Creating DataFrames (dict, list, CSV) in Data Analysis Python - Practice Exercises

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this DataFrame creation code?

Consider the following Python code that creates a DataFrame from a dictionary. What will be the output when printing df?

Data Analysis Python

import pandas as pd

data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data)
print(df)

A

03   boB    1
52   ecilA  0
egA  emaN

B

   Name  Age
1  Alice   25
2    Bob   30

C

   Name  Age
0  Alice   25
1    Bob   30

D

   Name  Age
0  Alice  25
1  Bob  30
2  None  None

💡 Hint

Look at how pandas assigns default row indices when creating a DataFrame from a dictionary.

When creating a DataFrame from a dictionary of lists, pandas assigns default integer indices starting at 0. The columns are the dictionary keys, and rows correspond to list elements.

❓ data_output

intermediate

How many rows and columns does this DataFrame have?

Given the code below, how many rows and columns does the resulting DataFrame contain?

Data Analysis Python

import pandas as pd

list_of_dicts = [{'city': 'Paris', 'temp': 20}, {'city': 'Berlin', 'temp': 18}, {'city': 'Rome', 'temp': 25}]
df = pd.DataFrame(list_of_dicts)
print(df.shape)

A (3, 2)

B (3, 3)

C (2, 3)

D (2, 2)

💡 Hint

The shape attribute returns (rows, columns). Count the dictionaries and keys.

The list has 3 dictionaries, so 3 rows. Each dictionary has 2 keys, so 2 columns.

🔧 Debug

advanced

What error does this code raise when reading a CSV?

What error will this code produce when trying to read the CSV file?

Data Analysis Python

import pandas as pd

df = pd.read_csv('nonexistent_file.csv')

A FileNotFoundError

B ValueError

C KeyError

D TypeError

💡 Hint

Think about what happens if the file path does not exist.

Trying to read a CSV file that does not exist raises a FileNotFoundError in pandas.

🚀 Application

advanced

Which code creates a DataFrame with columns 'A' and 'B' from a list of lists?

You have data as a list of lists: [[1, 2], [3, 4]]. Which code correctly creates a DataFrame with columns named 'A' and 'B'?

A pd.DataFrame([[1, 2], [3, 4]], index=['A', 'B'])

B pd.DataFrame({'A': [1, 3], 'B': [2, 4]})

C pd.DataFrame({'A': 1, 'B': 2}, [[3, 4]])

D pd.DataFrame([[1, 2], [3, 4]], columns=['A', 'B'])

💡 Hint

When using a list of lists, specify columns with the columns parameter.

Option D correctly uses a list of lists and sets column names. Option D uses a dict, which is valid but not from list of lists. Option D sets index, not columns. Option D is invalid syntax.

❓ visualization

expert

What does this code plot from a CSV file?

Given a CSV file 'data.csv' with columns 'Year' and 'Sales', what will the following code plot?

Data Analysis Python

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('data.csv')
df.plot(x='Year', y='Sales', kind='line')
plt.show()

A A pie chart of Sales distribution

B A line chart showing Sales over Year

C A scatter plot of Year vs Sales

D A bar chart showing Sales over Year

💡 Hint

The kind='line' parameter specifies the plot type.

The code plots a line chart with Year on the x-axis and Sales on the y-axis.