4. 데이터의 분포와 비율을 파악하기 위한 그래프

히스토그램

scores=[0,10,15,15,16,19,20,21,25,25,26,26,29,30,35,36,37,39,40,41,41,44,45,45,45,45,47
,50,50,50,51,51,51,53,54,55,55,56,60,61,62,63,64,65,65,66,66,66,66,67
,68,68,69,70,70,70,70,70,70,70,71,71,71,71,72,72,72,72,74,74,74,75,75
,76,76,76,77,77,77,78,78,78,78,79,79,79,80,80,80,80,80,81,81,82,82
,85,85,85,88,88,89,90,90,90,93,93,95,95,97,100]

plt.hist(scores)

 

bins=구간 개수

plt.hist(scores,bins=20)

 

누적 히스토그램

plt.hist(scores,bins=20,cumulative=True)

 

범위 지정

range=(min,max)

plt.hist(scores,bins=20,range=(50,90))

 

밀도 표현

density=Ture

도수를 총 개수로 나눈 수치를 y축에 표현

plt.hist(scores,density=True)

plt.hist(scores,density=True,orientation='horizontal')

 

막대스타일

선만 표시 histtype='step'

plt.hist(scores,density=True,histtype='step')

 

rwidth = 막대폭(0~1), color=막대색, alpha=투명도

edgeclor(ec)= 선색, linewidth(lw)=선두께, linestyle(ls)=선스타일,hatch=패턴

 

plt.hist(scores,rwidth=0.9,color='b',alpha=0.5,ec='k',lw=2,ls=':'
,hatch='/')
plt.xticks(range(0,101,10))
plt.grid(axis='y',ls=':')
plt.xlabel('점수')
plt.ylabel('인원')
plt.title('점수대별 인원 분포',size=20)
plt.show()

 

 

박스플롯

데이터로부터 얻어진 아래의 다섯 요약 수치를 사용해서 그린다.

최소값

제1사분위수

제2사분위수, 중위수

제3사분위수

최대값

 

 

import pandas as pd
scores=pd.Series([0,10,15,15,16,19,20,21,25,25,26,26,29,30,35,36,37,39,40,41,41,44,45,45,45,45,47
,50,50,50,51,51,51,53,54,55,55,56,60,61,62,63,64,65,65,66,66,66,66,67
,68,68,69,70,70,70,70,70,70,70,71,71,71,71,72,72,72,72,74,74,74,75,75
,76,76,76,77,77,77,78,78,78,78,79,79,79,80,80,80,80,80,81,81,82,82
,85,85,85,88,88,89,90,90,90,93,93,95,95,97,100])

scores.describe()

count    110.000000
mean      62.727273
std       22.202120
min        0.000000
25%       50.000000
50%       70.000000
75%       78.000000
max      100.000000
dtype: float64

 

 

이상치 구하기

Q1=scores.quantile(.25)

Q3=scores.quantile(.75)

plt.boxplot(scores)

 

평균 표시하기

showmeans=True

meanline=True

 

plt.boxplot(scores,showmeans=True,meanline=True)

 

수평박스플롯

vert=False

plt.boxplot(scores,showmeans=True,meanline=True,vert=False)

 

예제 데이터 가져오기

import seaborn as sns
iris = sns.load_dataset('iris')
iris.head()

plt.boxplot([iris['sepal_length'],iris['sepal_width'],iris['petal_length'],iris['petal_width']])
plt.show()

plt.boxplot([iris['sepal_length'],iris['sepal_width'],iris['petal_length'],iris['petal_width']]
,labels=['sepal_length','sepal_width','petal_length','petal_width'],
showmeans=True)
plt.grid(axis='y')
plt.show()

 

바이올린 플롯

plt.violinplot(scores)

최대값, 최소값, 중간값 표시

showextream=True/False

showemeans=True/False

showeedians=True/False

 

plt.violinplot(scores,showextrema=True,showmeans=True,showmedians=True,
quantiles=[0.25,0.75])
plt.show()

 

 

스타일로 지정하기

플롯['bodies'][인덱스].set_facecolor(컬러)

플롯['cmins'][인덱스].set_edgecolor(컬러)

플롯['cmaxes'][인덱스].set_edgecolor(컬러)

플롯['cbars'][인덱스].set_edgecolor(컬러)

플롯['cmedians'][인덱스].set_edgecolor(컬러)

플롯['cquantiles'][인덱스].set_edgecolor(컬러)

플롯['cmeans'][인덱스].set_edgecolor(컬러)

v1=plt.violinplot(scores,showextrema=True,showmeans=True,showmedians=True,
quantiles=[0.25,0.75])
v1['bodies'][0].set_facecolor('r')
v1['cmins'].set_edgecolor('g')
v1['cmaxes'].set_edgecolor('g')
v1['cbars'].set_edgecolor('k')
v1['cmedians'].set_edgecolor('r')
v1['cquantiles'].set_edgecolor('w')
v1['cmeans'].set_edgecolor('y')
plt.show()

 

 

iris=sns.load_dataset('iris')

plt.violinplot([iris['sepal_length'],iris['sepal_width'],iris['petal_length'],iris['petal_width']])
plt.show()

plt.violinplot([iris['sepal_length'],iris['sepal_width'],iris['petal_length'],iris['petal_width']])
plt.xticks(range(1,5,1),labels=['sepal_length','sepal_width','petal_length','petal_width'])
plt.show()

 

 

파이 그래프

blood_type=['A','B','O','AB']
personal=[111901,87066,86804,36495]

plt.pie(personal)
plt.show()

 

plt.pie(personal,labels=blood_type)
plt.show()

plt.pie(personal,labels=blood_type,labeldistance=1.2)
plt.show()

 

비율표시하기

autopct ='%소수점자리수%%'

pctdistance=중심점에서의 거리

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8)
plt.show()

 

돌출효과 주기

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0])
plt.show()

색변경하기

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'])
plt.show()

 

시작각도 변경

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'],
startangle=90)
plt.show()

1.8 회전방향

counterclock=True/False

 

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'],
startangle=90,
counterclock=False)
plt.show()

 

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'],
startangle=90,
counterclock=False)
plt.legend(loc=(1,0.5))
plt.show()

크기 변경

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'],
startangle=90,
counterclock=False,
radius=0.5)
plt.legend(loc=(1,0.5))
plt.show()

부채꼴 스타일

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'],
startangle=90,
counterclock=False,
radius=1,
wedgeprops={'ec':'k','lw':1,'ls':':','width':0.7})
plt.legend(loc=(1,0.5))
plt.show()

 

wedgeprops={'ec':'k','lw':1,'ls':':','width':0.7})

 

폰트지정

textprops={'fontsize:폰트사이즈, 'color':폰트컬러,'rotation':폰트회전각도}

plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'],
startangle=90,
counterclock=False,
radius=1,
wedgeprops={'ec':'k','lw':1,'ls':':','width':0.7},
textprops={'fontsize':15, 'color':'b','rotation':45})
plt.legend(loc=(1,0.5))
plt.show()

 

plt.figure(figsize=(5,5),facecolor='ivory',edgecolor='gray',linewidth=2)
plt.pie(personal,labels=blood_type,labeldistance=1.2,autopct='%.1f%%'
,pctdistance=0.8,explode=[0.1,0,0,0],
colors=['lightcoral','gold','greenyellow','skyblue'],
startangle=90,
counterclock=False,
radius=1,
wedgeprops={'ec':'k','lw':1,'ls':':','width':0.7},
textprops={'fontsize':15, 'color':'b','rotation':45})
plt.title('2019년 병역판정검사 - 혈액형분포',size=15)
plt.legend(loc=(1,0.5))

plt.show()

plt.figure(figsize=(5,5),facecolor='ivory',edgecolor='gray',linewidth=2)