## Calculating Vacancy Concentration with Python

In this post, we will complete a problem that might come up in an introductory Materials Science and Engineering class. We'll calculate the number of vacancy defects in a material using Python.

The following is a calculation of the number of vacancy defects in a material. All crystalline and poly-crystalline …

## Estimating the Deflection of a Truncated Cone using Python

In this post, we will complete a problem that might come up in a Strength of Materials class. We'll estimate the deflection of a truncated cone given an applied load using Python.

### The Problem¶

Below is an engineering mechanics problem that can be solved in Python. Follow along this post …

## Bar charts with error bars using Python, jupyter notebooks and matplotlib

Bar charts with error bars are useful in engineering to show the confidence or precision in a set of measurements or calculated values. Bar charts without error bars give the illusion that a measured or calculated value is known to high precision or high confidence. In this post, we will build a bar plot using Python, the statistics module and matplotlib. The plot will show the tensile strength of two different 3-D printer filament materials, ABS and HIPS. We will then add error bars to the plot based on the standard deviation of the data.

## Bar charts with error bars using Python and matplotlib

Bar charts with error bars are useful in engineering to show the confidence or precision in a set of measurements or calculated values. Bar charts without error bars give the illusion that a measured or calculated value is known to high precision or high confidence. In this post, we will build a bar plot using Python and matplotlib. The plot will show the coefficient of thermal expansion (CTE) of three different materials based on a small data set. Then we'll add error bars to this chart based on the standard deviation of the data.