digits =1)
8.
9. # Format c(1.0011, 2.011, 1) with digits = 1
10. format(c(1.0011, 2.011, 1), digits=1)
11.
12. # Format percent_change to one place after the decimal point
13. format(percent_change, digits=2)
14.
15. # Format income to whole numbers
16. format(income, digits=2)
17.
18. # Format p_values in fixed format
19. format(p_values, scientific=FALSE)
20.
21. ## 2
22. formatted_income <- format(income, digits = 2)
23.
24. # Print formatted_income
25. print(formatted_income)
26.
27. # Call writeLines() on the formatted income
28. writeLines(formatted_income)
29.
30. # Define trimmed_income
31. trimmed_income <- format(income, digits=2, trim=TRUE)
32.
33. # Call writeLines() on the trimmed_income
34. writeLines(trimmed_income)
35.
36. # Define pretty_income
37. pretty_income <- format(income, digits = 2, big.mark=",")
38.
39. # Call writeLines() on the pretty_income
40. writeLines(pretty_income)
41.
42.
43. #Rather than a scientific argument, formatC() has a format argument that takes a code representing the required format. The most useful are:
44.
45. #"f" for fixed,
46. #"e" for scientific, and
47. #"g" for fixed unless scientific saves space
48.
49. # From the format() exercise
50. x <- c(0.0011, 0.011, 1)
51. y <- c(1.0011, 2.011, 1)
52.
53. # formatC() on x with format = "f", digits = 1
54. formatC(x, format='f', digits=1)
55.
56. # formatC() on y with format = "f", digits = 1
57. formatC(y, format ="f", digits=1)
58.
59. # Format percent_change to one place after the decimal point
60. formatC(percent_change, format='f',digits=1)
61.
62. # percent_change with flag = "+"
63. formatC(percent_change, format='f',digits=1, flag="+")
64.
65. # Format p_values using format = "g" and digits = 2
66. formatC(p_values, format="g", digits=2)
67.
68. # Add \$ to pretty_income
69. paste("\$",pretty_income,sep='' )
70.
71. # Add % to pretty_percent
72. paste(pretty_percent, "%", sep="")
73.
74. # Create vector with elements like 2010: +4.0%`
75. year_percent <- paste(years, ': ', pretty_percent, "%", sep="")
76.
77. # Collapse all years into single string
78. paste(year_percent, collapse=', ')
79.
80. ## 3
81. # Define the names vector
82. income_names <- c("Year 0", "Year 1", "Year 2", "Project Lifetime")
83.
84. # Create pretty_income
85. pretty_income <- format(income, digits=2, big.mark=",")
86.
87. # Create dollar_income
88. dollar_income <- paste("\$", pretty_income, sep="")
89.
90. # Create formatted_names
91. formatted_names <- format(income_names, justify="right")
92.
93. # Create rows
94. rows<-paste(formatted_names, dollar_income, sep="   ")
95.
96. # Write rows
97. writeLines(rows)
98.
99. ## 3
100. # Randomly sample 3 toppings
101. my_toppings <- sample(toppings, size = 3)
102.
103. # Print my_toppings
104. my_toppings
105.
106. # Paste "and " to last element: my_toppings_and
107. my_toppings_and <- paste(c("", "", "and "), my_toppings, sep = "")
108.
109. # Collapse with comma space: these_toppings
110. these_toppings <- paste(my_toppings_and, collapse = ", ")
111.
112. # Add rest of sentence: my_order
113. my_order <- paste("I want to order a pizza with ", these_toppings, ".", sep = "")
114.
115. # Order pizza with writeLines()
116. writeLines(my_order)
117.
118. ## stringr
119. library(stringr)
120.
121. my_toppings <- c("cheese", NA, NA)
122. my_toppings_and <- paste(c("", "", "and "), my_toppings, sep = "")
123.
124. # Print my_toppings_and
125. print(my_toppings_and)
126.
127. # Use str_c() instead of paste(): my_toppings_str
128. my_toppings_str <- str_c(c("", "", "and "), my_toppings)
129.
130. # Print my_toppings_str
131. print(my_toppings_str)
132.
133. # paste() my_toppings_and with collapse = ", "
134. paste(my_toppings_and, collapse = ", ")
135.
136. # str_c() my_toppings_str with collapse = ", "
137. str_c(my_toppings_str, collapse = ", ")
138.
139. ##
140. library(stringr)
141. library(babynames)
142. library(dplyr)
143.
144. # Extracting vectors for boys' and girls' names
145. babynames_2014 <- filter(babynames, year == 2014)
146. boy_names <- filter(babynames_2014, sex == "M")\$name
147. girl_names <- filter(babynames_2014, sex == "F")\$name
148.
149. # Take a look at a few boy_names
151.
152. # Find the length of all boy_names
153. boy_length <- str_length(boy_names)
154.
155. # Take a look at a few lengths
157.
158. # Find the length of all girl_names
159. girl_length <- str_length(girl_names)
160.
161. # Find the difference in mean length
162. mean(girl_length) - mean(boy_length)
163.
164. # Confirm str_length() works with factors
166.
167. #####
168. # Extract first letter from boy_names
169. boy_first_letter <- str_sub(boy_names, 1,1)
170.
171. # Tabulate occurrences of boy_first_letter
172. table(boy_first_letter)
173.
174. # Extract the last letter in boy_names, then tabulate
175. boy_last_letter <- str_sub(boy_names, -1,-1)
176. table(boy_last_letter)
177.
178. # Extract the first letter in girl_names, then tabulate
179. girl_first_letter <- str_sub(girl_names, 1,1)
180. table(girl_first_letter)
181.
182. # Extract the last letter in girl_names, then tabulate
183. girl_last_letter <- str_sub(girl_names, -1,-1)
184. table(girl_last_letter)
185.
186.
187. ####
188. # Look for pattern "zz" in boy_names
189. contains_zz <- str_detect(boy_names, pattern="zz")
190.
191. # Examine str() of contains_zz
192. str(contains_zz)
193.
194. # How many names contain "zz"?
195. sum(contains_zz)
196.
197. # Which names contain "zz"?
198. boy_names[contains_zz]
199.
200. # Which rows in boy_df have names that contain "zz"?
201. boy_df[contains_zz,]
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