Learn Data Wrangling with Python
Learn how to wrangle data with Python! This course will teach you how to import data from CSV and Excel files, calculate the size of a dataset, investigate the first and last records, search for missing data, handle missing data, search for records with specific values, filter records using multiple filters, use conditions to filter records, sort items in ascending and descending order, divide a dataset column, combine data frames into a dataset, concatenate two columns into one column, and save a dataset in CSV or Excel format. Enroll now and become a data wrangling expert! ▼
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Course Feature
Cost:
Free
Provider:
Udemy
Certificate:
No Information
Language:
English
Course Overview
❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [June 30th, 2023]
This course provides an introduction to data wrangling with Python. Students will learn how to import a CSV or Excel file into a local dataset, import data from CSV and Excel files using a URL, calculate the size of a dataset, investigate a dataset's first and last records, investigate the datatypes of a dataset's features, search a dataset for missing data, handle missing data in a dataset, search a dataset for records with specific values, filter records from a dataset using multiple filters, use conditions to filter records from a dataset, sort items in ascending and descending order, divide a dataset column, combine data frames into a dataset, concatenate two columns into one column, and save a dataset in CSV or Excel format.
[Applications]
After taking this course, learners can apply their knowledge of data wrangling with Python to import, investigate, handle, filter, sort, divide, combine, and save datasets in CSV or Excel format. They can also use conditions to filter records from a dataset and concatenate two columns into one column.
[Career Paths]
One job position path that is recommended for learners of this course is Data Wrangler. Data Wranglers are responsible for preparing data for analysis by cleaning, transforming, and organizing it. They must be able to identify and correct errors in data, as well as identify patterns and trends. They must also be able to use various software tools to manipulate data, such as Python, SQL, and Excel. Data Wranglers must also be able to communicate their findings to stakeholders in a clear and concise manner.
The development trend of Data Wrangling is increasing as more and more organizations are recognizing the importance of data-driven decision making. Companies are investing in data wranglers to ensure that their data is accurate and up-to-date. As the demand for data wranglers increases, so does the need for more advanced skills and knowledge. Data wranglers must stay up-to-date with the latest technologies and trends in order to remain competitive in the job market.
[Education Paths]
The recommended educational path for learners of this course is a Bachelor's degree in Data Science. This degree program typically includes courses in mathematics, statistics, computer science, and programming, as well as courses in data wrangling and analysis. Students will learn how to use Python to import, clean, and analyze data, as well as how to use data to make decisions and solve problems. They will also learn how to use data visualization tools to present their findings. As the demand for data-driven decision-making increases, the development trend of this degree program is to focus on the application of data science in various industries, such as healthcare, finance, and marketing.
Course Syllabus
Reading Data
Data Exploration
Standardisation
Syntax Errors
Irrelevant Data
Duplicates
Missing Data
Filtering
Sorting
Concatenation
Outliers
Pros & Cons
New concepts in Python for understanding data coding.
Clear content and easy-to-follow examples.
Appropriate challenges for learning data cleansing tasks.
Outdated course with code adjustments required.
Inconsistent solution and challenge documents.
Some missing sections in the solution document.
Course Provider
Provider Udemy's Stats at AZClass
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