Pandas: First Steps

Course Content

Pandas: First Steps

Pandas: First Steps

1. Getting Started

Introduction to Pandas Series Task: Coffee Orders Series Task: Barista's Favorites Coffees Accessing Elements from a Series Task: Drink of the Hour Task - Signature Drinks Task: Mid-Morning Specials Task - Fetching the Mid-Shift Drinks Operations over Series Task: Modifying a single element Task: Modifying the Entire Series Task: Modifying Part of a Series Task: Processing the Restock of Inventory

2. Basics of Dataframes

What is a DataFrame?Task: Creating a Table of Popular Coffee Drinks Task: Tracking Coffee Bean Deliveries Task: Weekly Coffee Sales Report Adding new Columns Task: Finding Total Sales Per Drink Task: Calculating Total Sales Revenue Adding new Rows Task: Adding a New Employee to the Café Team Task: Adding New Coffee Types to the Café Menu

3. Fetching Data from DataFrames

The `head()` Method Task: Preview the Coffee Menu The `tail()` Method Task: Finding the Most Expensive Coffees The `sample()` Method Task: Randomly Select Customer Orders for Quality Check Extracting Multiple Columns Task: Extracting the Total Profit Task: Extract Sales Data For Analysis The `iloc` Property Task: Access Sales Data at Café Pandasia - Part 1 Task: Access Sales Data at Café Pandasia - Part 2 Task: Access Sales Data at Café Pandasia - Part 3

The `sample()` Method

The sample() method returns a random row from the DataFrame by default.

There are two optional named parameters which can be used to specify how many random rows to fetch:

n: Specifies the exact number of random rows to fetch;
frac: Specifies the fraction or percentage of the total rows to fetch. For example, frac=0.2 will return 20% of the total rows;


              123456789101112
            
import pandas as pd

# Sample DataFrame
df = pd.DataFrame({
    'Coffee': ['Espresso', 'Latte', 'Cappuccino', 'Americano', 'Macchiato'],
    'Price': [2.5, 3.5, 3.0, 2.8, 3.2],
    'Availability': ['Yes', 'Yes', 'Yes', 'Yes', 'No']
})

print("Get 2 random rows from the DataFrame:")
random_rows = df.sample(n=2)
print(random_rows)

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 5

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Course Content

Pandas: First Steps

Pandas: First Steps

1. Getting Started

Introduction to Pandas Series Task: Coffee Orders Series Task: Barista's Favorites Coffees Accessing Elements from a Series Task: Drink of the Hour Task - Signature Drinks Task: Mid-Morning Specials Task - Fetching the Mid-Shift Drinks Operations over Series Task: Modifying a single element Task: Modifying the Entire Series Task: Modifying Part of a Series Task: Processing the Restock of Inventory

2. Basics of Dataframes

What is a DataFrame?Task: Creating a Table of Popular Coffee Drinks Task: Tracking Coffee Bean Deliveries Task: Weekly Coffee Sales Report Adding new Columns Task: Finding Total Sales Per Drink Task: Calculating Total Sales Revenue Adding new Rows Task: Adding a New Employee to the Café Team Task: Adding New Coffee Types to the Café Menu

3. Fetching Data from DataFrames

The `head()` Method Task: Preview the Coffee Menu The `tail()` Method Task: Finding the Most Expensive Coffees The `sample()` Method Task: Randomly Select Customer Orders for Quality Check Extracting Multiple Columns Task: Extracting the Total Profit Task: Extract Sales Data For Analysis The `iloc` Property Task: Access Sales Data at Café Pandasia - Part 1 Task: Access Sales Data at Café Pandasia - Part 2 Task: Access Sales Data at Café Pandasia - Part 3

The `sample()` Method

The sample() method returns a random row from the DataFrame by default.

There are two optional named parameters which can be used to specify how many random rows to fetch:

n: Specifies the exact number of random rows to fetch;
frac: Specifies the fraction or percentage of the total rows to fetch. For example, frac=0.2 will return 20% of the total rows;


              123456789101112
            
import pandas as pd

# Sample DataFrame
df = pd.DataFrame({
    'Coffee': ['Espresso', 'Latte', 'Cappuccino', 'Americano', 'Macchiato'],
    'Price': [2.5, 3.5, 3.0, 2.8, 3.2],
    'Availability': ['Yes', 'Yes', 'Yes', 'Yes', 'No']
})

print("Get 2 random rows from the DataFrame:")
random_rows = df.sample(n=2)
print(random_rows)

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 5

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