vcs/_4.python/matplotlib/matplotlib1_plot6_yy.py at master · bunshue/vcs · GitHub

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"""

雙y軸

"""

print("------------------------------------------------------------") # 60個

# 共同

import os

import sys

import time

import math

import random

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

font_filename = "D:/_git/vcs/_1.data/______test_files1/_font/msch.ttf"

# 設定中文字型及負號正確顯示

# 設定中文字型檔

plt.rcParams["font.sans-serif"] = "Microsoft JhengHei" # 將字體換成 Microsoft JhengHei

# 設定負號

plt.rcParams["axes.unicode_minus"] = False # 讓負號可正常顯示

plt.rcParams["font.size"] = 12 # 設定字型大小

print("------------------------------------------------------------") # 60個

print("使用 plt.subplots() 做一圖")

x = np.linspace(0, 10, 50)

y = np.sin(x)

# fig, ax = plt.subplots() same

fig, ax = plt.subplots(1, 1)

ax.plot(x, y, "r-o", label="Sin(x)")

ax.set_xlabel("弧度", color="green")

ax.set_ylabel("Sin(x)", color="red")

ax.set_title("sin(x)", size=20)

plt.show()

print("------------------------------------------------------------") # 60個

# 共同參數

x = np.linspace(0, 2 * np.pi, 30)

y = np.sin(x)

y0 = np.sin(x)

y1 = np.cos(x)

y2 = np.tan(x)

print("------------------------------------------------------------") # 60個

print("兩Y軸不同刻度, plot + plot")

x = np.linspace(0, 10, 50)

sinus = np.sin(x)

sinhs = np.sinh(x)

fig, ax = plt.subplots()

ax2 = ax.twinx() # 使用相同的 x 軸

# 第1軸

ax.plot(x, sinus, "r-o", label="Sin(x)")

ax.set_xlabel("弧度", color="green")

ax.set_ylabel("Sin(x)", color="red")

ax.legend(loc="best")

# 第2軸

ax2.plot(x, sinhs, "g--", label="Sinh(x)")

ax2.set_ylabel("Sinh(x)", color="blue")

ax2.legend(loc="best")

ax.set_title("兩Y軸不同刻度 plot + plot", size=20)

plt.show()

print("------------------------------------------------------------") # 60個

x = np.linspace(0, 10, 50)

sinus = np.sin(x)

sinhs = np.sinh(x)

fig, ax = plt.subplots()

ax2 = ax.twinx() # 使用相同的 x 軸

lns1 = ax.plot(x, sinus, "r-o", label="Sin(x)")

ax.set_xlabel("x", color="green")

ax.set_ylabel("Sin(x)", color="red")

lns2 = ax2.plot(x, sinhs, "g--", label="Sinh(x)")

ax2.set_ylabel("Sinh(x)", color="blue")

# 自行建立圖例來顯示所有標籤

lns = lns1 + lns2

labs = [l.get_label() for l in lns]

ax.legend(lns, labs, loc="best")

plt.show()

print("------------------------------------------------------------") # 60個

x = np.linspace(0, 10, 50)

sinus = np.sin(x)

sinhs = np.sinh(x)

fig, ax = plt.subplots()

ax2 = ax.twinx() # 使用相同的 x 軸

ax.plot(x, sinus, "r-o")

ax.set_xlabel("x", color="green")

ax.set_ylabel("Sin(x)", color="red")

ax2.plot(x, sinhs, "g--")

ax2.set_ylabel("Sinh(x)", color="blue")

# 指定圖表標題文字

ax.set_title("Sin和Cos三角函數的波型", fontsize="large")

# 更改刻度的外觀

for tick in ax.xaxis.get_ticklabels():

tick.set_fontsize("large")

tick.set_fontname("Times New Roman")

tick.set_color("blue")

tick.set_weight("bold")

plt.show()

print("------------------------------------------------------------") # 60個

x = np.linspace(0, 10, 50)

sinus = np.sin(x)

sinhs = np.sinh(x)

fig, ax = plt.subplots()

ax2 = ax.twinx() # 使用相同的 x 軸

ax.plot(x, sinus, "r-o")

ax.set_xlabel("x", color="green")

ax.set_ylabel("Sin(x)", color="red")

ax2.plot(x, sinhs, "g--")

ax2.set_ylabel("Sinh(x)", color="blue")

plt.xticks(range(0, 11))

ax.set_yticks(np.linspace(-1, 1, 10))

ax2.set_yticks(np.linspace(0, 12000, 10))

plt.show()

print("------------------------------------------------------------") # 60個

print("兩Y軸不同刻度, plot + bar")

import matplotlib.gridspec as gridspec

x = np.linspace(0, 6.28, 10)

y = np.sin(x * 2)

y2 = np.sin(x * 2) * np.sin(x * 2) * 10

fig = plt.figure(figsize=(12, 8)) # 圖像大小[英吋]

gs = gridspec.GridSpec(4, 1, figure=fig)

ax = fig.add_subplot()

ax2 = ax.twinx() # 使用相同的 x 軸

ax.plot(x, y, marker="", alpha=0.8)

ax.grid(20)

ax2.bar(

y2,

alpha=0.2,

label="hold_volume",

color="pink",

)

ax.set_title("兩Y軸不同刻度 plot + bar", size=20)

plt.show()

print("------------------------------------------------------------") # 60個

# 新竹市平均高溫 °C

temperature_high = [

19.1,

19.4,

21.6,

25.6,

28.9,

31.5,

33.2,

32.8,

31.2,

28,

25.1,

21.1,

26.5,

]

# 新竹市日均氣溫 °C

temperature_average = [

15.7,

16,

18,

21.9,

25.2,

27.9,

29.3,

28.9,

27.3,

24.4,

21.5,

17.7,

22.8,

]

# 新竹市平均低溫 °C

temperature_low = [

13.1,

13.4,

15.2,

18.9,

22.2,

24.9,

26,

25.8,

24.4,

21.8,

18.8,

15.1,

20,

]

# 新竹市平均降雨量 mm

rainfall_average = [

75.7,

123,

159.8,

161.9,

249,

252,

120.2,

197.1,

174.5,

53.6,

51.1,

57.7,

1675.6,

]

print(len(temperature_high))

print(len(temperature_average))

print(len(temperature_low))

print(len(rainfall_average))

x = np.arange(0, 12, 1)

print(len(x))

print(x)

fig, ax1 = plt.subplots()

ax2 = ax1.twinx() # 使用相同的 x 軸

ax1.plot(x, temperature_high[:12], "r-")

ax1.plot(x, temperature_average[:12], "g-")

ax1.plot(x, temperature_low[:12], "b-")

ax1.set_xlabel("月份")

ax1.set_ylabel("氣溫")

ax2.plot(x, rainfall_average[:12], "yellow")

ax2.set_ylabel("雨量")

plt.show()

print("------------------------------------------------------------") # 60個

dists = {

"區名": [

"中正區",

"板橋區",

"桃園區",

"北屯區",

"安南區",

"三民區",

"大安區",

"永和區",

"八德區",

"前鎮區",

"鳳山區",

"信義區",

"新店區",

"人口": [

159598,

551452,

441287,

275207,

192327,

343203,

309835,

222531,

198473,

189623,

359125,

225561,

302070,

"面積": [

7.6071,

23.1373,

34.8046,

62.7034,

107.2016,

19.7866,

11.3614,

5.7138,

33.7111,

19.1207,

26.7590,

11.2077,

120.2255,

}

df = pd.DataFrame(dists, columns=["人口", "面積"], index=dists["區名"])

print(df)

fig, ax = plt.subplots()

fig.suptitle("分區統計")

ax.set_ylabel("人口")

ax.set_xlabel("分區")

ax2 = ax.twinx() # 使用相同的 x 軸

ax2.set_ylabel("面積")

df["人口"].plot(ax=ax, style="b--o", use_index=True, rot=90)

df["面積"].plot(ax=ax2, style="g-s", use_index=True, rot=90)

plt.show()

print("------------------------------------------------------------") # 60個

print("作業完成")

print("------------------------------------------------------------") # 60個

vcs/_4.python/matplotlib/matplotlib1_plot6_yy.py at master · bunshue/vcs · GitHub

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