In this article I would like to concentrate on 4 main measures of statistical dispersion: range (and the biggest and the smallest number as well), average deviation, variance and standard deviation. In Python, we can easily compute them with a…

In this article I would like to concentrate on 4 main measures of statistical dispersion: range (and the biggest and the smallest number as well), average deviation, variance and standard deviation. In Python, we can easily compute them with a…

Tagged with: average deviation, functions, python, range, standard deviation, statistics, variance

Posted in data analysis, python

Posted in data analysis, python

In the central tendency there are 3 most common measures: mean (arithmetic average), median and mode. Their manual calculation in Python is presented below. Mean Arithmetic mean is a sum of a collection of numbers divided by the total number…

Previous articles concentrated on managing and visualizing data with numpy and mathplotlib.pyplot libraries. Now, it is time to count more statistics, but manually, without built-in functions. For the beginning, let’s write some code to show a frequency distribution of the…

This study shows graphically the distribution of crater morphologies, crater location plot and relationship between diameter and depth of a crater. The Python program below should call the graphs, but unfortunately it is impossible due to traceback error (the matplot.pyplot…

Tagged with: coursera, data analysis, mars, python, research project

Posted in data analysis, python

Posted in data analysis, python

There were 3 variables worked out in this Python program: diameter of a crater (DIAM_CIRCLE_IMAGE), depth (DEPTH_RIMFLOOR_TOPOG) and ejecta morphologies (MORPHOLOGY_EJECTA_1,ย MORPHOLOGY_EJECTA_2). Below you can find the output of this program: counts and percentages for chosen variables. To have better organized…

Tagged with: coursera, data analysis, mars, python, research project

Posted in data analysis, python

Posted in data analysis, python

All observed craters on Mars were investigated in terms of several characteristics, like ejecta morphology, depth of the crater or number of layers.ย This Python program prints frequency distributions for 3 above mentioned variables: MORPHOLOGY_EJECTA_1, DEPTH_RIMFLOOR_TOPOG and NUMBER_LAYERS. Below you can…

Tagged with: coursera, data analysis, mars, python, research project

Posted in data analysis, python

Posted in data analysis, python