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Learn Exploring the Dataset | Analyzing the Data
Pandas First Steps

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Exploring the Dataset

In pandas, there's a handy method named info() that provides basic information about a dataset.

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import pandas as pd # It's a dataframe df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/example.csv') info = df.info() print(info)
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This method displays the number of rows and columns in the DataFrame, as well as each column's name and data type. For instance, df contains 20 rows and 5 columns.

To determine the length of the DataFrame, we can use the len() function, as demonstrated in the example below:

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Task

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You are given a DataFrame named wine_data.

  • Get more detailed information about this dataset and store the result in the information variable.

Solution

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SectionΒ 3. ChapterΒ 4
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book
Exploring the Dataset

In pandas, there's a handy method named info() that provides basic information about a dataset.

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

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

To determine the length of the DataFrame, we can use the len() function, as demonstrated in the example below:

python
Task

Swipe to start coding

You are given a DataFrame named wine_data.

  • Get more detailed information about this dataset and store the result in the information variable.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

close

Awesome!

Completion rate improved to 3.03

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