NumPy with Pandas integration - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert a Pandas Series to a NumPy array.

NumPy

import pandas as pd
s = pd.Series([1, 2, 3, 4])
arr = s.[1]()

Drag options to blanks, or click blank then click option'

Aarray

Basarray

Cvalues

Dto_numpy

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'values' which is deprecated in newer Pandas versions.

Trying to use 'array' which is not a Series method.

The to_numpy() method converts a Pandas Series to a NumPy array.

2fill in blank

medium

Complete the code to create a Pandas DataFrame from a NumPy array.

NumPy

import numpy as np
import pandas as pd
arr = np.array([[1, 2], [3, 4]])
df = pd.DataFrame([1])

Drag options to blanks, or click blank then click option'

Aarr

B[arr]

Carr.tolist()

Darr.values

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a list containing the array instead of the array itself.

Using 'arr.values' which is invalid for a NumPy array.

You can pass a NumPy array directly to pd.DataFrame() to create a DataFrame.

3fill in blank

hard

Fix the error in the code to get the mean of a NumPy array column in a DataFrame.

NumPy

import numpy as np
import pandas as pd
data = {'A': np.array([1, 2, 3]), 'B': [4, 5, 6]}
df = pd.DataFrame(data)
mean_col = df['A'].[1]()

Drag options to blanks, or click blank then click option'

Amean

Baverage

Cmean()

Davg

Attempts:

3 left

💡 Hint

Common Mistakes

Including parentheses inside the blank causing syntax error.

Using 'average' or 'avg' which are not valid Pandas methods.

The correct method to get the mean of a Series is mean(), but in the blank you only put the method name without parentheses because parentheses are already in the code.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length only if length is greater than 3.

NumPy

words = ['data', 'science', 'is', 'fun']
lengths = { [1] : [2] for word in words if len(word) > 3 }

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Aword

Blen(word)

Cword.upper()

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using transformations like upper or lower instead of the word itself.

Using the length as the key instead of the value.

The dictionary comprehension maps each word to its length using len(word).

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their values only if value is greater than 0.

NumPy

data = {'a': 1, 'b': -1, 'c': 3}
result = { [1] : [2] for k, v in data.items() if v [3] 0 }

Drag options to blanks, or click blank then click option'

Ak.upper()

Bv

C>

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase keys instead of uppercase.

Using wrong comparison operators like '<' or '==' in the condition.

Swapping keys and values.

The comprehension maps the uppercase key k.upper() to the value v only if v > 0.