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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:

python
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!

SectionΒ 3. ChapterΒ 4
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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