Worked these days with Dataquest and command lines. Also with histograms in Python and distributions like Normal and Uniform. An interesting observation about boxplots:
A value is an outlier if:
- It’s larger than the upper quartile by 1.5 times the difference between the upper quartile and the lower quartile (the difference is also called the interquartile range).
- It’s lower than the lower quartile by 1.5 times the difference between the upper quartile and the lower quartile (the difference is also called the interquartile range).
This site https://fivethirtyeight.com/ presents cool graphs and statistics and it would be helpful to occasionally read some articles!
Also I worked with some command lines like the following:
cd /home/dq/practice/wildcards
mkdir html_files archive data
mv *html html_files
mv 201[!9]* archive
mv *csv data
mv /sqlite-autoconf-3210000/tea/win/you_found_it.b64 /home
Also continued with presenting the NY schools project in a jupyter notebook in order to upload it in my Github profile. I try to understand everything I do and not just copy the code.
Angelo's progress in data analysis 