Selecting columns by name in Pandas - Mini Project: Build & Apply

Selecting columns by name

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

🎯 Goal: Learn how to select specific columns by their names from a table of data using pandas.

📋 What You'll Learn

Create a pandas DataFrame with given sales data

Create a list of column names to select

Select columns from the DataFrame using the list of column names

Print the selected columns

💡 Why This Matters

🌍 Real World

Selecting specific columns helps you focus on important parts of your data, like sales numbers or product names, without extra details.

💼 Career

Data scientists often select columns by name to prepare data for analysis or visualization, making their work clearer and faster.

1

Create the sales data table

Create a pandas DataFrame called sales_data with these exact columns and rows:
Product: ['Apple', 'Banana', 'Carrot', 'Dates']
Price: [1.2, 0.5, 0.8, 3.0]
Quantity: [10, 20, 15, 7]
Date: ['2024-06-01', '2024-06-01', '2024-06-02', '2024-06-02']

Pandas

import pandas as pd
# Create the DataFrame sales_data 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 with these exact column names: 'Product' and 'Quantity'

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot', 'Dates'],
    'Price': [1.2, 0.5, 0.8, 3.0],
    'Quantity': [10, 20, 15, 7],
    'Date': ['2024-06-01', '2024-06-01', '2024-06-02', '2024-06-02']
})
# Create the list columns_to_select with 'Product' and 'Quantity'
# Your code here

Need a hint?

Use square brackets to create a list with the exact column names as strings.

3

Select columns from the DataFrame

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

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot', 'Dates'],
    'Price': [1.2, 0.5, 0.8, 3.0],
    'Quantity': [10, 20, 15, 7],
    'Date': ['2024-06-01', '2024-06-01', '2024-06-02', '2024-06-02']
})
columns_to_select = ['Product', 'Quantity']
# Select the columns from sales_data using columns_to_select
# Your code here

Need a hint?

Use square brackets with the list of column names to select columns from the DataFrame.

4

Print the selected columns

Print the selected_data DataFrame to see only the selected columns

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot', 'Dates'],
    'Price': [1.2, 0.5, 0.8, 3.0],
    'Quantity': [10, 20, 15, 7],
    'Date': ['2024-06-01', '2024-06-01', '2024-06-02', '2024-06-02']
})
columns_to_select = ['Product', 'Quantity']
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.