HistogramsĪs awesome as box plots are, they don’t tell the whole store regarding numeric data. Now that’s what I call a powerful data visualization. Versicolor Petal Widths are mostly disjoint from Virginica Petal Widths.There is no overlap in Setosa Petal Widths at all!.Whoa! Here’s what pops in this data visualization: Things get even more interesting for the box plot of Petal Width: Excel Box Plot There is overlap of the boxes across the three categorical labels.There is overlap of the “T” bars across all three categorical labels.Take for example the following box plot that visualizes Sepal Width for each label: Excel Box PlotĮven without knowing the specific of how box plots work (see Wikipedia link above for more details), the visualization conveys so much more information than a pivot table: While a pivot table can provide you some insight into the numeric data using calculations like the minimum/max value and the average, box plots offer so much more. In the case of the iris data set, the categorical labels are the Species: Setosa, Versicolor, and Virginica. Box plots are super useful for visualizing numeric data in terms of categorical labels. Recent versions of Excel support the creation of box plots. While pivot tables are immensely useful, you can do better with Excel data visualizations. In particular, the differences in average Petal Length are quite striking.The average measurements of Versicolor and Virginica seem to be similar.
The average measurements for Setosa are dissimilar compared to the average measurements of Versicolor and Virginica.The data is evenly distributed around the three species types (I mentioned this above, but you get the idea).The above pivot table provides some valuable first-pass insights into the data:
Here’s an example pivot of the iris data set: Iris Data Excel Pivot Table That being said, I want to contrast pivot tables as a non-visual analysis technique with visual techniques.
#Create random floor generator exce;l how to
If you don’t know how to use pivot tables, they are a great place to start your data literacy journey. As such, I want to be clear on this – Excel pivot tables are wildly useful. Arguably, Excel pivot tables are the single most common form of data analysis. Data Literacy with Excel: Pivot TablesĪlmost everyone in the working world is familiar with Excel pivot tables. In the following sections I will illustrate how easy hands-on data literacy with Excel can be. The following table is random sample illustrating the data: Sepal Length For each observation there are 4 measurements (i.e., 5 variables total) of each flower. The iris data set consists of 150 observations (rows) of data with 50 observations each for 3 different iris species – setosa, versicolor, and virginica. Data Visualization Scenarioįor this post I will leverage the world-famous iris data set as the raw materials for the data visualizations. The human brain is optimized for visual pattern recognition and you can use trusty ol’ Excel to visually analyze your data. In the below example in cell C2, enter =RANDBETWEEN(1,1000).Ĭopy the formula down to the bottom of the range.A fundamental aspect of achieving data literacy with Excel is effective use of data visualization. Put your cursor in the cell in which you want to get the random numbers. We follow the following steps to generate random numbers using RANDBETWEEN: The result will give you a whole number which falls between the low and the high numbers.Īs an example let’s say we want to generate numbers between. RANDBETWEEN function takes two arguments – the start value (lower number) and the end value (higher number).
Excel RANDBETWEEN function generates a set of integer random numbers between the two specified numbers. The key worksheet function to perform the random generator is a formula call RANDBETWEEN. That way when you put the real data in you will know that the formula works on the random data set. One key aspect of testing any data set is the ability to quickly and easily generate random numbers in Excel.Īs an example you may wish to generate a dummy data set made up of completely different numbers to test formula on. Adding a Unique Random Number within a Range