singhai0

javascript:%20var%20array%20=%20document.URL.match(/amazon%5C.(.*?)%5C/.*?%5C/.*?%5C/(.%7B10%7D)/);%20if%20(array%20==%20null)%20%7B%20alert('Sorry,%20this%20doesn%5C't%20appear%20to%20be%20an%20Amazon%20book%20page.');%20%7D%20else%20%7B%20var%20x%20=%20window.location.replace('https://www.goodreads.com/review/isbn/'+%20array%5B2%5D%20+%20'?tld='%20+%20array%5B1%5D%20+%20'&from=bm',%20'add_review');%20x.focus();%20%7D

singhai0

Mapping earthquakes in Python 3.x using matplotlib and matplotlib's basemap

(with a big assist from Anaconda)

I currently use Python for nearly all of my data science and wrangling work these days but usually find myself switching to R to visualize data using ggplot2. This is due in part to ggplot2's general excellence, but also because I had a lot of trouble learning Python's most popular viz library, matplotlib on my own...its homepage is decent enough...but its variety of plotting APIs (--pylab? OOP? %matplotlib???) has led to widely differing examples and best practices among the many online matplotlib guides (not dissimilar to the general problem of trying to practice either Python 2.x or 3.x).

That changed yesterday when I stumbled across [Nicolas P. Rougier's beautifully designed and com

singhai0

function stashbox() {
  local branch_name=$(git stash list | fzf --ansi -m --preview "echo {} | cut -d':' -f1 | xargs -I % sh -c 'git stash show --color=always % | less -R'")

  if [[ $branch_name ]]; then
    echo $branch_name | cut -d':' -f1| xargs git stash pop
  fi
}

Courtesy: https://github.com/Brantron