Practice and Solution Notebooks included.

What you'll learn

To load a local dataset from CSV and Excel files.

To import a dataset from CSV and Excel files via a URL.

To detee the size of a dataset.

To explore the first and last records of a dataset.

To explore the datatypes of the features of a dataset.

To check for missing data in a dataset.

To deal with missing data in a dataset.

To filter for records with certain values from a dataset.

To filter records with multiple filters from a dataset.

To filter for records from a dataset through the use of conditions.

To perform sorting in ascending and descending order.

To split a column in a dataset.

To merge data frames to form a dataset.

To concatenate two columns to one column in a dataset.

To export a dataset in CSV and Excel formats.

Requirements

You will need to have basic python programming proficiency.

You will need a modern browser i.e. Google Chrome or Mozilla Firefox.

Description

By the end of this course, you will be able to:

Load a local dataset from CSV and Excel files.

Import a dataset from CSV and Excel files via a URL.

Detee the size of a dataset.

Explore the first and last records of a dataset.

Explore the datatypes of the features of a dataset.

Check for missing data in a dataset.

Deal with missing data in a dataset.

Filter for records with certain values from a dataset.

Filter records with multiple filters from a dataset.

Filter for records from a dataset through the use of conditions.

Perform sorting in ascending and descending order.

Split a column in a dataset.

Merge data frames to form a dataset.

Concatenate two columns to one column in a dataset.

Export a dataset in CSV and Excel formats.

Who this course is for:

This course is designed for professionals with an interest in getting hands-on experience with the respective data science techniques and tools.




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