Selecting columns in Data Analysis Python - Mini Project: Build & Apply

Selecting columns

📖 Scenario: You work in a small shop that keeps track of sales data in a table. You want to look at only some parts of the data to understand it better.

🎯 Goal: You will create a table of sales data and then select only the columns for Product and Price to see just those details.

📋 What You'll Learn

Create a pandas DataFrame with specific sales data

Create a list of column names to select

Select only the specified columns from the DataFrame

Print the selected columns DataFrame

💡 Why This Matters

🌍 Real World

Selecting specific columns from data tables is common when you want to focus on certain details, like product names and prices in sales data.

💼 Career

Data analysts and scientists often select columns to prepare data for reports, visualizations, or further analysis.

1

Create the sales data table

Create a pandas DataFrame called sales_data with these exact columns and rows:
Product: 'Apple', 'Banana', 'Carrot'
Price: 0.5, 0.3, 0.2
Quantity: 10, 20, 15

Data Analysis Python

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

Need a hint?

Use pd.DataFrame with a dictionary where keys are column names and values are lists of column values.

2

Create a list of columns to select

Create a list called columns_to_select that contains the exact column names 'Product' and 'Price'.

Data Analysis Python

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot'],
    'Price': [0.5, 0.3, 0.2],
    'Quantity': [10, 20, 15]
})
# Create the list columns_to_select with 'Product' and 'Price'
# Your code here

Need a hint?

Make a list with the two column names as strings.

3

Select the columns from the DataFrame

Create a new DataFrame called selected_data by selecting only the columns in columns_to_select from sales_data.

Data Analysis Python

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot'],
    'Price': [0.5, 0.3, 0.2],
    'Quantity': [10, 20, 15]
})
columns_to_select = ['Product', 'Price']
# Select the columns from sales_data and assign to selected_data
# Your code here

Need a hint?

Use bracket notation with the list of columns to select from the DataFrame.

4

Print the selected columns

Print the selected_data DataFrame to see only the Product and Price columns.

Data Analysis Python

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot'],
    'Price': [0.5, 0.3, 0.2],
    'Quantity': [10, 20, 15]
})
columns_to_select = ['Product', 'Price']
selected_data = sales_data[columns_to_select]
# Print the selected_data DataFrame
# Your code here

Need a hint?

Use print(selected_data) to show the selected columns.