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Pandas: First Steps
course content

Contenuti del Corso

Pandas: First Steps

Pandas: First Steps

1. Getting Started
Introduction to PandasSeriesTask: Coffee Orders SeriesTask: Barista's Favorites CoffeesAccessing Elements from a SeriesTask: Drink of the HourTask - Signature DrinksTask: Mid-Morning SpecialsTask - Fetching the Mid-Shift DrinksOperations over SeriesTask: Modifying a single elementTask: Modifying the Entire SeriesTask: Modifying Part of a SeriesTask: Processing the Restock of Inventory
2. Basics of Dataframes
What is a DataFrame?Task: Creating a Table of Popular Coffee DrinksTask: Tracking Coffee Bean DeliveriesTask: Weekly Coffee Sales ReportAdding new ColumnsTask: Finding Total Sales Per DrinkTask: Calculating Total Sales RevenueAdding new RowsTask: Adding a New Employee to the Café TeamTask: Adding New Coffee Types to the Café Menu
3. Fetching Data from DataFrames
The `head()` MethodTask: Preview the Coffee MenuThe `tail()` MethodTask: Finding the Most Expensive CoffeesThe `sample()` MethodTask: Randomly Select Customer Orders for Quality CheckExtracting Multiple ColumnsTask: Extracting the Total ProfitTask: Extract Sales Data For AnalysisThe `iloc` PropertyTask: Access Sales Data at Café Pandasia - Part 1Task: Access Sales Data at Café Pandasia - Part 2Task: Access Sales Data at Café Pandasia - Part 3

book
Series

Importing Pandas

Before we can start working with Pandas, we need to import it:

py



Defining a Series

We can define a Series in Pandas using the following syntax:

python

The following code defines a new Series called populations representing the populations of various cities (in milions):


              
12345678

            
import pandas as pd

populations = pd.Series(
    [8.9, 3.6, 2.7, 1.6],
    ["London", "Berlin", "Rome", "Budapest"]
)

print(populations)
copy

In some cases you might see the following syntax of creating a Series, which has the same effect, except in this case we use a named parameter to specify the index_list for the sake of readibility:

py



The index Property

We can access the list of indices of a Series using the index property:


              
12345678

            
import pandas as pd

populations = pd.Series(
    [8.9, 3.6, 2.7, 1.6],
    ["London", "Berlin", "Rome", "Budapest"]
)

print(populations.index)
copy

1. What does the following code create?

2. What will be the output of the following code?

3. You must always specify the index parameter when creating a Series.

question mark

What does the following code create?

Select the correct answer

question mark

What will be the output of the following code?

Select the correct answer

question mark

You must always specify the index parameter when creating a Series.

Select the correct answer

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 1. Capitolo 2

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course content

Contenuti del Corso

Pandas: First Steps

Pandas: First Steps

1. Getting Started
Introduction to PandasSeriesTask: Coffee Orders SeriesTask: Barista's Favorites CoffeesAccessing Elements from a SeriesTask: Drink of the HourTask - Signature DrinksTask: Mid-Morning SpecialsTask - Fetching the Mid-Shift DrinksOperations over SeriesTask: Modifying a single elementTask: Modifying the Entire SeriesTask: Modifying Part of a SeriesTask: Processing the Restock of Inventory
2. Basics of Dataframes
What is a DataFrame?Task: Creating a Table of Popular Coffee DrinksTask: Tracking Coffee Bean DeliveriesTask: Weekly Coffee Sales ReportAdding new ColumnsTask: Finding Total Sales Per DrinkTask: Calculating Total Sales RevenueAdding new RowsTask: Adding a New Employee to the Café TeamTask: Adding New Coffee Types to the Café Menu
3. Fetching Data from DataFrames
The `head()` MethodTask: Preview the Coffee MenuThe `tail()` MethodTask: Finding the Most Expensive CoffeesThe `sample()` MethodTask: Randomly Select Customer Orders for Quality CheckExtracting Multiple ColumnsTask: Extracting the Total ProfitTask: Extract Sales Data For AnalysisThe `iloc` PropertyTask: Access Sales Data at Café Pandasia - Part 1Task: Access Sales Data at Café Pandasia - Part 2Task: Access Sales Data at Café Pandasia - Part 3

book
Series

Importing Pandas

Before we can start working with Pandas, we need to import it:

py



Defining a Series

We can define a Series in Pandas using the following syntax:

python

The following code defines a new Series called populations representing the populations of various cities (in milions):


              
12345678

            
import pandas as pd

populations = pd.Series(
    [8.9, 3.6, 2.7, 1.6],
    ["London", "Berlin", "Rome", "Budapest"]
)

print(populations)
copy

In some cases you might see the following syntax of creating a Series, which has the same effect, except in this case we use a named parameter to specify the index_list for the sake of readibility:

py



The index Property

We can access the list of indices of a Series using the index property:


              
12345678

            
import pandas as pd

populations = pd.Series(
    [8.9, 3.6, 2.7, 1.6],
    ["London", "Berlin", "Rome", "Budapest"]
)

print(populations.index)
copy

1. What does the following code create?

2. What will be the output of the following code?

3. You must always specify the index parameter when creating a Series.

question mark

What does the following code create?

Select the correct answer

question mark

What will be the output of the following code?

Select the correct answer

question mark

You must always specify the index parameter when creating a Series.

Select the correct answer

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 1. Capitolo 2
Siamo spiacenti che qualcosa sia andato storto. Cosa è successo?
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