Course
Reshaping Data with tidyr
- IntermediateSkill Level
- 4.8+
- 1.1K
Transform almost any dataset into a tidy format to make analysis easier.
Data Manipulation
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Course
Transform almost any dataset into a tidy format to make analysis easier.
Data Manipulation
Course
Master data manipulation and analysis techniques such as CASE statements, subqueries, and CTEs in Snowflake.
Data Manipulation
Course
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
Data Manipulation
Course
Learn how to create pivot tables and quickly organize thousands of data points with just a few clicks.
Data Manipulation
Course
Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.
Data Manipulation
Course
In this course, youll learn the basics of relational databases and how to interact with them.
Data Manipulation
Course
Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.
Data Manipulation
Course
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
Data Manipulation
Course
This course will show you how to integrate spatial data into your Python Data Science workflow.
Data Manipulation
Course
Analyze text data in R using the tidy framework.
Data Manipulation
Course
Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.
Data Manipulation
Course
Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.
Data Manipulation
Course
Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.
Data Manipulation
Course
Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.
Data Manipulation
Course
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
Data Manipulation
Course
Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!
Data Manipulation
Course
Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.
Data Manipulation
Course
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.
Data Manipulation
Course
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.
Data Manipulation
Course
Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.
Data Manipulation
Course
Learn how to identify, analyze, remove and impute missing data in Python.
Data Manipulation
Course
Explore ways to work with date and time data in SQL Server for time series analysis
Data Manipulation
Course
Learn the most important functions for manipulating, processing, and transforming data in SQL Server.
Data Manipulation
Course
Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.
Data Manipulation
Course
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
Data Manipulation
Course
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Data Manipulation
Course
Learn how to segment customers in Python.
Data Manipulation
Course
Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.
Data Manipulation
Course
This course will show you how to combine and merge datasets with data.table.
Data Manipulation
Course
Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.
Data Manipulation
Data science is an area of expertise focused on gaining information from data. Using programming skills, scientific methods, algorithms, and more, data scientists analyze data to form actionable insights.
You’ll need to learn a programming language such as Python or R and master the principles of math and statistics. Knowledge of data analysis methods and data science tools is also essential. There are many ways to learn data science. As well as formal means of education, such as a degree or university study, there are plenty of other resources to help you learn at your own pace. As well as online courses and tutorials, there are books, videos, and more.
As well as knowledge of mathematics and statistics, data scientists need programming skills in languages such as Python, R, and SQL. Additionally, data science requires the ability to work with large data sets, knowledge of data visualization, data wrangling, and database management. Skills in machine learning and deep learning can also be useful.
In a professional capacity, almost every industry can use data science to some degree. Healthcare organizations use data science to detect and cure diseases, while finance companies use it to detect and prevent fraud. All kinds of industries use data science for marketing, such as building recommendation systems and analyzing customer churn.
Yes, data science is among the fastest-growing sectors in the US and worldwide. It’s also one of the best-paid careers out there. According to data from Payscale, experience data scientists earn an average of $97,609 and have a satisfaction rating of four stars out of five in the US.
There are a few things to consider here. First, data science degrees can be competitive to get onto, often requiring consistently high grades. Similarly, many of the skills required for data science require a lot of study and patience. It can take several months to master all of the necessary basics, as well as a lot of practical experience to secure an entry-level position.
Yes, you’ll need some coding experience in languages such as Python, R, SQL, Java, and C/C++. However, due to its relatively simple syntax, Python programming language is often the preferred choice among newcomers.
For a person with no prior coding experience and/or mathematical background, it can typically take 7 to 12 months of intensive studies to be at the level of an entry-level data scientist. However, it is important to remember that learning only the theoretical basis of data science may not make you a real data scientist.
Once you’ve mastered the foundations of data science, you can then specialize in a variety of areas, including machine learning, artificial intelligence, big data analysis, business analytics and intelligence, data mining, and more.
Make progress on the go with our mobile courses and daily 5-minute coding challenges.