For the following question answer all the parts in R studio use R language. mpg dataset is the default dataset in R studio. 1. Load the built-in “mpg” dataset in RStudio using data(mpg) and write code to perform the following: (a) Obtain the summary statistics for the “hwy” variable (Highway MPG). (b) Create a box plot of the “cty” variable (City MPG). (c) Create a scatterplot of the “hwy” variable against the “cty” variable. What kind of relationship do the two variables have?

this code is in (.c) and I need help with what is in the imageI have already done part one and now need help with making it work its almost done but it is not working please help below is what I have so far   /*KL25Z_LED_Blinky.c*/ #include <stdint.h> /* provides fixed width integer types. For example, uint32_t) */#include "derivative.h" /* KL25Z info */#include "mcg.h" /* main clock generator */#include "systick.h" /* SysTick timer */#include "KL25Z_gpio.h" /* GPIO routines */#include "KL25Z_port.h" /* PORT routines */#include "delays.h" /* software based delays */ /* Macro definitions */#define RED_LED_PIN 18 /* GPIO and PORT module "pins", not the device pins */#define GREEN_LED_PIN 19#define BLUE_LED_PIN 1#define LED_OFF 1#define LED_ON 0 /* Globals */volatile uint32_t sysTicks; int main(void) {int k; pll_init(8000000,0,1,4,24,1); sysTicks = 0;initSysTicks(); enable_port_clock(PORTB_PERIPHERAL);enable_port_clock(PORTD_PERIPHERAL);/* set signal multiplexing for GPIOs to the…

save_compressed_image: takes a nested list and a filename (string) as input, and saves it in the compressed PGM format to a file with the given filename. If the image matrix given as input is not a valid compressed PGM image matrix, instead raise a AssertionError with an appropriate error message. >>> save_compressed_image([["0x5", "200x2"], ["111x7"]], "test.pgm.compressed") >>> fobj open("test.pgm.compressed", 'r') >>> fobj.read() = 'P2C\\n7_2\\n255\\n0x5 200x2\\n111x7\\n' >>> fobj.close() >>> image [["0x5", "200x2"], ["111x7"]] >>> save_compressed_image(image, "test.pgm") >>> image2 = >>> image True = == load_compressed_image("test.pgm") image2 • save_image: takes a nested list and a filename (string) as input. Checks the type of elements in the list If thou are intogors thon saves the posted list as a PCM imago matrix into a file with the given

3. Which among the following shows a valid use of the Direction enumeration as a parameter to the moveCharacter function? Select al that apply. enum Direction {  case north, south, west, east}func moveCharacter(x: Int, y: Int, facing: Direction) {// code here}   moveCharacter(x: 0, y: 0, facing: .southwest)   moveCharacter(x: 0, y: 0, facing: Direction.north)   moveCharacter(x: 0, y: 0, facing: .south)   moveCharacter(x: 0, y: 0, facing: Direction.northeast)

You are given 2 text files named drywet.txt and wetwet.txt. wetwet.txt data file refers to the probability of next day being a wet day if the current day is wet. drywet.txt data file refers to the probability of next day being a wet day if the current day is dry. NOTE: the data for the same location in wetwet.txt and drywet.txt will have the same line number. These files are in the format of: (excerpt from wetwet.txt)-97.58 26.02 0.76 0.75 0.77 0.74 0.80 0.86 0.94 0.97 0.89 0.77 0.74 0.77 -97.19 26.03 0.73 0.76 0.75 0.71 0.79 0.85 0.92 0.95 0.90 0.81 0.76 0.75 -98.75 26.35 0.74 0.76 0.76 0.73 0.67 0.84 0.83 0.85 0.80 0.71 0.71 0.76 … In each line, the first and second numbers represent the location’s longitude and latitude. The following 12 numbers represent the probability of the next day being a wet day of the month. For example, on the first line of the excerpt above 0.75 means that in February (4th column), there is a 75% of chance that the next day is a wet day if today is a wet…

Click cell C9 and insert a VLOOKUP function that looks up the code in cell B9, compares it to the codes and types of art in the range B2:C6, and returns the type of art. Copy the function in cell C9 to the range C9:C54. Hide column B that contains the codes.

Please use the R language to answer the following questions

Get the one hot df to check how many extra columns/features were created as a result of the one-hot encoding. Put the result in the variable  one hot df shape.   # TODO 1 one_hot_df_shape = print(f"Shape of one_hot_df is: {one_hot_df_shape}") todo_check([ (one_hot_df_shape == (517,30),'one_hot_df shape did not match (517, 30)') ])

You are given a file which has an Australian state name and a university name in each line. You can view the file as follows. DO NOT CHANGE the content of the uni.txt (otherwise you will have to press the triple dot button at the top-right and then "Reset to Scaffold"). sorter.py uni.txt + uni.txt 1 NSW USYD 2 NSW UNSW 3 ACT ANU 4 WA UWA 5 QLD UQ 6 VIC UMEL 7 VIC MONASH_U 8 SA ADELAIDE_U Write a program sorter.py that 1) reads a command line argument containing the file to open, 2) opens and reads the file, 3) extracts each Australian state (not the university), i.e. the first word token in each line, and 4) sorts the states in alphabetical order. You may assume that each state is one word long. Furthermore, make sure to only record the names of unique states - so do not record any state twice. HINT: use the in keyword. E.g. ▸ Run 1 ls = [1, 2 if 4 in ls: 3 4 elif 4 not in ls: 2, 3] print("4 is in list") 5 print("4 is NOT in list") PYTHON You MUST use open(), read(), split(), sort(),…

add a menu that you design which includes these features: Ability for a user to input a set of grades into a vector. Make sure only integers between 0 and 100 are used. Cout the vector onto the screen with grades separated by spaces and starting with, "Original user vector: " Output the average grade. Ability to sort the user-inputted vector from low to high or high to low. Cout the new sorted vector onto the screen with grades separated by spaces and starting with, "Grades sorted vector: " Using the binary search method (not the linear search method), add the ability to find a user selected grade and change it.