alexisduque

alexisduque

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USEFUL ONE-LINE SCRIPTS FOR SED (Unix stream editor)        Dec. 29, 2005
Compiled by Eric Pement - pemente[at]northpark[dot]edu        version 5.5

Latest version of this file (in English) is usually at:
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alexisduque

#!/bin/bash

function code-up() {
  wget https://vscode-update.azurewebsites.net/latest/linux-deb-x64/stable -O /tmp/code_latest_amd64.deb 
  sudo dpkg -i /tmp/code_latest_amd64.deb
}

export -f code-up

alexisduque

[user]
	name = Alexis Duque
	email = alexisd61@gmail.com
	
[core]
	editor = vim
	pager = less
	excludesfile = ~/.gitignore_global
	autocrlf = input

alexisduque

Keybase proof

I hereby claim:

• I am alexisduque on github.
• I am alexisduque (https://keybase.io/alexisduque) on keybase.
• I have a public key whose fingerprint is A400 7D60 5BC9 F1B4 8F63 2FC4 3832 8388 B5B9 6439

To claim this, I am signing this object:

alexisduque

Every so often I have to restore my gpg keys and I'm never sure how best to do it. So, I've spent some time playing around with the various ways to export/import (backup/restore) keys.

Method 1

Backup the public and secret keyrings and trust database

cp ~/.gnupg/pubring.gpg /path/to/backups/
cp ~/.gnupg/secring.gpg /path/to/backups/
cp ~/.gnupg/trustdb.gpg /path/to/backups/

or, instead of backing up trustdb...

alexisduque

find . -name "*.md*" | while read i; do pandoc -f markdown -t asciidoc "$i" -o "${i%.*}.adoc"; done
for file in *.png; do convert $file -resize 500x500 -quality 90 "${file%.*}.jpg" ; done

alexisduque

/* Overwrite vscode dark markdown theme */
body {
	background-color: white !important;
	padding: .5em 5em;
}

.vscode-dark {
	color: rgb(30, 30, 30);
}

alexisduque

Source: http://willandorla.com/will/2011/01/convert-folder-into-git-submodule/

1. Clone new repository

$ git clone --no-hardlinks original-repo copied-repo

2. Filter out the files you want to keep and remove the others

alexisduque

#List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

#Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

#Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(value_list)]