Module 2 Review
Authored by Bayu Prasetya
Computers
Professional Development
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30 questions
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1.
MULTIPLE CHOICE QUESTION
10 mins • 8 pts
Perhatikan tabel di atas. Manakah query yang sesuai untuk menampilkan jumlah distrik di setiap negara-negara di benua Asia, diurutkan dari yang paling banyak.
2.
MULTIPLE CHOICE QUESTION
2 mins • 5 pts
Dengan SQL, bagaimana kita memilih semua catatan dari tabel bernama "Person" di mana nilai kolom "FirstName" mengandung karakter "al"
SELECT * FROM Persons WHERE FirstName LIKE "%al%"
SELECT * FROM Persons WHERE FirstName LIKE "_al_"
SELECT * FROM Persons WHERE FirstName = "al"
SELECT * FROM Persons WHERE FirstName LIKE "%al"
3.
MULTIPLE SELECT QUESTION
2 mins • 8 pts
Fungsi yang digunakan saat kita ingin membuat angka acak berdistribusi normal adalah...
numpy.random.randint()
numpy.random.randn()
numpy.random.normal()
numpy.random.random()
numpy.random.random_sample()
4.
MULTIPLE CHOICE QUESTION
2 mins • 10 pts
import numpy as np
arr = np.arange(1,21)
arr = arr.reshape(4,5)
print(arr)
Output dari syntax ini adalah ...
[[ 1 2 3 4 5]
[ 6 7 8 9 10]
[11 12 13 14 15]
[16 17 18 19 20]]
[ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]
Error
[ 1 2 3 4 5]
[ 6 7 8 9 10]
[11 12 13 14 15]
[16 17 18 19 20]
[[ 1 2 3 4]
[ 5 6 7 8]
[ 9 10 11 12]
[13 14 15 16]
[17 18 19 20]]
5.
MULTIPLE CHOICE QUESTION
2 mins • 10 pts
import numpy as np
arr = np.arange(1,21)
arr = arr.reshape(-1)
print(arr)
Output dari syntax ini adalah ...
[ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20]
Error
[[ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20]]
[[ 1] [ 2] [ 3] [ 4] [ 5] [ 6] [ 7] [ 8] [ 9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20]]
[20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1]
6.
MULTIPLE SELECT QUESTION
1 min • 6 pts
Manakah dari sintaks ini yang akan memilih index bernama "foo" dari DataFrame "df" ?
df['foo']
Tidak ada yang tepat
df.loc['foo',:]
df.loc[:,'foo']
df['foo'][:]
7.
MULTIPLE SELECT QUESTION
1 min • 7 pts
Lengkapi perintah ini agar menampilkan data dari baris ke 3 sampai 10 pada kolom yang mempunyai nama "Restorant A" dan "Restorant B"
df.loc[3:11, ["Restorant A","Restorant B"]]
df[2:10][["Restorant A","Restorant B"]]
df.iloc[2:10, ["Restorant A","Restorant B"]]
df[["Restorant A","Restorant B"]]
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