Creating DataFrames (dict, list, CSV) in Data Analysis Python - Try It Yourself

Creating DataFrames from Dictionary, List, and CSV

📖 Scenario: You work as a data analyst for a small bookstore. You want to organize book information using tables to analyze sales and inventory easily.

🎯 Goal: You will create tables called DataFrames from different data sources: a dictionary, a list of lists, and a CSV file. This will help you understand how to start working with data in Python.

📋 What You'll Learn

Use the pandas library to create DataFrames

Create a DataFrame from a dictionary

Create a DataFrame from a list of lists

Create a DataFrame by reading a CSV file

Print the DataFrames to see their content

💡 Why This Matters

🌍 Real World

DataFrames are the main way to organize and analyze data in many fields like sales, finance, and research.

💼 Career

Knowing how to create DataFrames from various data sources is a key skill for data analysts and data scientists.

1

Create a DataFrame from a dictionary

Import the pandas library as pd. Then create a dictionary called book_dict with these exact entries: 'Title': ['Python Basics', 'Data Science 101', 'Machine Learning'], 'Author': ['John Doe', 'Jane Smith', 'Emily Davis'], and 'Price': [29.99, 39.99, 49.99]. Finally, create a DataFrame called df_dict from book_dict using pd.DataFrame().

Data Analysis Python

import pandas as pd
# Create the dictionary book_dict with the given entries
# Create the DataFrame df_dict from book_dict
# Your code here

Need a hint?

Use pd.DataFrame() to convert the dictionary into a DataFrame.

2

Create a DataFrame from a list of lists

Create a list of lists called book_list with these exact rows: ['Python Basics', 'John Doe', 29.99], ['Data Science 101', 'Jane Smith', 39.99], and ['Machine Learning', 'Emily Davis', 49.99]. Then create a DataFrame called df_list from book_list using pd.DataFrame() and set the column names to ['Title', 'Author', 'Price'].

Data Analysis Python

import pandas as pd
book_dict = {
    'Title': ['Python Basics', 'Data Science 101', 'Machine Learning'],
    'Author': ['John Doe', 'Jane Smith', 'Emily Davis'],
    'Price': [29.99, 39.99, 49.99]
}
df_dict = pd.DataFrame(book_dict)
# Create the list of lists book_list with the given rows
# Create the DataFrame df_list from book_list with columns ['Title', 'Author', 'Price']
# Your code here

Need a hint?

Use columns=[...] to name the columns when creating the DataFrame from the list.

3

Create a DataFrame by reading a CSV file

Create a CSV file named books.csv with these exact contents including the header:

Title,Author,Price
Python Basics,John Doe,29.99
Data Science 101,Jane Smith,39.99
Machine Learning,Emily Davis,49.99

Then read this CSV file into a DataFrame called df_csv using pd.read_csv().

Data Analysis Python

import pandas as pd
book_dict = {
    'Title': ['Python Basics', 'Data Science 101', 'Machine Learning'],
    'Author': ['John Doe', 'Jane Smith', 'Emily Davis'],
    'Price': [29.99, 39.99, 49.99]
}
df_dict = pd.DataFrame(book_dict)
book_list = [
    ['Python Basics', 'John Doe', 29.99],
    ['Data Science 101', 'Jane Smith', 39.99],
    ['Machine Learning', 'Emily Davis', 49.99]
]
df_list = pd.DataFrame(book_list, columns=['Title', 'Author', 'Price'])
# Create the CSV file books.csv with the given content
# Read the CSV file into a DataFrame called df_csv
# Your code here

Need a hint?

Use open() with mode 'w' to create the CSV file, then pd.read_csv() to read it.

4

Print all three DataFrames

Print the DataFrames df_dict, df_list, and df_csv in this exact order, each on its own line.

Data Analysis Python

import pandas as pd
book_dict = {
    'Title': ['Python Basics', 'Data Science 101', 'Machine Learning'],
    'Author': ['John Doe', 'Jane Smith', 'Emily Davis'],
    'Price': [29.99, 39.99, 49.99]
}
df_dict = pd.DataFrame(book_dict)
book_list = [
    ['Python Basics', 'John Doe', 29.99],
    ['Data Science 101', 'Jane Smith', 39.99],
    ['Machine Learning', 'Emily Davis', 49.99]
]
df_list = pd.DataFrame(book_list, columns=['Title', 'Author', 'Price'])
with open('books.csv', 'w') as f:
    f.write('Title,Author,Price\n')
    f.write('Python Basics,John Doe,29.99\n')
    f.write('Data Science 101,Jane Smith,39.99\n')
    f.write('Machine Learning,Emily Davis,49.99\n')
df_csv = pd.read_csv('books.csv')
# Print df_dict, df_list, and df_csv each on its own line
# Your code here

Need a hint?

Use three print() statements, one for each DataFrame.