The the National Examinations Council of Tanzania publishes Primary and Secondary Education Examination Results. But the National Library Services archieve this results. While a fantastic resource for history primary and secondary school results, these records are painful to analyze using software because of the grades results is organized is untidy and in messy. You need to work on this column of the result to have a clean and right format dataset for exploration and modelling.

tidyverse While the base R packages includes many useful functions and data structures that you can use to accomplish a wide variety of data science task, the add–on tidyverse package supports a comprehensive data science workflow as illustrated in figure 1. Figure 1: Schematic drawing of the data science workflow Tidyverse is a coherent system of packages designed to address specific component of the workflow. Most of the package in the tidyverse were developed by Hadley Wickham [-@tidyverse], and many other contributors.

Introduction This chapter provides brief explanations of the fundamental vector model. You will get familiar with the theory behind vector model and the disciplines in which they predominate, before demonstrating its implementation in R. Vector is the most basic data structure in R. It is a sequence of elements of the same data type. if the elemenets are of different data types, they be coerced to a commontype that can accomodate all the elelements.

Kernel density estimation is a popular tool for visualizing the distribution of data. In this post, we are going to look on how to create smoothed map of random points. We will use a shapefile dataset that contains potential fishing zones derived from sea surface temperature recorded between January and June 2020 in Pemba channel. You can simply download the file from this link. Once you have downloaded the file, unzip and browse in the uncompressed file you find the shapefile pfz.

An ogive (oh-jive), sometimes called a cumulative frequency polygon, is a type of frequency polygon that shows cumulative frequencies. In other words, the cumulative percents are added on the graph from left to right. An ogive graph plots cumulative frequency on the y-axis and class boundaries along the x-axis. It’s very similar to a histogram, only instead of rectangles, an ogive has a single point marking where the top right of the rectangle would be.