R-Tutorials Training
Let s get your data in shape!
Data Pre–Processing is the very first step in data analytics. You cannot escape it, it is too important. Unfortunately this topic is widely overlooked and information is hard to find.
With this course I will change this!
Data Pre–Processing as taught in this course has the following steps:
1. Data Import: this might sound trivial but if you consider all the different data formats out there you can imagine that this can e confusing. In the course we will take a look at a standard way of importing csv files, we will learn about the very fast fread method and I will show you what you can do if you have more exotic file formats to handle.
2. Selecting the object class: a standard data.frame might be fine for easy standard tasks, but there are more advanced classes out there like the data.table. Especially with those huge datasets nowadays, a data.frame might not do it anymore. Alternatives will be demonstrated in this course.
3. Getting your data in a tidy form: a tidy dataset has 1 row for each observation and 1 column for each variable. This might sound trivial, but in your daily work you will find instances where this simple rule is not followed. Often times you will not even notice that the dataset is not tidy in its layout. We will learn how tidyr can help you in getting your data into a clean and tidy format.
Instructor Details
Courses : 4
Specification: R Data Pre-Processing & Data Management – Shape your Data!
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26 reviews for R Data Pre-Processing & Data Management – Shape your Data!
Add a review
| Price | $14.99 |
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| Provider | |
| Duration | 6.5 hours |
| Year | 2018 |
| Level | All |
| Language | English |
| Certificate | Yes |
| Quizzes | No |
$14.99
Madhubanti Nath –
very well structured course. learnt a lot.
Patrick Fritz –
Great course to look at managing data in R. Good use of exercises.
Tchouakam Kouekam Herve –
So far the general introduction into the course is okay
Szymon Szumia –
Bardzo dobrze przemy lany i przyst pny kurs.
Maria Caro –
Well structured course with clear explanations and examples. In my opinion this is how an online course should be taught. However, you need to have some knowledge of R to better follow up the instructor.
Biju Soman –
very useful
Huub Kuypers –
De cursus ging van eenvoudig naar moeilijk. De eenvoudige zaken werden te uitgebreid uitgelegd. Ik had ook meer info over SQL willen hebben
Farooq Anwer –
The course is presented in a simple way which is easy to understand and follow. However certain concepts such as date and time in difference time zones is a new concept for learners who usually work with local data sets.
Enrique Lamarque –
Really good and clear course. Finally we can see some real points!!
Nathan Young –
Data Pre processing is often 80% of a project. This course covers some key libraries and functions that will make an analyst much more efficient
luuk geraets –
A clear explanation of every exercise which gives a great introduction to R
AnthonyL –
As close as you can image to what you’d be do’n in the real Data environment.
Bernd Hipfel –
Lot’s of information to keep in mind for future usage. But far too many exercises instead of a little better explanations of concepts and usage of functions.
Eric Medeiros –
Very nice didactic, full of exercises, and show where to get more
Kindra Martinenko –
I found this to be a very comprehensive overview of pre processing and data management for the R Programming language. I am a professional practitioner of R with little formal programming experience or training. This course helped me understand the foundational concepts of the R programming language in addition to more advanced methods for big data management and working with messy data. Some sections need to be updated to carry over some changes made to some packages required for the exercises and examples to work properly. If you’re taking this course, I recommend taking note of the version of R you’re using and understand that some packages may not function properly or need to be updated.
Paula Junior –
Thus far, the imformation is clearly explained. The importance of understanding and knowing the process of cleaning data before visualization has been demonstrated.
Dhirendra Singh –
Need more practical scenarios examples as reference materials
Barbara Leighnor –
I really appreciated all the opportunities for practice
Frederico M Cohrs –
Claro que s o in cio. Eu esperava um curso do tipo m os na massa. Como s o in cio, vejamos a sequ ncia.
Arief Yudaprawira –
Very helpful in their daily application of data processing
Bronwyn Barker –
excellent course!
Columbus Ohaeri –
good course, just about met my expectation
Jaroslaw Dziegielewski –
Rather good, but some info not updated (e.g. olson time zones was removed from lubridate few years ago).
Debdip Roy –
Complex queries are not simplified in many cases , if you are expecting all exparts to join your course , please do mention the same. does not make sense
Channing Powers –
Great course. Very informative!
Channing Powers –
This course is a must for anyone planning to work in the Data industry, using the R programming language.