1 a 00 a use the read.csv(l) function to read in the Wine. csv fite. Nase it wine and don't forget to use the stringsit argunent. zwtrze Note that the Code Grade virtual machine (conputer) already has the Wine.csv file in its working directory. matan When subeitting to code grade, use a read.csv() statement that assumes the file is already in the working directory. anzafs Do not submit code with setwd() or that has a path (for example: Users/first. last/Desktop) in it. vine read, csv("Wine.csv", strings=t) f. 01a = How many observations (rows) are available to you? Use the nrow() function. nrow (288992) A 026 z How tany variables (columns) are collected on each rated wine? Use the ncol() function. 9 ncol (13) 10 zaruat it is ieportant to find the exact spellings of colunn nases and entries within columns in the wine datafrane. 11 F 02a \# Use the nanes() or str(l) function on the wine datafrane to view the exact spellings of the colunn nanes. 12 nanes (Wine) 13 : Q2b * Use the sumary(l) function on the taster twitter handle coluan to view the exact speltings of the tasters' twitter handles. 14. earratz You will use this-strategy of "looking" in a colum to get exact sepllings to answer questions on this quiz. 16 is interar It is inportant to know whether there are missing values (NAS) in your data. 17 mourrar since Mas need to be addressed for certain functions to work correctly. 18 F 03a = Use the siall and is. nal) functions to find the nunber of nissing values in the wine datafrane. 28=036= Use the sue() and is.na() functions to count the number of missing vatues in the points column. 22 : 03c Use the sum() and is. na() functions to count the nusber of nissing vatues in the price cotumn. 24 : oad a Use the sun(i) and is. naf) functions to count the nueber of observations that have a price. 25. orereez linti since the I means "not", putting an t in tront of is.na() counts the non-eissing vatues. - O4a o use the mean() function to calculate the average points for the wines in the dataset. - 04b: Use the eeant) function to calculate the average price for the wines in the dataset, - 050 = Use the neanin function to cateulate the average points for the Mapa 5onons sub-region. wases yoar code should be a single tine and witl use the square brackets for subsetting.. - OSb : use the neanil function to colculate the average price for the Napa Sonona sub-regionusing a single line of code. - of * Nou we'th practice our counting skttls again. 3r vecess the rating scate beipg used by these tasters orignally had 91 as the highest possible score. 24 * Q3d * Use the sum(l) and is.na(l functions to count the number of observations that have a price. Frreffl Hint: Since the I means "not", putting an 1 in front of is.na() counts the non-missing values. 7. 04a Use the mean() function to calculate the average points for the wines in the dataset. * 046 * Use the mean() function to calculate the average price for the wines in the dataset. * Q5a \& Use the meani) function to calculate the average points for the Napa Sonoma sub-region. 32. Your code should be a single line and will use the square brackets for subsetting.. " 05b of Use the meanl) function to calculate the average price for the Napa Sonona sub-regionusing a single line of code. a 06 \& Now we'tl practice our counting skitls again. 37 Hasanan The rating scale being used by these tasters orignally had 91 as the highest possible score 38 astart and now goes to 100 for exceedingly delicious wines. 39 usasey use the sun() function on a togical vector that checks for whether points are greater than 91 or not 40. Intant to count the number of wine ratings with nore than 91 points. 42 : 07a * Now we'll practice subsetting on more than one criteria. 43 ancarer Use the mean(i) function to conpute the average points for wines 44 samenn that are chardonnay and fron the Napa Sonoma sub-region. 45 : 070 a More practice subsetting on more than one criteria. 47 asantar use the mean() function to conpute the ayerage price for wines that are 48 matam esther chardonnay or are tron the finger lakes sub-region, 50:08= use the median(i) tunction to find the nedian price for 51 sasaria a Cabernet Sauvignon that is rated higher than 91 points. 1 a 00 a use the read.csv(l) function to read in the Wine. csv fite. Nase it wine and don't forget to use the stringsit argunent. zwtrze Note that the Code Grade virtual machine (conputer) already has the Wine.csv file in its working directory. matan When subeitting to code grade, use a read.csv() statement that assumes the file is already in the working directory. anzafs Do not submit code with setwd() or that has a path (for example: Users/first. last/Desktop) in it. vine read, csv("Wine.csv", strings=t) f. 01a = How many observations (rows) are available to you? Use the nrow() function. nrow (288992) A 026 z How tany variables (columns) are collected on each rated wine? Use the ncol() function. 9 ncol (13) 10 zaruat it is ieportant to find the exact spellings of colunn nases and entries within columns in the wine datafrane. 11 F 02a \# Use the nanes() or str(l) function on the wine datafrane to view the exact spellings of the colunn nanes. 12 nanes (Wine) 13 : Q2b * Use the sumary(l) function on the taster twitter handle coluan to view the exact speltings of the tasters' twitter handles. 14. earratz You will use this-strategy of "looking" in a colum to get exact sepllings to answer questions on this quiz. 16 is interar It is inportant to know whether there are missing values (NAS) in your data. 17 mourrar since Mas need to be addressed for certain functions to work correctly. 18 F 03a = Use the siall and is. nal) functions to find the nunber of nissing values in the wine datafrane. 28=036= Use the sue() and is.na() functions to count the number of missing vatues in the points column. 22 : 03c Use the sum() and is. na() functions to count the nusber of nissing vatues in the price cotumn. 24 : oad a Use the sun(i) and is. naf) functions to count the nueber of observations that have a price. 25. orereez linti since the I means "not", putting an t in tront of is.na() counts the non-eissing vatues. - O4a o use the mean() function to calculate the average points for the wines in the dataset. - 04b: Use the eeant) function to calculate the average price for the wines in the dataset, - 050 = Use the neanin function to cateulate the average points for the Mapa 5onons sub-region. wases yoar code should be a single tine and witl use the square brackets for subsetting.. - OSb : use the neanil function to colculate the average price for the Napa Sonona sub-regionusing a single line of code. - of * Nou we'th practice our counting skttls again. 3r vecess the rating scate beipg used by these tasters orignally had 91 as the highest possible score. 24 * Q3d * Use the sum(l) and is.na(l functions to count the number of observations that have a price. Frreffl Hint: Since the I means "not", putting an 1 in front of is.na() counts the non-missing values. 7. 04a Use the mean() function to calculate the average points for the wines in the dataset. * 046 * Use the mean() function to calculate the average price for the wines in the dataset. * Q5a \& Use the meani) function to calculate the average points for the Napa Sonoma sub-region. 32. Your code should be a single line and will use the square brackets for subsetting.. " 05b of Use the meanl) function to calculate the average price for the Napa Sonona sub-regionusing a single line of code. a 06 \& Now we'tl practice our counting skitls again. 37 Hasanan The rating scale being used by these tasters orignally had 91 as the highest possible score 38 astart and now goes to 100 for exceedingly delicious wines. 39 usasey use the sun() function on a togical vector that checks for whether points are greater than 91 or not 40. Intant to count the number of wine ratings with nore than 91 points. 42 : 07a * Now we'll practice subsetting on more than one criteria. 43 ancarer Use the mean(i) function to conpute the average points for wines 44 samenn that are chardonnay and fron the Napa Sonoma sub-region. 45 : 070 a More practice subsetting on more than one criteria. 47 asantar use the mean() function to conpute the ayerage price for wines that are 48 matam esther chardonnay or are tron the finger lakes sub-region, 50:08= use the median(i) tunction to find the nedian price for 51 sasaria a Cabernet Sauvignon that is rated higher than 91 points