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Pandas First Steps
Pandas First Steps
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.
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.
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
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.
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.
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
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.
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.
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu 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.
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.
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo