In my previous post I mentioned that I got into Tech Leaders program. Now, after a few months I would like to relate my experiences of doing something unbelievable, which I’ve never thought I will be able to do. Tech…

In my previous post I mentioned that I got into Tech Leaders program. Now, after a few months I would like to relate my experiences of doing something unbelievable, which I’ve never thought I will be able to do. Tech…

Tagged with: career, data analyst, data streaming, peewee, python, research project, tweepy, Twitter

Posted in learning

Posted in learning

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, 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