Hyungyong Kim yong27

## broken_fastq.py
def is_valid_fastq(lines):
    start = lines[0].startswith('@')
    middle = lines[2].startswith('+')
    length = len(lines[1]) == len(lines[3])
    return all([start, middle, length])

def FastqIterator(file):
    lines = [file.next(), file.next(), file.next()]
    for line in file:
        lines.append(line)

## hangul_python.py
import unittest

class 유형:
    def __init__(자기, *인수, **키워드인수):
        자기.생성될때(*인수, **키워드인수)

class 시험사례(unittest.TestCase):
    같아야함 = unittest.TestCase.assertEquals

class 배열(list):

## clock_angle.py
import unittest
from math import pi, degrees

def get_hour_angle(hour, minute=0):
    angle = (hour / 6.) * pi
    minute_angle = get_minute_angle(minute) / 12
    return angle + minute_angle

def get_minute_angle(minute):
    angle = (minute / 30.) * pi

## clock_angle_chart.ipynb

      
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                yong27
                / clock_angle_chart.ipynb
            
            
              Created
              May 24, 2013 05:53
            
              
                Clock angle chart ipython notebook
              
          
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## geo_downloader.py
# -*- coding:utf-8 -*-
"""
GEO file downloader

Requirements
 * beautifulsoup4 (pip install lxml beautifulsoup4)
 * wget

Usage
 1. get CSV file in the GEO browse page.

## apply_df_by_multiprocessing.py
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')

## gist:1663c74272b7e685fdc2
{
 "metadata": {
  "name": "",
  "signature": "sha256:9299994bc33725ce2fb54720efc2a7b1a7fb1e955d3914b9e8ba9de6a50bd456"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [

## metagenome_profiler.py
import pandas as pd
from subprocess import Popen, PIPE

def len_fasta(filename):
    p1 = Popen(['cat', filename], stdout=PIPE, stderr=PIPE)
    p2 = Popen(['grep', '>'], stdin=p1.stdout, stdout=PIPE, stderr=PIPE)
    p3 = Popen(['wc', '-l'], stdin=p2.stdout, stdout=PIPE, stderr=PIPE)

    result, err = p3.communicate()
    if p3.returncode != 0:

## Korean-social-newtork-status.json
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[대한민국 SNS 이용현황](http://m.blog.naver.com/mobidays01/220331132165) 블로그 글에 표시된 그림을 좀 다르게 그려보자\n",
    "\n",
    "![](http://mblogthumb1.phinf.naver.net/20150414_20/mobidays01_14290006372183j5KB_JPEG/mobidays_sns%C0%CC%BF%EB%C7%F6%C8%B2.jpg?type=w2)"
   ]

## go_term_stat.py
"""
It's for counting biological_process terms which have is_a and part_of.

Usage:

    $ wget http://purl.obolibrary.org/obo/go.obo
    $ python3 go_term_stat.py < go.obo

Main data structure
	def is_valid_fastq(lines):
	start = lines[0].startswith('@')
	middle = lines[2].startswith('+')
	length = len(lines[1]) == len(lines[3])
	return all([start, middle, length])

	def FastqIterator(file):
	lines = [file.next(), file.next(), file.next()]
	for line in file:
	lines.append(line)
	import unittest

	class 유형:
	def __init__(자기, 인수, *키워드인수):
	자기.생성될때(인수, *키워드인수)

	class 시험사례(unittest.TestCase):
	같아야함 = unittest.TestCase.assertEquals

	class 배열(list):
	import unittest
	from math import pi, degrees

	def get_hour_angle(hour, minute=0):
	angle = (hour / 6.) * pi
	minute_angle = get_minute_angle(minute) / 12
	return angle + minute_angle

	def get_minute_angle(minute):
	angle = (minute / 30.) * pi
	# -- coding:utf-8 --
	"""
	GEO file downloader

	Requirements
	* beautifulsoup4 (pip install lxml beautifulsoup4)
	* wget

	Usage
	1. get CSV file in the GEO browse page.
	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')
	{
	"metadata": {
	"name": "",
	"signature": "sha256:9299994bc33725ce2fb54720efc2a7b1a7fb1e955d3914b9e8ba9de6a50bd456"
	},
	"nbformat": 3,
	"nbformat_minor": 0,
	"worksheets": [
	{
	"cells": [
	import pandas as pd
	from subprocess import Popen, PIPE

	def len_fasta(filename):
	p1 = Popen(['cat', filename], stdout=PIPE, stderr=PIPE)
	p2 = Popen(['grep', '>'], stdin=p1.stdout, stdout=PIPE, stderr=PIPE)
	p3 = Popen(['wc', '-l'], stdin=p2.stdout, stdout=PIPE, stderr=PIPE)

	result, err = p3.communicate()
	if p3.returncode != 0:
	{
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"[대한민국 SNS 이용현황](http://m.blog.naver.com/mobidays01/220331132165) 블로그 글에 표시된 그림을 좀 다르게 그려보자\n",
	"\n",
	"![](http://mblogthumb1.phinf.naver.net/20150414_20/mobidays01_14290006372183j5KB_JPEG/mobidays_sns%C0%CC%BF%EB%C7%F6%C8%B2.jpg?type=w2)"
	]
	"""
	It's for counting biological_process terms which have is_a and part_of.

	Usage:

	$ wget http://purl.obolibrary.org/obo/go.obo
	$ python3 go_term_stat.py < go.obo

	Main data structure