Visualizing Your Data: A Guide to Selecting the Perfect Chart
Visualizing data is an important step in understanding and communicating findings. The correct chart can make a significant difference in presenting a clear, easy-to-understand message as opposed to a confusing jumble of information.
When working with data, it is important to understand the different types of data that maybe present. There are three primary categories: numerical, categorical and ordinal.
Numerical data is data that can be quantified such as numbers or measurements. Categorical data is data that can be divided into categories, such as colors or names. Ordinal data is data that can be ordered, such as levels of education or income.
After determining the nature of your data, you can proceed to choose an appropriate chart.
However choosing the right chart for your data can be a challenge. In this guide, we will explore the different charts available and how to select the perfect chart for your data.
Bar Charts: They are used to compare the values of different categories or groups. They are often used to compare the values of different products, services, or regions. For example, a bar chart can be used to shoe the sales of different products in a particular region.
Line Chart: They are used to show changes and trends over time, such as changes in stock prices or changes in the population of a city. They’re also used to compare the values of different groups, such as the sales of different products over time.
Pie Charts : They are used to show proportion of different parts of a whole. Such as the distribution of the population by age or the distribution of sales by product.
Scatter Plot: This type of chart is used to display the relationship between two variables, typically represented by a set of x and y coordinates.
Area Charts: This is used to trends and patterns over time, as well comparing different groups or categories. They can be used to show changes in data as stock prices, population growth or weather patterns.
Box plot: Also known box-and-whisker plot, provides an easy way to visualize the spread and skewness of a data set and also identify any outliers and unusual observations.
Bubble Charts: They are used to show relationship between three variables. They are similar to scatter plots but they add additional dimension by using the size of the bubbles to represent a third variable. Such as population, GDP, and CO2 emissions for different countries.
