python の matplotlib の生成例

ライブラリのインストールシンプルな折れ線グラフ折れ線・散布図・棒グラフの複数のグラフを描画折れ線・散布図・棒グラフの複数のグラフをそれぞれ描画エラーバー付きのグラフを描画複数の棒グラフを描画 1 複数の棒グラフを描画 2 x 軸のメモリ値を回転して描画軸のメモリの表記を変えて描画画像と文字列を表示

ライブラリのインストール

!pip install -q matplotlib japanize-matplotlib

シンプルな折れ線グラフ

import matplotlib.pyplot as plt
import japanize_matplotlib
import numpy as np

fig = plt.figure(figsize=(6.4, 4.8))
fig.suptitle('title')
# plt.subplots_adjust(wspace=0.2, hspace=0.2) # グラフ間の幅調整

ax = fig.add_subplot(1, 1, 1, xlabel='$x$', ylabel='$y$')

x = np.arange(0, 20, 1)
y = 2 * x * x

ax.plot(x, y, label="$y = 2x^{2}$")

ax.legend()

fig.savefig('example1.png') # eps, jpeg, jpg, pdf, pgf, png, ps, raw, rgba, svg, svgz, tif, tiff

# 画像を閉じる
# plt.clf()
# plt.close()

折れ線・散布図・棒グラフの複数のグラフを描画

import matplotlib.pyplot as plt
import japanize_matplotlib
import numpy as np

fig = plt.figure(figsize=(6.4, 4.8))
fig.suptitle('title')

ax = fig.add_subplot(1, 1, 1, xlabel='$x$', ylabel='$y$')

x1 = np.arange(0, 20, 1)
y1 = 3 * x1 
ax.plot(x1, y1, label="$y = 3x$")

x2 = np.arange(0, 20, 1)
y2 = 2 * x2
ax.scatter(x2, y2, label="$y = 2x$")

x3 = np.arange(0, 20, 1)
y3 = 1 * x3
ax.bar(x3, y3, label="$y = x$")

ax.legend()

fig.savefig('example2.png') # eps, jpeg, jpg, pdf, pgf, png, ps, raw, rgba, svg, svgz, tif, tiff

折れ線・散布図・棒グラフの複数のグラフをそれぞれ描画

import matplotlib.pyplot as plt
import japanize_matplotlib
import numpy as np

fig = plt.figure(figsize=(6.4 * 3, 4.8))
fig.suptitle('title')

ax1 = fig.add_subplot(1, 3, 1, xlabel='$x$', ylabel='$y$')
ax2 = fig.add_subplot(1, 3, 2, xlabel='$x$', ylabel='$y$')
ax3 = fig.add_subplot(1, 3, 3, xlabel='$x$', ylabel='$y$')

x1 = np.arange(0, 7, 0.1)
y1 = np.sin(x1)
ax1.plot(x1, y1, label="$y = 3x$")
ax1.set_title("折れ線グラフ sin")
ax1.legend()

x2 = np.arange(0, 7, 0.1)
y2 = np.cos(x2)
ax2.scatter(x2, y2, label="$y = 2x$")
ax2.set_title("散布図 cos")
ax2.legend()

x3 = np.arange(0, 20, 1)
y3 = 1 * x3
ax3.bar(x3, y3, label="$y = x$")
ax3.set_title("棒グラフ $y=x$")
ax3.legend()


fig.savefig('example3.png') # eps, jpeg, jpg, pdf, pgf, png, ps, raw, rgba, svg, svgz, tif, tiff

エラーバー付きのグラフを描画

import matplotlib.pyplot as plt
import japanize_matplotlib
import numpy as np

fig = plt.figure(figsize=(6.4, 4.8))
fig.suptitle('title')

ax = fig.add_subplot(1, 1, 1, xlabel='time', ylabel='score')

data = np.random.normal(50, 10, (10, 20)) # 平均50 標準偏差10
x = np.arange(len(data[0]))
mean = np.mean(data, axis=0) # 平均の取得
std = np.std(data, axis=0) # 標準偏差の取得

ax.set_ylim(0, 100)
ax.errorbar(x=x, y=mean, yerr=std, label="平均点と標準偏差")

ax.legend()

fig.savefig('example4.png') # eps, jpeg, jpg, pdf, pgf, png, ps, raw, rgba, svg, svgz, tif, tiff

複数の棒グラフを描画 1

https://inchblog.com/blog/how-to-draw-multiple-bar-charts-using-matplotlib

https://inchblog.com

📄 matplotlib を用いて複数の棒グラフを描画する

に解説があります．

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

fig = plt.figure(figsize=(6.4 * 1, 4.8))

ax = fig.add_subplot(1, 1, 1, xlabel='x', ylabel='y')

width = 0.2

df = pd.DataFrame(data=np.random.randint(1, 10, (5, 3)))
#    0  1  2
# 0  1  8  3
# 1  7  2  2
# 2  7  6  3
# 3  9  6  6
# 4  1  4  6

cols = df.columns
df_index = np.array(df.index)
for i, col in enumerate(cols):
    ax.bar(df_index+width*(i-len(cols)/2), df.loc[:, col], label=col, width=width, align='edge')
ax.legend()
fig.savefig('example5.png')

複数の棒グラフを描画 2

https://inchblog.com/blog/how-to-draw-multiple-bar-charts-using-matplotlib

に解説があります．

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

fig = plt.figure(figsize=(6.4 * 1, 4.8))

ax = fig.add_subplot(1, 1, 1, xlabel='x', ylabel='y')

width = 0.2

df = pd.DataFrame(data=np.random.randint(1, 10, (5, 3)))
#       A  B  C
# 2001  6  5  1
# 2002  8  5  5
# 2003  7  4  6
# 2004  4  3  7
# 2005  8  4  2

cols = df.columns
df_index = np.array(df.index)
for i, col in enumerate(cols):
    ax.bar(df_index+width*(i-len(cols)/2), df.loc[:, col], label=col, width=width, align='edge')
ax.legend()
fig.savefig('example6.png')

x 軸のメモリ値を回転して描画

from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure(figsize=(6.4 * 1, 4.8))

ax = fig.add_subplot(1, 1, 1, xlabel='time', ylabel='value')

time = [datetime(2020, 1, 25) + timedelta(days=i) for i in range(10)]
value = np.random.randint(1, 10, (10))
ax.bar(time, value, label="")
ax.xaxis.set_tick_params(rotation=90)

fig.savefig('example7.png')

軸のメモリの表記を変えて描画

y 軸をカンマ区切り、x 軸を日付表記にしました．

from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import ticker
from matplotlib import dates as mdates

def add_comma(x, pos):
    return f"{x:,.2f}"


fig = plt.figure(figsize=(6.4 * 1, 4.8))

ax = fig.add_subplot(1, 1, 1, xlabel='time', ylabel='value')

time = [mdates.date2num
        (datetime(
    year = 2020, 
    month = 1, 
    day = 25, 
    ) + timedelta(hours=i)) for i in range(10)]

value = np.random.randint(1000, 10000, (10))
ax.plot(time, value, label="")
ax.xaxis.set_tick_params(rotation=90)
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y年%m月%d日"))
ax.yaxis.set_major_formatter(ticker.FuncFormatter(add_comma))

fig.savefig('example9.png')

画像と文字列を表示

from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import ticker
from matplotlib import dates as mdates
from PIL import Image


fig = plt.figure(figsize=(6.4 * 3, 4.8))
fig.suptitle("title")

ax1 = fig.add_subplot(1, 2, 1, xlabel="", ylabel="")
ax2 = fig.add_subplot(1, 2, 2, xlabel="", ylabel="")

img_path = "/content/example1.png"
image = Image.open(img_path)
ax1.imshow(image, label="画像")
ax1.axis("off")

text="文字列"
ax2.text(x=0, y=0, s=f"(0, 0){text}", size=16)
ax2.text(x=0, y=0.5, s=f"(0, 0.5){text}", size=16)
ax2.text(x=0, y=1, s=f"(0, 1){text}", size=16)

ax2.text(x=0.5, y=0, s=f"(0.5, 0){text}", size=16)
ax2.text(x=0.5, y=0.5, s=f"(0.5, 0.5){text}", size=16)
ax2.text(x=0.5, y=1, s=f"(0.5, 1){text}", size=16)

ax2.text(x=1, y=0, s=f"(1, 0){text}", size=16)
ax2.text(x=1, y=0.5, s=f"(1, 0.5){text}", size=16)
ax2.text(x=1, y=1, s=f"(1, 1){text}", size=16)

ax2.axis("off")

fig.savefig('example10.png')
# plt.clf()
# plt.close()