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eraldagjika

Eralda Gjika Dhamo

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Plotly - World data Population- GDP and Life Expectancy
Adding Population evolution to the two main variables and dynamic Plotly ! Find more information on datasets and code here: https://github.com/EGjika/GDP-vs-Life-Expectancy-with-Plotly/tree/main
GDP per Capita vs Life Expectancy Over years 1960-2022
This dynamic Plotly shows how the GDP per Capita and Life Expectancy evolves over years for countries over the world. It shows the dynamics of changes and can be modified to filter specific countries and/or specific regions. Full code and data may be found here: https://github.com/EGjika/GDP-vs-Life-Expectancy-with-Plotly
Netflix text Analysis with R
This material will show you an introduction to sentiment analysis with R. tidyr and tidytext together with dplyr and ggplot will be used to get a better information about. There are many things you may do with this dataset. just try to combine your knowledge in data wrangling and visualization with R as well! Enjoy!
Matrix-Dataframe and DPLYR all in one
This material shows all in one the use of Matrix, dataframe and DPLYR functions. Applications to the 50 state dataset of USA. Note: comments are missing but the logic is easy to follow.
Text Mining word2vec
Application of word2vec function in analyzing similarities between words.
Sentiment Analysis in Beatles Album
This is a project done in Beatles Album and within the songs to analyse their sentiments over the years, between albums and songs. tidytext and tidyverse are the main libraries used. Enjoy!
Intro to vectors
A brief into to vectors.
Missing observation and data wrangling
An example of how to deal with NAs and merge-filter-select functions in R.
THE POWER
This material is a short presentation at THE POWER -WORKSHOP. Tirana, 15-16 October 2021
Introduction to R- Matrices, Arrays and linear equation solver
In this material you will find useful functions for sets and subsets. Then an introduction to matrices is presented through examples (manipulations with rows and columns) . Arrays are also mentioned and how to solve linear equations in R is presented. Enjoy it!
Introduction to R- Declaration and Vectors
This material will help you start understanding the syntax used for declaration of objects in R. It has examples of how to work with vectors in R, sort, order, create sequences and more. (Matrices and dataframes are coming in the next publication). Also, through examples and exercises it is a very organized material to work / learn by your self. If you like it please share! Enjoy!
Regression Trees and Tree based Methods- Hitters dataset
Hitters dataset is used to show some basic regression trees and classification models. Pruning process and also accuracy of the models is performed. Prediction using a train data and a test data is also explained. Enjoy!
Fitting Probability distribution in R
In this session you will find how the fitdistrplus package is used to fit probability distributions to a real data vector. (a numeric data) Basic distributions such as: Normal Distribution, Log-normal, Logis, Exponential, Negative Binomial, Poisson, Weibull etc. are used to perform the estimation phase and then the goodness of fit statistical test and AIC/BIC PS:Data used are from a cyber attack dataset (the link is in the material) Enjoy!
Simulation and Probability Distributions in R
This is a material where the basic discrete and continuous probability distributions are presented with examples and also graphical visualizations. Histograms, density plot are used to observe the simulations and changes based on the sample size. It is a basic material for those who wish to start working with probability distributions in R. Enjoy it!
Linear models and diagnostic
In this material you may find steps of building a simple linear model , a multiple linear model, adding an interaction term and quadratic models. Also functions and libraries on how to do a diagnostic evaluation of the models. Enjoy it!
Graphics in R-library ggplot2
Working with banking dataset and a Covid-19 dataset imported from European center for Disease. Histograms, boxplot and grouping by a categorical variable are shown. Enjoy!
Data Wrangling and Graphics in R
In this material you will have the opportunity to work on data wrangling with libraries such as: dplyr; tidyverse, tidyr Also you will have the opportunity to work with basic graphics in R. At the end of the material the Esquisse library is presented to obtain beautiful graphs through "ggplot" library. As an example is used a banking dataset which may be downloaded from the link in the material. Hope you enjoy it!
Dates and Times manipulation in R
This material shows some examples on how to create dates/time format in R using some of the packages such as: lubridate dplyr tidyverse xts It also show some data manipulations using the pipe operator %>% . Thank you for reading it!
Merry Christmas and happy New year 2021
A little contribution from the Department of Applied Mathematics, Faculty of Natural Science. Best wishes to all R-LOVERS!!!
Correlation and linear regression models in time series
Correlation among time series variables are analyzed and correlation plot are presented. The example is executed in Albanian yearly time series data obtained from the World Bank web page.
Benford and Blondeau distribution for Albania-COVID-19-data
Using BeyondBenford package in R which allows to compare the goodness of fit of Benford's and Blondeau Da Silva's digit distributions in a dataset. It is used to check whether the data distribution is consistent with theoretical distributions highlighted by Blondeau Da Silva. The codes are applied for the Albanian COVID-19 data for a period from 31 December 2019-12 October 2020. This is an ongoing project. Mail:eralda.dhamo@fshn.edu.al
Benford Law and Probability Simulations in Cyber Attacks Dataset
These examples are a simulations of Benford law and a cyber attack data set is used for controlling the Benford law in real data. The explanations are in english and albanian language. Then some probability distributions are fitted to the data and used for estimation of probability an event will occur in the future. Reference for data set: https://osf.io/mv98y/
Sampling methods
these is a material where Sampling methods are applied at "credit" dataset: Simple random Sampling Stratified Sampling Systematic Sampling Comparing samples
COVID-19_Evolution of new cases and deaths in Balkan-Europe
The codes show how to obtain some graphical representation of the COVID-19 evolution numbers in Balkan region, in European countries and World. ggplot package and many other packages in R are used to improve the view of the graphs and numbers. Please if you find it helpful share and mention it @eraldagjika or tag #eraldagjika. Thank you!
Markov Chain example in R
This is a Markov chain example in R using the library(markovchain). explanations are in Albanian language to help in understanding the functions of "markovchain" library. Hope it helps to new R users and especially those who are interested in Markov chain models.