Arthur Mwai bolshoibooze

The issue:

..mobile browsers will wait approximately 300ms from the time that you tap the button to fire the click event. The reason for this is that the browser is waiting to see if you are actually performing a double tap.

(from a new defunct https://developers.google.com/mobile/articles/fast_buttons article)

touch-action CSS property can be used to disable this behaviour.

touch-action: manipulation The user agent may consider touches that begin on the element only for the purposes of scrolling and continuous zooming. Any additional behaviors supported by auto are out of scope for this specification.

from scipy.spatial import Delaunay, ConvexHull
import networkx as nx
 
points = [ [0,0],[0,50],[50,50],[50,0],[0,400],[0,450],[50,400],[50,450],[700,300],[700,350],[750,300],[750,350],
          [900,600],[950,650],[950,600],[900,650]
]
def concave(points,alpha_x=150,alpha_y=250):
    points = [(i[0],i[1]) if type(i) <> tuple else i for i in points]
    de = Delaunay(points)

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)

Sample service script for debianoids

Look at LSB init scripts for more information.

Usage

Copy to /etc/init.d:

# replace "$YOUR_SERVICE_NAME" with your service's name (whenever it's not enough obvious)

	1. Highlight a recommended option,
	2. Allow users to switch currency (€/$/£)
	3. Allow users to switch pricing monthly/yearly
	4. Keep the entire pricing plan area clickable
	5. Use slider to calculate how much a user would save
	6. Provide free first month for good engagement
	7. Prominently highlight testimonials prominently
	8. Repeating call to action on top and bottom
	9. Sell benefits instead of features
	10. Indicate that users can cancel any time


	# coding: utf-8

	# Imports

	import os
	import cPickle
	import numpy as np
	import theano
	import theano.tensor as T

	def convertCSVtoJSON(input): #pass the name of the input csv file
	f = open(input, 'r')
	j = open('.tempJSON', 'w')
	fieldnames = ("field1,field2,field3")
	reader = csv.DictReader(f, fieldnames)
	for row in reader:
	json.dump(row, j)
	j.write('\n')
	f.close()
	j.close()

	from scipy.spatial.distance import pdist, squareform
	import numpy as np

	from numbapro import jit, float32

	def distcorr(X, Y):
	""" Compute the distance correlation function

	>>> a = [1,2,3,4,5]
	>>> b = np.array([1,2,9,4,4])



	class BigForeignKey(models.ForeignKey):
	def db_type(self, connection):
	""" Adds support for foreign keys to big integers as primary keys.
	"""
	rel_field = self.rel.get_related_field()
	if (isinstance(rel_field, BigAutoField) or
	(not connection.features.related_fields_match_type and
	isinstance(rel_field, (BigIntegerField, )))):

	"""making a dataframe"""
	df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))

	"""quick way to create an interesting data frame to try things out"""
	df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd'])

	"""convert a dictionary into a DataFrame"""
	"""make the keys into columns"""
	df = pd.DataFrame(dic, index=[0])