Section 1 종합 회고

EDA , Data visualization , statistics , Linear Algebra and project

SECTION 1 리뷰
01 - Data preprocess , EDA , Data visualization
02 - Statistics
03 - Linear Algebra
04 - Project (게임 데이터 분석 기반 기획안 작성)

01 - KEYWORD

• git
• github - Repository , Fork , Clone , Commit , Pull Request
• pandas - concat , merge , pandas 조금더 능숙하게 다루기 (1) 
• Tidy data - melt (wide->tidy) , pivot table (tidy->melt)
• data frame
• EDA
• Feature engineering
• 문자타입 type casting - Float , int , string
• Data Visualization - seaborn , matplot , plotly

시작,EDA,Data Science_Day1	khalidpark2029.tistory.com/3
Feature Engineering,데이터전처리_Day2	khalidpark2029.tistory.com/4
Feature Engineering,형변환_Day2(2)	khalidpark2029.tistory.com/5
Data Manipulation,concat,merge,melt_Day3	khalidpark2029.tistory.com/7
25 pandas tricks_Day3(2)	khalidpark2029.tistory.com/6
Data Manipulation_Day3(3)_Tidy data	khalidpark2029.tistory.com/14
Data Manipulation_Day3(4)_ggplot,그래픽문법	khalidpark2029.tistory.com/13
Data Manipulation_Day3(5)_pipe & chaining	khalidpark2029.tistory.com/15
Data Visulaize,plot,seaborn_Day4	khalidpark2029.tistory.com/10
판다스 데이터프레임에서 1줄만 잘랐을때 series가 왜 될까?	khalidpark2029.tistory.com/16
Data Slice , loc , iloc	khalidpark2029.tistory.com/20

(1) pandas.pydata.org/pandas-docs/stable/user_guide/10min.html

10 minutes to pandas — pandas 1.2.1 documentation

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02 - KEYWORD

• 기술통계 - boxplot , violinplot
• 추리통계 - 샘플링
• 가설검정
• 표본평균 - 표본오차 , 표본편차 , 표본의수n
• student t - test
• One sample t-test - Two sample t-test
• 귀무가설 (Null Hypothesis) - 대안가설 (Alternative Hypothesis)
• 신뢰도 - 95% , 99%
• 신뢰구간
• P-Value
• One tail test - Two tail test
• non - parametric
• chi-square test - One sample (stats.chi2.cdf) , two sample (chi2_contingency)
• 자유도 (Degree of Freedom)
• 큰 수의 법칙
• 중심극한정리 (CLT)
• 총 확률의 법칙
• 베이지안 이론

Hypothesis Test,귀무,대안,T-test_Day6	khalidpark2029.tistory.com/18
Hypothesis Test,One sample,Two sample_Day6(2)	khalidpark2029.tistory.com/19
A/B 테스트의 기본개념_Day6(3)	khalidpark2029.tistory.com/54
student.t.distribution/스튜던트t검정_Day6(4)	khalidpark2029.tistory.com/55
Hypothesis Test,자유도,one tail,two tail,chi square _2_Day7	khalidpark2029.tistory.com/21
Hypothesis Test, T-test, type of error, parametric_2_Day7(2)	khalidpark2029.tistory.com/22
1sample vs 2sample chisquare 코드_Day7(3)	khalidpark2029.tistory.com/50
Empirical Analysis. 경험적 분석(실증적 분석)_Day7(4)	khalidpark2029.tistory.com/51
콜모고로프-스미르노브 검정_Day7(5)	khalidpark2029.tistory.com/52
Multivariate Test,다변수테스트,A/B테스트와 비교_Day7(6)	khalidpark2029.tistory.com/53
Confidence interval & CLT_Day8	khalidpark2029.tistory.com/25
큰수의법칙,CLT,신뢰구간_Day8(2)	khalidpark2029.tistory.com/26
신뢰구간의 개념 한번더_Day8(3)	khalidpark2029.tistory.com/49
Bayesian_Day9	khalidpark2029.tistory.com/30
베이지안적 통계 이론_Day9(2)	khalidpark2029.tistory.com/31
t-test란 무엇인가? (완전정복)	khalidpark2029.tistory.com/34
Convert two-tailed to a one-tailed test	khalidpark2029.tistory.com/31
표준오차,표준편차,표본평균,모평균 통계용어 정리	khalidpark2029.tistory.com/28
np.random.poisson & np.random.binomial	khalidpark2029.tistory.com/27
P-value & Q-value	khalidpark2029.tistory.com/24
표본 크기가 커지면 발생할 수 있는 p-value 오류	khalidpark2029.tistory.com/23

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03 - KEYWORD

• 벡터 - 스칼라 , 벡터의 크기 , 내적  (Dot) , 
• 매트릭스 - 차원 , transpose , 정사각 매트릭스
• 단위 매트릭스 - I
• 행렬식 (Determinant)
• 역행렬 
• 분산 - 모집단의 분산 , 샘플의 분산
• 표준편차
• 공분산 (Covariance) - positive , negative
• 상관계수 (Correlation coefficient) 
• 수직(orthogonality)
• 단위벡터
• span
• 선형관계의 벡터 - 선형관계에 있지 않은 벡터
• basis
• rank
• Linear projection
• 벡터변환 - transpose
• 고유벡터 - eigenvector
• 고유값 - eigenvalue
• 고차원의 문제 - 고차원의 시각화의 문제
• 차원축소
• feature selection , feature extraction
• PCA
• 클러스터 - Kmeans 클러스터 , 중심점(centroid)

선형대수 Linear Algebra_Day11	khalidpark2029.tistory.com/35
Linear Algebra2_Day12	khalidpark2029.tistory.com/36
선형대수학을 위한 벡터 복습_Day12(2)	khalidpark2029.tistory.com/38
공분산,상관계수,span,basis,rank_Day12(3)	khalidpark2029.tistory.com/39
eigenvector,eigenvalue,고윳값,고유벡터_Day13	khalidpark2029.tistory.com/42
벡터변환,고유벡터,고유값_Day13(2)	khalidpark2029.tistory.com/43
PCA의원리_Day13(3)	khalidpark2029.tistory.com/44
선형대수와 매트릭스의 시작.기본개념_Day13(4)	khalidpark2029.tistory.com/48
HCA(하이어리컬, 클러스터)_Day14	khalidpark2029.tistory.com/46
클러스터, scree plot, k-means, ML_Day14(2)	khalidpark2029.tistory.com/47

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04 - Project

• 게임 데이터 분석 기반 기획안 작성

 

게임데이터분석 및 기획안 작성 프로젝트_Day16~19	khalidpark2029.tistory.com/60
완성)게임데이터분석 및 기획안 작성 프로젝트_Day20	khalidpark2029.tistory.com/61
피드백)게임데이터분석 및 기획안 작성 프로젝트_Day20	khalidpark2029.tistory.com/62

 

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이미지 출처 : medium.muz.li/guide-to-data-visualization-comparison-part-1-678382ceef00

Your guide to Data Visualization for Comparison

www.edx.org/course/math-of-data-science-linear-algebra

RiceX Linear Algebra Part 1

m.dexlabanalytics.com/blog/bayes-theorem-application-in-r-and-python

Bayes’ Theorem – Application in R and Python