Talented Pakistan

AI Engineering Course - Module 2

Numpy & Pandas Assessment

Assessment Numpy Pandas

Step 1
Step 2

First Name

Last Name

Email

Phone/Mobile

1. What is the output?

import numpy as np
a = np.array([1, 2, 3, 4, 5])
print(a[1:4])

[1 2 3 4]

[1 4]

[2 3 4]

[2 3 4 5]

2. What is the output?

import numpy as np 
a = np.array([[1,2,3],[4,5,6]]) 
print(a.reshape(3, 2))

[[1 2 3] [4 5 6]

[[1 4] [2 5] [3 6]]

[[4 5 6] [1 2 3]]

[[1 2] [3 4] [5 6]]

3. What is the output?

import numpy as np
a = np.array([10, 20, 30, 40])
print(np.where(a > 20, a, 0))

[ 30 40 30 40]

[ 0 0 30 40]

[ 30 40 0 0]

[ 30 0 0 40]

4. What is the output?

import numpy as np
a = np.array([1, 2, 3, 4, 5])
print(a[::-1])

[5 4 3 2 1]

[1 2 3 4 5]

[1 5]

[5 1]

5. What is the output?

import numpy as np
M = np.array([[1,2,3],[4,5,6],[7,8,9]], dtype=float)
col_means = M.mean(axis=0)
M_centered = M - col_means
print(M_centered)

[[-1. -1. -1.] [ 0. 0. 0.] [ 1. 1. 1.]]

[[-2. -2. -2.] [ 0. 0. 0.] [ 2. 2. 2.]]

[[-3. -3. -3.] [ 0. 0. 0.] [ 3. 3. 3.]]

[[-4. -4. -4.] [ 0. 0. 0.] [ 4. 4. 4.]]

6. What is the output?

import pandas as pd
df = pd.DataFrame({'x': [1,2,None,4]})
print(df['x'].isnull().sum())

7

3

0

1

7. What is the output?

import pandas as pd
df = pd.DataFrame({'A':[1,2,3],'B':[4,5,6]})
print(df.iloc[1, 0])

6

4

2

0

8. What is the output?

import pandas as pd
df = pd.DataFrame({'A':[1,2,3],'B':[4,5,6]})
print(df.describe()['A']['mean'])

2

6

3

5

9. What is the output?

import pandas as pd
df = pd.DataFrame({'A':[3,1,2],'B':[6,4,5]})
print(df.sort_values('A').reset_index(drop=True))

a.

b.

c.

d.

10. What is the output?

import pandas as pd
df = pd.DataFrame({'A':[1,2,3],'B':[4,5,6],'C':[7,8,9]})
print(df[['A','C']].head(2))

a.

b.

c.

d.