DataFrame

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              123456
            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)

Task

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Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. Give it a try!

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 4

DataFrame

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              123456
            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)

Task

Swipe to show code editor

Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. Give it a try!

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 4

DataFrame

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              123456
            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)

Task

Swipe to show code editor

Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. Give it a try!

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Series is the simplest data structure in pandas. Now let's delve into a more complex data structure: DataFrame. This is a two-dimensional object that is more commonly used.

Think of a DataFrame as akin to a spreadsheet, capable of containing large volumes of data. Like a spreadsheet, a DataFrame comes with an index and columns.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() function. Let's examine how the coding is executed.


              123456
            
import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)

Task

Swipe to show code editor

Let's craft an animal DataFrame using the dataset data and the pd.DataFrame() function. Give it a try!

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 1. Chapter 4

Switch to desktop for real-world practiceContinue from where you are using one of the options below