[Python] Matplotlib 시각화

선그래프

import matplotlib.pyplot as  plt
import matplotlib as mpl
%matplotlib inline

plt.title('Plot')
plt.plot([1,4,9,16])
plt.show()

 

 

 

제목 설정

plt.title('x ticks')
plt.plot([10,20,30,40], [1,4,9,16])
plt.show()

 

 

한글 설정 (Mac)

# 폰트 설정
mpl.rc('font', family='NanumGothic')
#유니코드에서 음수 부호 설정
mpl.rc('axes', unicode_minus=False)

 

 

 

스타일 지정

# 스타일 지정
plt.title('rs style')
plt.plot([10,20,30,40], [1,4,9,16], 'rs--')
plt.show()

- 색깔 : b, g, r, c, m, y, k, w
- 마커 : ".", '," , o, v, ^, <, >, 1,2,3,4,s,o, *, h, H, +, D, d
- 선스타일 : -, --, -., :
- 스타일 문자열 : c(선색깔), lw(선굵기), ls(선스타일),marker(마커종류), ms(마커크기), mec(마커선색깔), mew(마커 선굵기), mfc(마커 내부 색깔)

 

 

plt.plot([10,20,30,40], [1,4,9,16], c='b', lw = 5,
         ls='--', marker='o', ms=15, mec='g', mew=5, mfc='r')
plt.title('style example')
plt.show()

 

 

 

#그림 범위 지정
plt.title('x, y lim')
plt.plot([10,20,30,40], [1,4,9,16],
         c='b', lw=5,ls='--',marker='o',ms=15,mec='g',mew=5,mfc='r')
plt.xlim(0,50)
plt.ylim(-10,30)
plt.show()

 

 

 

# 틱 설정 : 축상의 위치 표시 지점
import numpy as np
X = np.linspace(-np.pi, np.pi, 256)
C = np.cos(X)
plt.title('tick label')
plt.plot(X,C)
plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi])
plt.yticks([-1,0,1])
plt.show()

 

 

X = np.linspace(-np.pi, np.pi, 256)
C = np.cos(X)
plt.title('Latex')
plt.plot(X,C)
plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],
           [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$'])
plt.yticks([-1,0,1], ['low','zero','high'])
plt.show()

 

 

 

# 그리드 설정
X = np.linspace(-np.pi, np.pi, 256)
C = np.cos(X)
plt.title('Grid')
plt.plot(X,C)
plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],
           [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$'])
plt.yticks([-1,0,1], ['low','zero','high'])
plt.grid(True)
plt.show()

 

 

 

# 겹쳐 그리기
plt.plot([1,4,9,16],
         c='b',lw=5,ls='--',marker='o',ms=15,mec='g',mew=5,mfc='r')
plt.plot([9,16,4,1],
         c='k',lw=3,ls=':',marker='s',ms=10,mec='m',mew=5,mfc='c')
plt.show()

 

 

 

# 범례 표시
X = np.linspace(-np.pi, np.pi, 256)
C, S = np.cos(X), np.sin(X)
plt.title('legend')
plt.plot(X,C, ls='--', label='cosine')
plt.plot(X,S, ls=':', label='sine')
plt.legend(loc=2)
plt.show()

 

 

 

# x축, y축 label, title
X = np.linspace(-np.pi, np.pi, 256)
C, S = np.cos(X), np.sin(X)
plt.plot(X,C, label='cosine')
plt.xlabel('time')
plt.ylabel('amplitude')
plt.title('Cosine Plot')
plt.show()

 

 

 

# Figure 객체
np.random.seed(0)
f1 = plt.figure(figsize=(10,2))
plt.title('figsize : (10,2)')
plt.plot(np.random.randn(100))
plt.show()

 

 

 

f1 = plt.figure(1)
plt.title('now figure')
plt.plot([1,2,3,4], 'ro:')

f2 = plt.gcf()
print(f1, id(f1))
print(f2, id(f2))
plt.show()

 

 

 

x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 5.0)
y1 = np.cos(2*np.pi*x1) * np.exp(-x1)
y2 = np.cos(2*np.pi*x2)

ax1 = plt.subplot(2,1,1)
plt.plot(x1,y1,'yo-')
plt.title('A tale of 2 subplots')
plt.ylabel("Damped oscillation")

ax2 = plt.subplot(2,1,2)
plt.plot(x2, y2, 'r.-')
plt.xlabel('time (s)')
plt.ylabel('Undamped')

plt.tight_layout()
plt.show()

 

 

 

# 2 * 2 형태
np.random.seed(0)
plt.subplot(221)
plt.plot(np.random.rand(5))
plt.title('axes1')

plt.subplot(222)
plt.plot(np.random.rand(5))
plt.title('axes2')

plt.subplot(223)
plt.plot(np.random.rand(5))
plt.title('axes3')

plt.subplot(224)
plt.plot(np.random.rand(5))
plt.title('axes4')

plt.tight_layout()
plt.show()

 

 

 

fig, axes = plt.subplots(2,2)
np.random.seed(0)
axes[0,0].plot(np.random.rand(5))
axes[0,0].set_title('axes1')
axes[0,1].plot(np.random.rand(5))
axes[0,1].set_title('axes2')
axes[1,0].plot(np.random.rand(5))
axes[1,0].set_title('axes3')
axes[1,1].plot(np.random.rand(5))
axes[1,1].set_title('axes4')

plt.tight_layout()
plt.show()

 

 

 

 

# Axis 객체와 축 : 복수의 y축 생성
fig, ax0 = plt.subplots()
ax1 = ax0.twinx()
ax0.set_title('2 Axis')
ax0.plot([10,5,2,9,7], 'r-', label='y0')
ax0.set_ylabel('y0')
ax0.grid(False)

ax1.plot([100,200,220, 120],'g:', label='y1')
ax1.set_ylabel('y1')
ax0.set_xlabel('X')
plt.show()

 

 

 

 

# Bar Chart
from matplotlib import rc
rc('font', family='AppleGothic')
plt.rcParams['axes.unicode_minus'] = False

y = [2,3,1]
x = np.arange(len(y))

xlabel = ['가', '나','다']
plt.title("Bar chart")
plt.bar(x,y)
plt.xticks(x, xlabel)
plt.yticks(sorted(y))
plt.xlabel('가나다')
plt.ylabel('빈도 수')
plt.show()

 

 

 

# alpha : 투명도
people = ['몽룡', '춘향', '방자', '향단']
y_pos = np.arange(len(people))
performance = 3 + 10*np.random.rand(len(people))
error = np.random.rand(len(people))

plt.title('Bar Chart')
plt.barh(y_pos, performance, xerr=error, alpha=0.4)
plt.yticks(y_pos, people)
plt.xlabel('x 라벨')
plt.show()

 

 

 

 

# 스템 플롯 : 바차트와 유사하지만 폭이 없음
x = np.linspace(0.1, 2*np.pi, 10)
plt.title('Stem Plot')
plt.stem(x, np.cos(x), '-.')
plt.show()

 

 

 

# 파이차트 

labels = ['개구리', '돼지', '개', '통나무']
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0)
plt.title('Pie Chart')
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
        autopct='%1.1f$', shadow=True, startangle=90)
plt.axis('equal')   #원의 형태를 유지하는 명령어
plt.show()

 

 

 

# 히스토그램
np.random.seed(0)
x = np.random.randn(1000)
plt.title('Histogram')
arrays, bins, patchs = plt.hist(x, bins=10)
plt.show()

 

 

 

# 스캐터 플롯
np.random.seed(0)
X = np.random.normal(0, 1, 100)
y = np.random.normal(0, 1, 100)
plt.title('Scatter Plot')
plt.scatter(X, y)
plt.show()

 

 

 

# 데이터가 3차원 혹은 4차원인 경우의 스캐터플롯
N = 30
np.random.seed(0)
x = np.random.rand(N)
y1 = np.random.rand(N)
y2 = np.random.rand(N)
y3 = np.pi * (15*np.random.rand(N)) **2

plt.title('Bubble Chart')
plt.scatter(x, y1, c=y2, s=y3)
plt.show()

 

 

 

# Imshow
from sklearn.datasets import load_digits
digits = load_digits()
X = digits.images[0]

plt.title('Mnist digits; 0')
plt.imshow(X, interpolation='nearest', cmap=plt.cm.bone_r)
plt.xticks([])
plt.yticks([])
plt.grid(False)
plt.subplots_adjust(left=0.35, right=0.65, bottom=0.35, top=0.65)
plt.show()

 

 

 

# 컬러맵 확인
dir(plt.cm)[:10]

 

 

 

# 컨투어 플롯
def f(x, y):
    return (1 - x/2 + x**5 + y**3) * np.exp(-x**2 -y**2)

n = 256
x = np.linspace(-3,3,n)
y = np.linspace(-3,3,n)
XX, YY = np.meshgrid(x, y)
ZZ = f(XX, YY)

plt.title('Contour Plot')
plt.contourf(XX, YY, ZZ, alpha=.75, cmap='jet')
plt.contour(XX, YY, ZZ, colors='black')
plt.show()

 

 

 

# 3D 서피스 플롯
from mpl_toolkits.mplot3d import Axes3D
X = np.arange(-4, 4, 0.25)
y = np.arange(-4, 4, 0.25)

XX, YY = np.meshgrid(X, y)
RR = np.sqrt(XX**2 + YY**2)
ZZ = np.sin(RR)

fig = plt.figure()
ax = Axes3D(fig)
ax.set_title('3D Surface Plot')
ax.plot_surface(XX, YY, ZZ, rstride=1, cstride=1, cmap='hot')
plt.show()