• Problem 1

Import the numpy package under the name np

Create a vector or 1D array with 10 zeros and print it

Find the memory size of this array

[ ]: array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])

[ ]: print(The Size of the array is, arr.itemsize*arr.size, Bytes)

The Size of the array is 80 Bytes

• Problem 2:

Create another vector or 1D array with values ranging from 10 to 20

Reverse the created vector (first element becomes last) Is there any NumPy method that you can use?

[ ]: array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20])

[ ]: array([20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10])

• Problem 3:

Create a 34 array with random values (standard normal distribution) and find the minimum and maximum values

[ ]: array([[8672, 9272, 6342],

[3784, 5232, 7887],

[5001, 4270, 3926],

[6843, 5154, 7836]])

[ ]: arr3.max()

[ ]: 9272

[ ]: arr3.min()

[ ]: 3784

• Problem 4:

Given the following 1D array, negate all elements which are between 3 and 8, in place. (include both 3 and 8 in conditional statements)

[ ]: Z

[ ]: array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])

[ ]: array([ 0, 1, 2, -3, -4, -5, -6, -7, -8, 9, 10])

Given the 1D array Z, find the closest value to the given scalar v?

[ ]: Z

[ ]: array([ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,

22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,

39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55,

56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,

73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,

90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

Closet Value is %d 33

Subtract the mean of each row of the following matrix

,

NameError Traceback (most recent call

,last)

<ipython-input-1-3b30b7c6267b> in <module>() -> 1 np.random.seed(2)

• X = np.random.rand(3, 4)
• print(X)

NameError: name np is not defined

[ ]: array([[0.3617265 , 0.3617265 , 0.3617265 , 0.3617265 ],

[0.39365556, 0.39365556, 0.39365556, 0.39365556],

[0.42918947, 0.42918947, 0.42918947, 0.42918947]])

[[ 0.0742684 -0.33580027 0.18793598 0.07359589] [ 0.02671225 -0.06332073 -0.18900692 0.22561541]

[-0.1295348 -0.16236219 0.19194436 0.09995263]]

Timing comparison for multiplication of 4 arrays. Find the fastest way to compute the multiplication ABCD. Make sure you report the elapsed time. (hint: you can find relevant information at https://youtu.be/SeBRHg9ZrSs) Complete the following:

5 Problem 5

Import and print the file parks.csv (Park Code should be the index column)

<IPython.core.display.HTML object>

[ ]: Park Name Longitude

Park Code

ACAD	Acadia National Park		-68.21
ARCH	Arches National Park		-109.57
BADL	Badlands National Park		-102.50
BIBE	Big Bend National Park		-103.25
BISC	Biscayne National Park		-80.08
BLCA	Black Canyon of the Gunnison National Park		-107.72
BRCA	Bryce Canyon National Park		-112.18
CANY	Canyonlands National Park		-109.93
CARE	Capitol Reef National Park		-111.17
CAVE	Carlsbad Caverns National Park		-104.44
CHIS	Channel Islands National Park		-119.42
CONG	Congaree National Park		-80.78
CRLA	Crater Lake National Park		-122.10
CUVA	Cuyahoga Valley National Park		-81.55
DENA	Denali National Park and Preserve		-150.50
DEVA	Death Valley National Park		-116.82
DRTO	Dry Tortugas National Park		-82.87
EVER	Everglades National Park		-80.93
GAAR	Gates Of The Arctic National Park and Preserve		-153.30
GLAC	Glacier National Park		-114.00
GLBA	Glacier Bay National Park and Preserve		-137.00
GRBA	Great Basin National Park		-114.30
GRCA	Grand Canyon National Park		-112.14
GRSA	Great Sand Dunes National Park and Preserve		-105.51
GRSM	Great Smoky Mountains National Park		-83.53
GRTE	Grand Teton National Park		-110.80
GUMO	Guadalupe Mountains National Park		-104.87
HALE	Haleakala National Park		-156.17
HAVO	Hawaii Volcanoes National Park		-155.20
HOSP	Hot Springs National Park		-93.05
ISRO	Isle Royale National Park		-88.55
JOTR	Joshua Tree National Park		-115.90
KATM	Katmai National Park and Preserve		-155.00
KEFJ	Kenai Fjords National Park		-149.65
KOVA	Kobuk Valley National Park		-159.28
LACL	Lake Clark National Park and Preserve		-153.42
LAVO	Lassen Volcanic National Park		-121.51
MACA	Mammoth Cave National Park		-86.10
MEVE	Mesa Verde National Park		-108.49
MORA	Mount Rainier National Park		-121.75
NOCA	North Cascades National Park		-121.20
OLYM	Olympic National Park		-123.50
PEFO	Petrified Forest National Park		-109.78
PINN	Pinnacles National Park		-121.16
REDW	Redwood National Park		-124.00
ROMO	Rocky Mountain National Park		-105.58
SAGU	Saguaro National Park		-110.50
SEKI	Sequoia and Kings Canyon National Parks		-118.68
SHEN	Shenandoah National Park		-78.35
THRO	Theodore Roosevelt National Park		-103.45
VOYA	Voyageurs National Park		-92.88
WICA	Wind Cave National Park		-103.48
WRST	Wrangell St Elias National Park and Preserve		-142.00
YELL	Yellowstone National Park		-110.50
YOSE	Yosemite National Park		-119.50
ZION	Zion National Park		-113.05

[56 rows x 5 columns]

Print all column names

[ ]: list(parks.columns) [Park Name , State , Acres , Latitude , Longitude ] Make sure tha all letters are lower case and replace space with _

[ ]: parks = parks.astype(str).apply(lambda x: x.str.lower())

[ ]: parks = parks.astype(str).apply(lambda x: x.str.rstrip())

[ ]: parks = parks.astype(str).apply(lambda x: x.str.replace( ,_))

[ ]: parks[State ] = parks[State ].apply(lambda state: state.replace(_,)) Which state has the smallest national park?

[ ]: 5550

[ ]: Park Name State Acres Latitude Longitude

Park Code

HOSP hot_springs_national_park ar 5550 34.51 -93.05

State is Arkansas

Produce a histogram plot that shows the distribution of acres.

[ ]: