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# Hyungyong Kim yong27

Created Aug 25, 2016
US baby names
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 { "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "notes" } }, "source": [
Created Apr 17, 2016
keybase.md
View keybase.md

### Keybase proof

I hereby claim:

• I am yong27 on github.
• I am yong27 (https://keybase.io/yong27) on keybase.
• I have a public key ASAjtQNw9SDOQaz1UbCt8SF8R7dYOe-xaZQKCGYa8jmPugo

To claim this, I am signing this object:

Last active Jan 21, 2016
Jupyter 데이터 분석 사례 (인코고등학교 중간고사 성적)
View 데이터분석사례-중간고사성적.ipynb.json
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 { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 성적 데이터 분석\n", "\n", "인코고등학교 1학년의 중간고사 성적이 나왔습니다. 1반과 2반 두개의 반으로 구성되어 있고, 학생은 각각 6명입니다. 이 성적 데이터로 간단한 데이터 분석을 하고자 합니다. \n", "\n",
Created May 13, 2015
It's for counting biological_process terms which have is_a and part_of.
View go_term_stat.py
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 """ 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
Last active Aug 29, 2015
View Korean-social-newtork-status.json
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 { "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)" ]
Created Mar 13, 2015
Metagenome basic profiler
View metagenome_profiler.py
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 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:
Created Feb 6, 2015
plottest.ipynb
View gist:1663c74272b7e685fdc2
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 { "metadata": { "name": "", "signature": "sha256:9299994bc33725ce2fb54720efc2a7b1a7fb1e955d3914b9e8ba9de6a50bd456" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [
Last active Mar 17, 2022
pandas DataFrame apply multiprocessing
View apply_df_by_multiprocessing.py
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 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')
Last active May 19, 2020