Information on the Data

In pandas, there's a handy method named info() that provides basic information about a dataset. Let's explore how to use this method.


              12345
            
import pandas as pd
# It's a dataframe
frame = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/example.csv')
info = frame.info()
print(info)

This method displays the number of rows and columns in the dataframe, as well as each column's name and data type. For instance, our dataframe contains 20 rows and 5 columns.

To determine the size of our dataframe, we can use the len() function, as demonstrated in the example below.

Task

Swipe to show code editor

We have a DataFrame labeled data_frame. You need to get more detailed information about this dataset, such as the types of data it contains, any missing values (and their count), and the memory usage.

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 3. Chapter 4

Information on the Data

In pandas, there's a handy method named info() that provides basic information about a dataset. Let's explore how to use this method.


              12345
            
import pandas as pd
# It's a dataframe
frame = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/example.csv')
info = frame.info()
print(info)

This method displays the number of rows and columns in the dataframe, as well as each column's name and data type. For instance, our dataframe contains 20 rows and 5 columns.

To determine the size of our dataframe, we can use the len() function, as demonstrated in the example below.

Task

Swipe to show code editor

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 3. Chapter 4

Information on the Data

In pandas, there's a handy method named info() that provides basic information about a dataset. Let's explore how to use this method.


              12345
            
import pandas as pd
# It's a dataframe
frame = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/example.csv')
info = frame.info()
print(info)

This method displays the number of rows and columns in the dataframe, as well as each column's name and data type. For instance, our dataframe contains 20 rows and 5 columns.

To determine the size of our dataframe, we can use the len() function, as demonstrated in the example below.

Task

Swipe to show code editor

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

Everything was clear?

Thanks for your feedback!

In pandas, there's a handy method named info() that provides basic information about a dataset. Let's explore how to use this method.


              12345
            
import pandas as pd
# It's a dataframe
frame = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/example.csv')
info = frame.info()
print(info)

This method displays the number of rows and columns in the dataframe, as well as each column's name and data type. For instance, our dataframe contains 20 rows and 5 columns.

To determine the size of our dataframe, we can use the len() function, as demonstrated in the example below.

Task

Swipe to show code editor

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

Section 3. Chapter 4

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