Python vs R vs Excel for analysis in Data Analysis Python - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the pandas library, which is used for data analysis in Python.

Data Analysis Python

import [1] as pd

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

Anumpy

Bseaborn

Cmatplotlib

Dpandas

Attempts:

3 left

💡 Hint

Common Mistakes

Importing numpy instead of pandas

Using matplotlib or seaborn which are for plotting

We use pandas for data analysis in Python. Importing it as pd is a common practice.

2fill in blank

medium

Complete the code to read a CSV file named 'data.csv' into a pandas DataFrame.

Data Analysis Python

df = pd.[1]('data.csv')

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

Aread_excel

Bread_csv

Cread_json

Dread_table

Attempts:

3 left

💡 Hint

Common Mistakes

Using read_excel for CSV files

Using read_json or read_table incorrectly

The read_csv function loads CSV files into a DataFrame.

3fill in blank

hard

Fix the error in the code to calculate the mean of the 'Age' column in the DataFrame.

Data Analysis Python

mean_age = df['Age'].[1]()

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

Amean

Bcount

Csum

Dmedian

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum() instead of mean()

Using count() which counts entries

Using median() which finds the middle value

The mean() function calculates the average value of the column.

4fill in blank

hard

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

Data Analysis Python

{word: [1] for word in words if [2] > 3}

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

Alen(word)

Bword

Clen(words)

Dword.length

Attempts:

3 left

💡 Hint

Common Mistakes

Using word instead of len(word) for length

Using len(words) which is the length of the list, not the word

We use len(word) to get the length of each word and check if it's greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their counts if the count is greater than 1.

Data Analysis Python

{ [1]: [2] for [3], [2] in word_counts.items() if [2] > 1 }

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

Aword.upper()

Bcount

Cword

Dword_counts

Attempts:

3 left

💡 Hint

Common Mistakes

Using word_counts as a loop variable

Mixing up keys and values

Not converting word to uppercase

The key is the uppercase word (word.upper()), the value is the count (count), and the loop variables are word and count.