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  • 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

wilsonzhang746

Python

Using for loop through a list in Python

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! Looping in Python provides a feasible way to deal with each element of an object for particular operations using just a single block of statements. A for loop handling Read more…

By wilsonzhang746, 1 yearJune 4, 2024 ago
Python

Introducing string variables in Python

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! String variables in Python are data objects encapsulated in double or single quotes. For example we can create a string variable ‘msg’ and print it out in the following Read more…

By wilsonzhang746, 1 yearJune 3, 2024 ago
R Advanced Data Management

Introduction of S3 class in R programming

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! S3 class system is the most used R object oriented programming mechanism. The calling of ‘S3’ comes from the third version of S, which is the ancestor of R Read more…

By wilsonzhang746, 1 yearJune 2, 2024 ago
R Data Structure Dataset

Create, index and modify lists in R

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! List is a type of data objects in R. It can store different types of data objects into one object. You can combine scalars, vectors, matrices, data frames, and Read more…

By wilsonzhang746, 1 yearJune 1, 2024 ago
R Basic Data Management

How to create, index and modify data frames in R

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! Data frame is the most widely used data object in R programming, due to the fact that a data frame can store different type of data contents (numeric, character, Read more…

By wilsonzhang746, 1 yearMay 30, 2024 ago
R Basic Data Management

Some useful functions for working with objects in R

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! In this post, we will introduce and provide several useful and important functions in R. Most of them are fairly basic, and frequently used in data analysis with R Read more…

By wilsonzhang746, 1 yearMay 26, 2024 ago
R Basic Data Management

Using with() function to simplify your work 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 and often easier way to deal with data management and analysis. Say we have a data frame ‘grade’, and want to calculate Read more…

By wilsonzhang746, 1 yearMay 25, 2024 ago
R Basic Data Management

Variable type and conversion in R

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! In R programming, variable type can be numeric or character. Categorical variables are usually called factors. R provides a series of functions working with specific type test and type Read more…

By wilsonzhang746, 1 yearMay 24, 2024 ago
Statistics Using Python

Calculate mean, median and mode using Python

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! Mean, median and mode are three statistics that measure the central tendency of numerical data. Mean is the average of sample, and median the mid point of the sample Read more…

By wilsonzhang746, 1 yearMay 21, 2024 ago
R Advanced Data Management

Environment system in R programming

We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! R’s environment system behaves as a hierarchical folder system where objects in an R session are located. So when a R session is started, and with several objects created, Read more…

By wilsonzhang746, 1 yearMay 19, 2024 ago

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