#Distribution

Following up on the information presented in the post “Descriptive Statistics”, below, we will know the most basic ways to visualize the data or information to be analyzed. Specifically: Pie chart Line chart Treemap & Subburst Histograms & Bar charts Density plot Boxplots Violin plots Scatter plots Pareto chart Note: All the examples (except for the line graphs due to its features) are based on the train.csv dataset file, which is a subset of 891 representative individuals of the population of the Titanic used for the training of models of Machine Learning. [Read More]

As a starting point in data analysis, it is necessary to know some mathematical and statistical foundations in order to work with the information to be analyzed. Thus, we will start learning some basic concepts: Population, Samples, Individuals and Variables: Population: The set of all the elements under study Sample: A subset of elements of the population (it should be representative of the population) Individuals: Every individual element in the popularion Variables: Characteristics of the individuals Example: Titanic Dataset [Read More]