ashcarr Everestparts

Animated Tab Bar

Designed by: Mauricio Bucardo

Original image: https://dribbble.com/shots/5619509-Animated-Tab-Bar

Common zsh Keyboard Shortcuts on macOS

Navigation

CTRL + A : Move the cursor to the beginning of the line
CTRL + E : Move the cursor to the end of the line
OPTION + Left Arrow : Move the cursor one word backward
OPTION + Right arrow : Move the cursor one word forward
Left Arrow : Move the cursor one character backward
Right Arrow : Move the cursor one character forward

If .DS_Store was never added to your git repository, simply add it to your .gitignore file.

If you don't have one, create a file called

.gitignore

In your the root directory of your app and simply write

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

	# extraction pattern: ngram TAB year TAB match_count TAB volume_count NEWLINE
	# out: unique_ngram TAB sum(match_count) NEWLINE

	import re
	import os, sys, mmap
	from pathlib import Path
	from tqdm import tqdm
	from concurrent.futures import ThreadPoolExecutor

	abv = re.compile(r'^(([A-Z]\.){1,})(_\|[^\w])') # A.B.C.

	# List unique values in a DataFrame column
	df['Column Name'].unique() # Note, `NaN` is included as a unique value. If you just want the number, use `nunique()` which stands
	# for 'number of unique values'; By default, it excludes `NaN`. `.nunique(dropna=False)` will include `NaN` in the count of unique values.

	# To extract a specific column (subset the dataframe), you can use [ ] (brackets) or attribute notation.
	df.height
	df['height']
	# are same thing!!! (from http://www.stephaniehicks.com/learnPython/pages/pandas.html
	# -or-
	# http://www.datacarpentry.org/python-ecology-lesson/02-index-slice-subset/)

	import io

	from PIL import Image # https://pillow.readthedocs.io/en/4.3.x/
	import requests # http://docs.python-requests.org/en/master/


	# example image url: https://m.media-amazon.com/images/S/aplus-media/vc/6a9569ab-cb8e-46d9-8aea-a7022e58c74a.jpg
	def download_image(url, image_file_path):
	r = requests.get(url, timeout=4.0)
	if r.status_code != requests.codes.ok:

	#!/usr/bin/env python

	"""Basic Python Cheat Sheet by Filip Kral on 2015/02/16"""

	"""
	Python is a cross-platform, interpreted, object-oriented programming language.
	That means you can run it on Linux, Windows, Mac, and other platforms,
	you don't need to compile your code to execute it because it is compiled on
	the fly, and you can use classes and objects.

	import multiprocessing
	import pandas as pd
	import numpy as np

	def _apply_df(args):
	df, func, kwargs = args
	return df.apply(func, **kwargs)

	def apply_by_multiprocessing(df, func, **kwargs):
	workers = kwargs.pop('workers')

	{
	"cmd": ["/usr/local/var/pyenv/shims/python", "-u", "$file"],
	"file_regex": "^[ ]File \"(...?)\", line ([0-9]*)",
	"selector": "source.python"
	}