DataFrame structure (index, columns, values) in Data Analysis Python - Mini Project: Build & Apply

Understanding DataFrame Structure: Index, Columns, and Values

📖 Scenario: You are working with a small dataset of fruit sales in a store. You want to organize this data in a table format to easily see the fruit names, their quantities sold, and prices.

🎯 Goal: Build a simple DataFrame using pandas that shows the fruit names as the index, and columns for quantity sold and price. Learn how to set up the index, columns, and access the values.

📋 What You'll Learn

Create a pandas DataFrame with specific data

Set the fruit names as the index

Define columns for quantity and price

Access the DataFrame's index, columns, and values attributes

💡 Why This Matters

🌍 Real World

Organizing sales data in tables helps store managers quickly find and analyze product information.

💼 Career

Data analysts and scientists often use DataFrames to clean, organize, and analyze data efficiently.

1

Create the initial DataFrame

Import pandas as pd and create a DataFrame called df with this data: fruits 'Apple', 'Banana', 'Cherry'; quantities 10, 20, 15; prices 0.5, 0.3, 0.8. Use a dictionary with keys 'Fruit', 'Quantity', and 'Price'.

Data Analysis Python

import pandas as pd
# Create the DataFrame df with the given data
# Your code here

Need a hint?

Use pd.DataFrame() with a dictionary to create the table.

2

Set the index to the fruit names

Set the Fruit column as the index of the DataFrame df using set_index method with inplace=True.

Data Analysis Python

import pandas as pd
data = {'Fruit': ['Apple', 'Banana', 'Cherry'], 'Quantity': [10, 20, 15], 'Price': [0.5, 0.3, 0.8]}
df = pd.DataFrame(data)
# Set the 'Fruit' column as the index of df
# Your code here

Need a hint?

Use df.set_index('Fruit', inplace=True) to change the index.

3

Access the DataFrame's index, columns, and values

Create three variables: index to store df.index, columns to store df.columns, and values to store df.values.

Data Analysis Python

import pandas as pd
data = {'Fruit': ['Apple', 'Banana', 'Cherry'], 'Quantity': [10, 20, 15], 'Price': [0.5, 0.3, 0.8]}
df = pd.DataFrame(data)
df.set_index('Fruit', inplace=True)
# Assign df.index to index, df.columns to columns, and df.values to values
# Your code here

Need a hint?

Use df.index, df.columns, and df.values to get these parts.

4

Complete the DataFrame structure setup

Add a comment above the DataFrame creation that says # Fruit sales data to label the data clearly.

Data Analysis Python

# Fruit sales data
import pandas as pd
data = {'Fruit': ['Apple', 'Banana', 'Cherry'], 'Quantity': [10, 20, 15], 'Price': [0.5, 0.3, 0.8]}
df = pd.DataFrame(data)
df.set_index('Fruit', inplace=True)
index = df.index
columns = df.columns
values = df.values
# Your code here

Need a hint?

Comments start with # in Python. Add it above the data.