실습에 필요한 데이터 파일 다운로드

directory = 'data/house_price.csv'

기본 import

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

구글 코랩 (Colab) 한글 폰트 깨짐현상

  • 구글 코랩 (Google Colab) 에서 한글 폰트 깨짐 현상이 발생합니다.
  • 이는, 코랩에서 한글 폰트가 설치가 안되어 깨지는 현상이 발행하는 것입니다.
  • 따라서, 한글 폰트를 설치 해주면, 깨짐 현상이 해결됩니다.
  • 네이버가 제공하는 나눔 고딕 폰트를 설치하도록 하겠습니다.
df = pd.read_csv(directory)
df.plot()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 50672 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 46020 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 50900 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 48516 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 50577 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 44032 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 50672 missing from current font.
  font.set_text(s, 0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 46020 missing from current font.
  font.set_text(s, 0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:176: RuntimeWarning: Glyph 50900 missing from current font.
  font.load_char(ord(s), flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 48516 missing from current font.
  font.set_text(s, 0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 50577 missing from current font.
  font.set_text(s, 0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 44032 missing from current font.
  font.set_text(s, 0, flags=flags)

!sudo apt-get install -y fonts-nanum
!sudo fc-cache -fv
!rm ~/.cache/matplotlib -rf
Reading package lists... Done
Building dependency tree       
Reading state information... Done
fonts-nanum is already the newest version (20140930-1).
The following packages were automatically installed and are no longer required:
  linux-headers-4.4.0-31 linux-headers-4.4.0-31-generic
  linux-image-4.4.0-31-generic linux-image-4.4.0-59-generic
  linux-image-extra-4.4.0-31-generic linux-image-extra-4.4.0-59-generic
Use 'sudo apt autoremove' to remove them.
0 upgraded, 0 newly installed, 0 to remove and 158 not upgraded.
/usr/share/fonts: caching, new cache contents: 0 fonts, 1 dirs
/usr/share/fonts/truetype: caching, new cache contents: 0 fonts, 2 dirs
/usr/share/fonts/truetype/dejavu: caching, new cache contents: 21 fonts, 0 dirs
/usr/share/fonts/truetype/nanum: caching, new cache contents: 17 fonts, 0 dirs
/usr/local/share/fonts: caching, new cache contents: 0 fonts, 0 dirs
/home/ubuntu/.local/share/fonts: skipping, no such directory
/home/ubuntu/.fonts: skipping, no such directory
Re-scanning /usr/share/fonts: caching, new cache contents: 0 fonts, 1 dirs
Re-scanning /usr/share/fonts/truetype: caching, new cache contents: 0 fonts, 2 dirs
/var/cache/fontconfig: cleaning cache directory
/home/ubuntu/.cache/fontconfig: not cleaning non-existent cache directory
/home/ubuntu/.fontconfig: not cleaning non-existent cache directory
fc-cache: succeeded

상단 메뉴 - 런타임 - 런타임 다시 시작 클릭

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

plt.rcParams["figure.figsize"] = (10, 7)
plt.rc('font', family='NanumBarunGothic') 
df = pd.read_csv(directory)
df.plot()

matplotlib.pyplot

matplotlib.pyplot의 기본적인 canvas 그리기와 스타일링 예제

pyplot 공식 도큐먼트 살펴보기

본 튜토리얼은 matplotlib의 가장 기본적인 튜토리얼을 제공합니다.

다양한 옵션값과 스타일 기본 설정법을 배울 수 있습니다.

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
plt.rc('font', family='NanumBarunGothic') 
plt.rcParams["figure.figsize"] = (10, 7)

1. 밑 그림 그리기

1-1. 단일 그래프

## data 생성
data = np.arange(1, 100)
## plot
plt.plot(data)
## 그래프를 보여주는 코드
plt.show()

1-2. 다중 그래프 (multiple graphs)

1개의 canvas 안에 다중 그래프 그리기

data = np.arange(1, 51)
plt.plot(data)

data2 = np.arange(51, 101)
# plt.figure()
plt.plot(data2)

plt.show()

2개의 figure로 나누어서 다중 그래프 그리기 * figure()는 새로운 그래프 canvas를 생성합니다.

data = np.arange(100, 201)
plt.plot(data)

data2 = np.arange(200, 301)
# figure()는 새로운 그래프를 생성합니다.
plt.figure()
plt.plot(data2)

plt.show()

1-3. 여러개의 plot을 그리는 방법 (subplot)

subplot(row, column, index)

data = np.arange(100, 201)
plt.subplot(2, 1, 1)
plt.plot(data)

data2 = np.arange(200, 301)
plt.subplot(2, 1, 2)
plt.plot(data2)

plt.show()

위의 코드와 동일하나 , (콤마)를 제거한 상태

data = np.arange(100, 201)
# 콤마를 생략하고 row, column, index로 작성가능
# 211 -> row: 2, col: 1, index: 1
plt.subplot(211)
plt.plot(data)

data2 = np.arange(200, 301)
plt.subplot(212)
plt.plot(data2)

plt.show()

data = np.arange(100, 201)
plt.subplot(1, 3, 1)
plt.plot(data)

data2 = np.arange(200, 301)
plt.subplot(1, 3, 2)
plt.plot(data2)

data3 = np.arange(300, 401)
plt.subplot(1, 3, 3)
plt.plot(data3)

plt.show()

1-4. 여러개의 plot을 그리는 방법 (subplots) - s가 더 붙습니다.

plt.subplots(행의 갯수, 열의 갯수)

data = np.arange(1, 51)
# data 생성

# 밑 그림
fig, axes = plt.subplots(2, 3)

axes[0, 0].plot(data)
axes[0, 1].plot(data * data)
axes[0, 2].plot(data ** 3)
axes[1, 0].plot(data % 10)
axes[1, 1].plot(-data)
axes[1, 2].plot(data // 20)

plt.tight_layout()
plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

2. 주요 스타일 옵션

from IPython.display import Image

# 출처: matplotlib.org
Image('https://matplotlib.org/_images/anatomy.png')

2-1. 타이틀

plt.plot([1, 2, 3], [3, 6, 9])
plt.plot([1, 2, 3], [2, 4, 9])
# 타이틀 & font 설정
plt.title('이것은 타이틀 입니다')

plt.show()

plt.plot([1, 2, 3], [3, 6, 9])
plt.plot([1, 2, 3], [2, 4, 9])
# 타이틀 & font 설정
plt.title('타이틀 fontsize를 키웁니다', fontsize=20)

plt.show()

2-2. X, Y축 Label 설정

plt.plot([1, 2, 3], [3, 6, 9])
plt.plot([1, 2, 3], [2, 4, 9])

# 타이틀 & font 설정
plt.title('Label 설정 예제입니다', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

plt.show()

2-3. X, Y 축 Tick 설정 (rotation)

Tick은 X, Y축에 위치한 눈금을 말합니다.

plt.plot(np.arange(10), np.arange(10)*2)
plt.plot(np.arange(10), np.arange(10)**2)
plt.plot(np.arange(10), np.log(np.arange(10)))

# 타이틀 & font 설정
plt.title('X, Y 틱을 조정합니다', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/ipykernel_launcher.py:3: RuntimeWarning: divide by zero encountered in log
  This is separate from the ipykernel package so we can avoid doing imports until

2-4. 범례(Legend) 설정

plt.plot(np.arange(10), np.arange(10)*2)
plt.plot(np.arange(10), np.arange(10)**2)
plt.plot(np.arange(10), np.log(np.arange(10)))

# 타이틀 & font 설정
plt.title('범례 설정 예제입니다', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

# legend 설정
plt.legend(['10 * 2', '10 ** 2', 'log'], fontsize=15)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/ipykernel_launcher.py:3: RuntimeWarning: divide by zero encountered in log
  This is separate from the ipykernel package so we can avoid doing imports until

2-5. X와 Y의 한계점(Limit) 설정

xlim(), ylim()

plt.plot(np.arange(10), np.arange(10)*2)
plt.plot(np.arange(10), np.arange(10)**2)
plt.plot(np.arange(10), np.log(np.arange(10)))

# 타이틀 & font 설정
plt.title('이것은 타이틀 입니다', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

# legend 설정
plt.legend(['10 * 2', '10 ** 2', 'log'], fontsize=15)

# x, y limit 설정
plt.xlim(0, 5)
plt.ylim(0.5, 10)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/ipykernel_launcher.py:3: RuntimeWarning: divide by zero encountered in log
  This is separate from the ipykernel package so we can avoid doing imports until

2-6. 스타일 세부 설정 - 마커, 라인, 컬러

스타일 세부 설정은 마커, 선의 종류 설정, 그리고 컬러가 있으며, 문자열로 세부설정을 하게 됩니다.

세부 도큐먼트 확인하기

marker의 종류 * ‘.’ point marker * ‘,’ pixel marker * ‘o’ circle marker * ‘v’ triangle_down marker * ‘^’ triangle_up marker * ‘<’ triangle_left marker * ‘>’ triangle_right marker * ‘1’ tri_down marker * ‘2’ tri_up marker * ‘3’ tri_left marker * ‘4’ tri_right marker * ‘s’ square marker * ‘p’ pentagon marker * ‘’ star marker ’h’ hexagon1 marker * ‘H’ hexagon2 marker * ‘+’ plus marker * ‘x’ x marker * ‘D’ diamond marker * ‘d’ thin_diamond marker * ‘|’ vline marker * ’_’ hline marker

plt.plot(np.arange(10), np.arange(10)*2, marker='o', markersize=5)
plt.plot(np.arange(10), np.arange(10)*2 - 10, marker='v', markersize=10)
plt.plot(np.arange(10), np.arange(10)*2 - 20, marker='+', markersize=15)
plt.plot(np.arange(10), np.arange(10)*2 - 30, marker='*', markersize=20)

# 타이틀 & font 설정
plt.title('마커 설정 예제', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

line의 종류 * ‘-’ solid line style * ‘–’ dashed line style * ‘-.’ dash-dot line style * ‘:’ dotted line style

plt.plot(np.arange(10), np.arange(10)*2, marker='o', linestyle='')
plt.plot(np.arange(10), np.arange(10)*2 - 10, marker='o', linestyle='-')
plt.plot(np.arange(10), np.arange(10)*2 - 20, marker='v', linestyle='--')
plt.plot(np.arange(10), np.arange(10)*2 - 30, marker='+', linestyle='-.')
plt.plot(np.arange(10), np.arange(10)*2 - 40, marker='*', linestyle=':')

# 타이틀 & font 설정
plt.title('다양한 선의 종류 예제', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

color의 종류 * ‘b’ blue * ‘g’ green * ‘r’ red * ‘c’ cyan * ‘m’ magenta * ‘y’ yellow * ‘k’ black * ‘w’ white

plt.plot(np.arange(10), np.arange(10)*2, marker='o', linestyle='-', color='b')
plt.plot(np.arange(10), np.arange(10)*2 - 10, marker='v', linestyle='--', color='c')
plt.plot(np.arange(10), np.arange(10)*2 - 20, marker='+', linestyle='-.', color='y')
plt.plot(np.arange(10), np.arange(10)*2 - 30, marker='*', linestyle=':', color='r')

# 타이틀 & font 설정
plt.title('색상 설정 예제', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

plt.plot(np.arange(10), np.arange(10)*2, color='b', alpha=0.1)
plt.plot(np.arange(10), np.arange(10)*2 - 10, color='b', alpha=0.3)
plt.plot(np.arange(10), np.arange(10)*2 - 20, color='b', alpha=0.6)
plt.plot(np.arange(10), np.arange(10)*2 - 30, color='b', alpha=1.0)

# 타이틀 & font 설정
plt.title('투명도 (alpha) 설정 예제', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

2-7. 그리드 설정

plt.plot(np.arange(10), np.arange(10)*2, marker='o', linestyle='-', color='b')
plt.plot(np.arange(10), np.arange(10)*2 - 10, marker='v', linestyle='--', color='c')
plt.plot(np.arange(10), np.arange(10)*2 - 20, marker='+', linestyle='-.', color='y')
plt.plot(np.arange(10), np.arange(10)*2 - 30, marker='*', linestyle=':', color='r')

# 타이틀 & font 설정
plt.title('그리드 설정 예제', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

# grid 옵션 추가
plt.grid()

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

## 2-8 annotate 설정
plt.plot(np.arange(10), np.arange(10)*2, marker='o', linestyle='-', color='b')
plt.plot(np.arange(10), np.arange(10)*2 - 10, marker='v', linestyle='--', color='c')
plt.plot(np.arange(10), np.arange(10)*2 - 20, marker='+', linestyle='-.', color='y')
plt.plot(np.arange(10), np.arange(10)*2 - 30, marker='*', linestyle=':', color='r')

# 타이틀 & font 설정
plt.title('그리드 설정 예제', fontsize=20)

# X축 & Y축 Label 설정
plt.xlabel('X축', fontsize=20)
plt.ylabel('Y축', fontsize=20)

# X tick, Y tick 설정
plt.xticks(rotation=90)
plt.yticks(rotation=30)

# annotate 설정
plt.annotate('코로나 사태 발생 지점', xy=(3, -20), xytext=(3, -25), arrowprops=dict(facecolor='black', shrink=0.05))

# grid 옵션 추가
plt.grid()

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

matplotlib 을 활용한 다양한 그래프 그리기

pyplot 공식 도큐먼트 살펴보기

1. Scatterplot

0 ~ 1 사이의 임의의 랜덤한 값을 생성합니다.

np.random.rand(50)
array([0.29626504, 0.78371348, 0.11357925, 0.21256524, 0.8109623 ,
       0.33517112, 0.68046713, 0.28353737, 0.12155099, 0.94619289,
       0.69900728, 0.55185715, 0.82033173, 0.11200389, 0.91439391,
       0.11403073, 0.60428939, 0.52969614, 0.09555855, 0.35015891,
       0.25106891, 0.43855905, 0.91421888, 0.99440876, 0.63035013,
       0.04861833, 0.94204009, 0.03636596, 0.33057959, 0.90177104,
       0.48091921, 0.00494735, 0.54410306, 0.27708987, 0.26808791,
       0.49820038, 0.3969647 , 0.72744635, 0.70675491, 0.18997341,
       0.84598122, 0.91546396, 0.99657786, 0.29806435, 0.82270311,
       0.36317454, 0.30802989, 0.44184502, 0.4875401 , 0.37602673])

0 부터 50개의 값을 순차적으로 생성합니다.

np.arange(50)
array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
       17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,
       34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49])

1-1. x, y, colors, area 설정하기

  • colors 는 임의 값을 color 값으로 변환합니다.
  • area는 점의 넓이를 나타냅니다. 값이 커지면 당연히 넓이도 커집니다.
x = np.random.rand(50)
y = np.random.rand(50)
colors = np.arange(50)
area = x * y * 1000
plt.scatter(x, y, s=area, c=colors)
plt.show()

1-2. cmap과 alpha

  • cmap에 컬러를 지정하면, 컬러 값을 모두 같게 가져갈 수도 있습니다.
  • alpha값은 투명도를 나타내며 0 ~ 1 사이의 값을 지정해 줄 수 있으며, 0에 가까울 수록 투명한 값을 가집니다.
np.random.rand(50)
array([0.78516521, 0.54489727, 0.83812005, 0.16160557, 0.19091308,
       0.22809742, 0.97868944, 0.36879998, 0.03570702, 0.41551716,
       0.70459881, 0.6113276 , 0.19187684, 0.22188036, 0.41030993,
       0.52020618, 0.3816434 , 0.57140818, 0.63444532, 0.80470719,
       0.04899969, 0.62245326, 0.31310982, 0.38447058, 0.8117971 ,
       0.65465056, 0.56533836, 0.73710174, 0.21237264, 0.48956598,
       0.17043096, 0.07870155, 0.63045311, 0.45282431, 0.09999136,
       0.85872203, 0.97021617, 0.49723785, 0.98449735, 0.14325659,
       0.69517703, 0.85776342, 0.26192053, 0.08704771, 0.97536983,
       0.47573521, 0.9043739 , 0.12915836, 0.51061284, 0.62506511])
plt.figure(figsize=(12, 6))

plt.subplot(131)
plt.scatter(x, y, s=area, cmap='blue', alpha=0.1)
plt.title('alpha=0.1')

plt.subplot(132)
plt.title('alpha=0.5')
plt.scatter(x, y, s=area, cmap='blue', alpha=0.5)

plt.subplot(133)
plt.title('alpha=1.0')
plt.scatter(x, y, s=area, cmap='blue', alpha=1.0)

plt.show()

2. Barplot, Barhplot

1개의 canvas 안에 다중 그래프 그리기

2-1. 기본 Barplot 그리기

x = ['Math', 'Programming', 'Data Science', 'Art', 'English', 'Physics']
y = [66, 80, 60, 50, 80, 10]

plt.figure(figsize=(6, 3))
# plt.bar(x, y)
plt.bar(x, y, align='center', alpha=0.7, color='red')
plt.xticks(x)
plt.ylabel('Number of Students')
plt.title('Subjects')

plt.show()

2-2. 기본 Barhplot 그리기

barh 함수에서는 xticks로 설정했던 부분을 yticks로 변경합니다.

x = ['Math', 'Programming', 'Data Science', 'Art', 'English', 'Physics']
y = [66, 80, 60, 50, 80, 10]

plt.barh(x, y, align='center', alpha=0.7, color='green')
plt.yticks(x)
plt.xlabel('Number of Students')
plt.title('Subjects')

plt.show()

Batplot에서 비교 그래프 그리기

x_label = ['Math', 'Programming', 'Data Science', 'Art', 'English', 'Physics']
x = np.arange(len(x_label))
y_1 = [66, 80, 60, 50, 80, 10]
y_2 = [55, 90, 40, 60, 70, 20]

# 넓이 지정
width = 0.35

# subplots 생성
fig, axes = plt.subplots()

# 넓이 설정
axes.bar(x - width/2, y_1, width, align='center', alpha=0.5)
axes.bar(x + width/2, y_2, width, align='center', alpha=0.8)

# xtick 설정
plt.xticks(x)
axes.set_xticklabels(x_label)
plt.ylabel('Number of Students')
plt.title('Subjects')

plt.legend(['john', 'peter'])

plt.show()

x_label = ['Math', 'Programming', 'Data Science', 'Art', 'English', 'Physics']
x = np.arange(len(x_label))
y_1 = [66, 80, 60, 50, 80, 10]
y_2 = [55, 90, 40, 60, 70, 20]

# 넓이 지정
width = 0.35

# subplots 생성
fig, axes = plt.subplots()

# 넓이 설정
axes.barh(x - width/2, y_1, width, align='center', alpha=0.5, color='green')
axes.barh(x + width/2, y_2, width, align='center', alpha=0.8, color='red')

# xtick 설정
plt.yticks(x)
axes.set_yticklabels(x_label)
plt.xlabel('Number of Students')
plt.title('Subjects')

plt.legend(['john', 'peter'])

plt.show()

3. Line Plot

3-1. 기본 lineplot 그리기

x = np.arange(0, 10, 0.1)
y = 1 + np.sin(x)

plt.plot(x, y)

plt.xlabel('x value', fontsize=15)
plt.ylabel('y value', fontsize=15)
plt.title('sin graph', fontsize=18)

plt.grid()

plt.show()

3-2. 2개 이상의 그래프 그리기

  • color: 컬러 옵션
  • alpha: 투명도 옵션
x = np.arange(0, 10, 0.1)
y_1 = 1 + np.sin(x)
y_2 = 1 + np.cos(x)

plt.plot(x, y_1, label='1+sin', color='blue', alpha=0.3)
plt.plot(x, y_2, label='1+cos', color='red', alpha=0.7)

plt.xlabel('x value', fontsize=15)
plt.ylabel('y value', fontsize=15)
plt.title('sin and cos graph', fontsize=18)

plt.grid()
plt.legend()

plt.show()

3-3. 마커 스타일링

  • marker: 마커 옵션
x = np.arange(0, 10, 0.1)
y_1 = 1 + np.sin(x)
y_2 = 1 + np.cos(x)

plt.plot(x, y_1, label='1+sin', color='blue', alpha=0.3, marker='o')
plt.plot(x, y_2, label='1+cos', color='red', alpha=0.7, marker='+')

plt.xlabel('x value', fontsize=15)
plt.ylabel('y value', fontsize=15)
plt.title('sin and cos graph', fontsize=18)

plt.grid()
plt.legend()

plt.show()

3-4 라인 스타일 변경하기

  • linestyle: 라인 스타일 변경 옵션
x = np.arange(0, 10, 0.1)
y_1 = 1 + np.sin(x)
y_2 = 1 + np.cos(x)

plt.plot(x, y_1, label='1+sin', color='blue', linestyle=':')
plt.plot(x, y_2, label='1+cos', color='red', linestyle='-.')

plt.xlabel('x value', fontsize=15)
plt.ylabel('y value', fontsize=15)
plt.title('sin and cos graph', fontsize=18)

plt.grid()
plt.legend()

plt.show()

4. Areaplot (Filled Area)

matplotlib에서 area plot을 그리고자 할 때는 fill_between 함수를 사용합니다.

y = np.random.randint(low=5, high=10, size=20)
y
array([5, 6, 9, 9, 5, 8, 7, 8, 5, 7, 7, 8, 9, 5, 5, 9, 8, 8, 7, 5])

4-1. 기본 areaplot 그리기

x = np.arange(1,21)
y =  np.random.randint(low=5, high=10, size=20)

# fill_between으로 색칠하기
plt.fill_between(x, y, color="green", alpha=0.6)
plt.show()

4-2. 경계선을 굵게 그리고 area는 옅게 그리는 효과 적용

plt.fill_between(x, y, color="green", alpha=0.3)
plt.plot(x, y, color="green", alpha=0.8)

4-3. 여러 그래프를 겹쳐서 표현

x = np.arange(1, 10, 0.05)
y_1 =  np.cos(x)+1
y_2 =  np.sin(x)+1
y_3 = y_1 * y_2 / np.pi

plt.fill_between(x, y_1, color="green", alpha=0.1)
plt.fill_between(x, y_2, color="blue", alpha=0.2)
plt.fill_between(x, y_3, color="red", alpha=0.3)

5. Histogram

5-1. 기본 Histogram 그리기

N = 100000
bins = 30

x = np.random.randn(N)

plt.hist(x, bins=bins)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

  • sharey: y축을 다중 그래프가 share
  • tight_layout: graph의 패딩을 자동으로 조절해주어 fit한 graph를 생성

5-2. 다중 Histogram 그리기

N = 100000
bins = 30

x = np.random.randn(N)

fig, axs = plt.subplots(1, 3, 
                        sharey=True, 
                        tight_layout=True
                       )

fig.set_size_inches(12, 5)

axs[0].hist(x, bins=bins)
axs[1].hist(x, bins=bins*2)
axs[2].hist(x, bins=bins*4)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

5-3. Y축에 Density 표기

N = 100000
bins = 30

x = np.random.randn(N)

fig, axs = plt.subplots(1, 2, 
                        tight_layout=True
                       )
fig.set_size_inches(9, 3)

# density=True 값을 통하여 Y축에 density를 표기할 수 있습니다.
axs[0].hist(x, bins=bins, density=True, cumulative=True)
axs[1].hist(x, bins=bins, density=True)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

6. Pie Chart

pie chart 옵션

  • explode: 파이에서 툭 튀어져 나온 비율
  • autopct: 퍼센트 자동으로 표기
  • shadow: 그림자 표시
  • startangle: 파이를 그리기 시작할 각도

texts, autotexts 인자를 리턴 받습니다.

texts는 label에 대한 텍스트 효과를

autotexts는 파이 위에 그려지는 텍스트 효과를 다룰 때 활용합니다.

labels = ['Samsung', 'Huawei', 'Apple', 'Xiaomi', 'Oppo', 'Etc']
sizes = [20.4, 15.8, 10.5, 9, 7.6, 36.7]
explode = (0.3, 0, 0, 0, 0, 0)

# texts, autotexts 인자를 활용하여 텍스트 스타일링을 적용합니다
patches, texts, autotexts = plt.pie(sizes, 
                                    explode=explode, 
                                    labels=labels,  
                                    autopct='%1.1f%%',
                                    shadow=True, 
                                    startangle=90)

plt.title('Smartphone pie', fontsize=15)

# label 텍스트에 대한 스타일 적용
for t in texts:
    t.set_fontsize(12)
    t.set_color('gray')
    
# pie 위의 텍스트에 대한 스타일 적용
for t in autotexts:
    t.set_color("white")
    t.set_fontsize(18)

plt.show()

7. Box Plot

샘플 데이터를 생성합니다.

# 샘플 데이터 생성
spread = np.random.rand(50) * 100
center = np.ones(25) * 50
flier_high = np.random.rand(10) * 100 + 100
flier_low = np.random.rand(10) * -100
data = np.concatenate((spread, center, flier_high, flier_low))

7-1 기본 박스플롯 생성

plt.boxplot(data)
plt.tight_layout()
plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

7-2. 다중 박스플롯 생성

# 샘플 데이터 생성
spread = np.random.rand(50) * 100
center = np.ones(25) * 50
flier_high = np.random.rand(10) * 100 + 100
flier_low = np.random.rand(10) * -100
data = np.concatenate((spread, center, flier_high, flier_low))

spread = np.random.rand(50) * 100
center = np.ones(25) * 40

flier_high = np.random.rand(10) * 100 + 100
flier_low = np.random.rand(10) * -100

d2 = np.concatenate((spread, center, flier_high, flier_low))

data.shape = (-1, 1)
d2.shape = (-1, 1)

data = [data, d2, d2[::2,0]]

boxplot()으로 매우 쉽게 생성할 수 있습니다.

다중 그래프 생성을 위해서는 data 자체가 2차원으로 구성되어 있어야 합니다.

row와 column으로 구성된 DataFrame에서 Column은 X축에 Row는 Y축에 구성된다고 이해하시면 됩니다.

plt.boxplot(data)
plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

7-3. Box Plot 축 바꾸기

vert=False 옵션을 통해 표시하고자 하는 축을 바꿀 수 있습니다.

plt.title('Horizontal Box Plot', fontsize=15)
plt.boxplot(data, vert=False)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

7-4. Outlier 마커 심볼과 컬러 변경

outlier_marker = dict(markerfacecolor='r', marker='D')
plt.title('Changed Outlier Symbols', fontsize=15)
plt.boxplot(data, flierprops=outlier_marker)

plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

8. 3D 그래프 그리기

3d 로 그래프를 그리기 위해서는 mplot3d를 추가로 import 합니다

from mpl_toolkits import mplot3d

8-1. 밑그림 그리기 (캔버스)

fig = plt.figure()
ax = plt.axes(projection='3d')

8-2. 3d plot 그리기

# project=3d로 설정합니다
ax = plt.axes(projection='3d')

# x, y, z 데이터를 생성합니다
z = np.linspace(0, 15, 1000)
x = np.sin(z)
y = np.cos(z)

ax.plot(x, y, z, 'gray')
plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

# project=3d로 설정합니다
ax = plt.axes(projection='3d')

sample_size = 100
x = np.cumsum(np.random.normal(0, 1, sample_size))
y = np.cumsum(np.random.normal(0, 1, sample_size))
z = np.cumsum(np.random.normal(0, 1, sample_size))

ax.plot3D(x, y, z, alpha=0.6, marker='o')

plt.title("ax.plot")
plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

8-3. 3d-scatter 그리기

fig = plt.figure(figsize=(10, 5))
ax = fig.add_subplot(111, projection='3d') # Axe3D object

sample_size = 500

x = np.cumsum(np.random.normal(0, 5, sample_size))
y = np.cumsum(np.random.normal(0, 5, sample_size))
z = np.cumsum(np.random.normal(0, 5, sample_size))

ax.scatter(x, y, z, c = z, s=20, alpha=0.5, cmap='Greens')

plt.title("ax.scatter")
plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

8-4. contour3D 그리기 (등고선)

x = np.linspace(-6, 6, 30)
y = np.linspace(-6, 6, 30)
x, y = np.meshgrid(x, y)

z = np.sin(np.sqrt(x**2 + y**2))

fig = plt.figure(figsize=(12, 6))
ax = plt.axes(projection='3d')

ax.contour3D(x, y, z, 20, cmap='Reds')

plt.title("ax.contour3D")
plt.show()
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0.0, flags=flags)
/home/ubuntu/anaconda3/envs/tensorflow2_p36/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 8722 missing from current font.
  font.set_text(s, 0, flags=flags)

9. imshow

이미지(image) 데이터와 유사하게 행과 열을 가진 2차원의 데이터를 시각화 할 때는 imshow를 활용합니다.

from sklearn.datasets import load_digits

digits = load_digits()
X = digits.images[:10]
X[0]
array([[ 0.,  0.,  5., 13.,  9.,  1.,  0.,  0.],
       [ 0.,  0., 13., 15., 10., 15.,  5.,  0.],
       [ 0.,  3., 15.,  2.,  0., 11.,  8.,  0.],
       [ 0.,  4., 12.,  0.,  0.,  8.,  8.,  0.],
       [ 0.,  5.,  8.,  0.,  0.,  9.,  8.,  0.],
       [ 0.,  4., 11.,  0.,  1., 12.,  7.,  0.],
       [ 0.,  2., 14.,  5., 10., 12.,  0.,  0.],
       [ 0.,  0.,  6., 13., 10.,  0.,  0.,  0.]])

  • load_digits는 0~16 값을 가지는 array로 이루어져 있습니다.

  • 1개의 array는 8 X 8 배열 안에 표현되어 있습니다.

  • 숫자는 0~9까지 이루어져있습니다.

fig, axes = plt.subplots(nrows=2, ncols=5, sharex=True, figsize=(12, 6), sharey=True)

for i in range(10):
    axes[i//5][i%5].imshow(X[i], cmap='Blues')
    axes[i//5][i%5].set_title(str(i), fontsize=20)
    
plt.tight_layout()
plt.show()