Course Content
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.
Task
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.
Thanks for your 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.
Task
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.
Thanks for your 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.
Task
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.
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.
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
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.