What is Data Wrangling? | Data Wrangling with Python | Data Wrangling | Intellipaat
114To analyze data, manipulation is essential. Of course, we don't mean the deceitful kind; we mean the data kind!
All of these tasks involve manipulating data in some way, whether it be by scraping data from the web, performing statistical analyses, or making dashboards and visualizations.
This video on "What Is Data Wrangling?" will help ease your fears, as it improves data usability by converting it to make it compatible with the end system. So, let's get started with this Data Wrangling Tutorial for beginners!
What is Data Wrangling?
The initial phases of the data analytics process are often referred to as "data wrangling." It entails converting and mapping data between different formats.
The goal is to increase data accessibility for applications like business analytics and machine learning.
Numerous tasks may be involved in the data wrangling process.
These include activities like gathering data, conducting exploratory analysis, cleaning up the data, building data structures, and storing the data.
Why Data Wrangling?
The knowledge acquired through the data wrangling process can be extremely valuable.
They'll probably have an impact on how a project develops going forward.
Poor data models will be produced as a result of skipping or rushing this step, which will affect an organization's decision-making and reputation.
Data wrangling tools organize and transform data to meet the needs of the target system in order to make it usable for the final processes.
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Following topics are covered in this session:
00:00 - Introduction to Data Wrangling
01:16 - What is Data Wrangling?
02:42 - Steps invovled in Data Wrangling
07:56 - Getting Started with Python Libraries
10:11 - Hands-On
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