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- R Course Source FilesDownload R Course code source files.
R Programming
- DplyrR tidyverse frame, and Dplyr plackege. Using pipe structure to chain fucntions together. Filter commands of Dplyr in R Arange functions of Dplyr in R, Rename the column name in R using Dplyr, Mutate, Select to Choose Variables/Columns, Joins, Slice, Summarise, Gather, Spread , Separate , n(),Nth,n_distinct() , na_if, coalesce , Ranking functions , Sampling, count , case_when , Group By .
- ggplot2R graphic plackage ggplot2. Introduction of ggplot2, Start building a graph and Add Geoms in ggplot() , Using Grouping, Using Scales , Using Facets , Formulate Labels, Formulate Themes , Graphs as objects , Saving graphs , Bar charts, Pie charts , Histograms , Box plots, Kernel density plots , Violin Plots , Scatter plots , Dot plots , Stem and Leaf Plots , Tree maps , Lollipop , Diverging Bars , Colorful Display of Categorical/Character Frequencies , Nested Pie Chart using plotly , Bubble Plot , step chart , Heatmap.
- R Advanced Data ManagementThis section and category includes mainly intermediate and more advanced techniques for R data analysis. It specially involve R mathematical functions, R Statistical functions, Probability functions in R, and R Character functions. Apply function as well as in this family, descriptive statistics, and table function family are talked about in this section too. We will also focus on how to write your own functions in R, and how to use control flow. In addition, some frequently used techniques such as reshaping, aggregating dataset are introduced.
- R Basic Data ManagementR basic data management contains recode and rename variables, sorting , sorting data, handling missing values, using data values. There are also reshaping data, merging data , and subset of data frame in this category.
- R Data Structure DatasetThis section introduces R data structures: One-dimensional data structure Vector; 2-dimensional data structure Matrix; n-dimensional data structure Array; tabular data structure Data Frame; and data structure List which can store any other type data objects. And this section also introduce how to create R data structure: using read.table() function to read text or csv files to create a data frame; using read.csv() function to read csv file to create a data frame. This section also introduces several functions: with().
Python
- NumpyNumpy module, ndarray, data type.Numpy array include creation of ndarray, and indexing , slicing of the array, and broadcasting array, reading data to return array, etc.
- PandasPython Pandas module. Data structure Series, Data Frame.
- Python ClassObject oriented programming in Python uses class. Class definition contains attributes, methods creation. Particular objects(instance) belonging to a class can be created by call a class, or instantiation. The attributes of an object can be directly assigned a new value, by using methods defined in class, etc.
- Python dictionaryDictionary is a data object type in Python. It stores key-value pairs information. The creation of a dictionary uses braces.
- Python FunctionFunctions in Python a block of code doing some specific job. Python uses def keyword to define a function. A function can contain argument, default value for the arguments, etc. Functions can be called when it is doing real tasks. And parameters are passed to the function when it is called.
- Python ListIntroducing lists Changing, Appending,Removing items of Lists . Sorting lists. Looping through a list. Making Numerical Lists . List comprehension and Working with Part of a List. Tuples. Building sets. Removing items from a set – remove(), pop(),and difference. Using a while Loop with Lists. Set operation.
- Python loopingfor and while loop in Python
- Python Machine LearningMachine learning algorithms in Python programming. The topics include document sentiment analysis, logistic regression, linear regression, and computer vision, CNN, RNN with PyTorch, Tensorflow.
- Python StringPython denotes information stored in quotes are string, no matter it is number or words inside the quotes. Both double quotes and single quotes can be used to create a string.
Statistics
- Statistics distributionStatistical distributions contains both continuous and discrete random distributions. Discrete distributions include binomial, Poisson, Hypergeometric, Negative Binomial, Geometric. Continuous distributions contain Normal, Exponential, Gamma, Beta, Chi-square, Lognormal, t, F, and Weibull distribution.
- Statistics Using PythonDoing and discovering statistics using Python programming. Python functions handling calculating the density, cumulative probability, quantile and random number generation for different statistical distributions: Normal distribution, t distribution, gamma distribution, chi-square distribution, F distribution, beta distribution, Hypothesis testing, etc. Linear regression and Generalized linear models using Python programming. ANOVA, factor analysis using Python programming. Clustering model using Python programming.
- Statistics Using RDoing and discovering statistics using R programming. R functions handling calculating the density, cumulative probability, quantile and random number generation for different statistical distributions: Normal distribution, t distribution, gamma distribution, chi-square distribution, F distribution, beta distribution, etc. Linear regression and Generalized linear models using R programming. Discrete choice modeling using R programming. ANOVA, factor analysis using R programming. Clustering model using R programming.
Course
- Course Registration
- Course InstructorCourse instructor introduction
- R Basic CourseR fundamental programming course.
- Python Basic CoursePython Basic Course

R Programming

Course registration link:

https://rdatacode.com/contact-us/

R programming tutorials includes two parts. Part 1 focus on R programming fundamentals. There are following sections in this part: Get started with R and RStudio environment; R data structure and create datasets; R data management basic methods; R data management advanced methods; Data visualization with ggplot2 package; Data analysis with dplyr package; Working with string and text mining. Part 2 focus on Statistical data analysis using R programming.

How to use arrange() function in R to sort dataset

We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! arrange() function from Dplyr package in R provides an alternative way as sort() function in R base installation for sorting a data frame with respect to variables, either Read more…

By wilsonzhang746, 1 yearJuly 9, 2024 ago

Dplyr

How to use filter() function to select observations in R

We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Dplyr is a package in R. It belongs to Tidyverse framework, and is allowed to use pipeline structure to chain multiple operations together into one statement. There are Read more…

By wilsonzhang746, 1 yearJuly 8, 2024 ago

Python

Nesting dictionary in Python

We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Dictionary in Python is a useful data object that stores key-value paired information. It can be nested, combined with lists or with dictionaries. In this post, we briefly Read more…

By wilsonzhang746, 1 yearJuly 6, 2024 ago

R Programming

Power analysis for t-test using R

We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Power analysis is a part of planning analysis for experimental design. It is usually used to determine the minimum sample size required to detect a specified effect with Read more…

By wilsonzhang746, 1 yearJune 30, 2024 ago

R Advanced Data Management

How to generate descriptive statistics in R

We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! When we have a data set on hand, the first step of data analysis is usually drawing descriptive statistics. The most common descriptive statistics for numerical variables are Read more…

By wilsonzhang746, 1 yearJune 29, 2024 ago

R Advanced Data Management

Some basic mathematical functions in R

We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! In this post, we list some of the most common mathematical functions in R. abs() – compute absolute value of a numerical input. sqrt() – compute square root Read more…

By wilsonzhang746, 1 yearJune 28, 2024 ago

R Basic Data Management

How to modify data frame using transform() function in R

We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! Similar as with() function in R, transform() function provides a way to work on data frame with simplified code inside its block. transform() is mostly used to modify Read more…

By wilsonzhang746, 1 yearJune 27, 2024 ago

R Basic Data Management

How to transpose data objects in R

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! Tabular data objects in R can be easily transposed with t() function. In the following example, we create a matrix of 2 rows and 3 columns, then transpose it, Read more…

By wilsonzhang746, 1 yearJune 26, 2024 ago

R Basic Data Management

Using with() to simply your object operations in R

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! with() function in R provides an alternative way of carrying out several operations bypassing inputting object name repeatedly. For example, we have a data frame ‘grade’ on hand, and Read more…

By wilsonzhang746, 1 yearJune 25, 2024 ago

R Advanced Data Management

How to use apply() function in R

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! apply() function in R programming is used to perform a specified function, either a R base installation function or an user-written function, to the rows or columns of a Read more…

By wilsonzhang746, 1 yearJune 23, 2024 ago