仅需10道题轻松掌握Matplotlib图形处理 | Python技能树征题
仅需10道题轻松掌握Matplotlib图形处理 | Python技能树征题
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- 0. 前言
- 1. 第 1 题：曲线图的绘制
- 2. 第 2 题：散点图的绘制
- 3. 第 3 题：条形图的绘制
- 4. 第 4 题：饼图的绘制
- 5. 第 5 题：直方图的绘制
- 6. 第 6 题：添加标题
- 7. 第 7 题：为坐标轴添加标签
- 8. 第 8 题：在图形中添加文本说明
- 9. 第 9 题：在图形中添加箭头
- 10. 第 10 题：在图形中添加图例
- 试题代码地址
0. 前言
Matplotlib 是 Python 的绘图库，它提供了一整套和 matlab 相似的命令 API，可以生成出版质量级别的精美图形，Matplotlib 使绘图变得非常简单，我们就通过 10 道 Python 编程题来掌握使用 Matplotlib 库进行图形绘制吧！
1. 第 1 题：曲线图的绘制
知识点描述：绘制曲线图。
问题描述：在同一图片中绘制函数 y = x 2 y=x^2 y=x2， y = l o g e x y=log_ex y=logex以及 y = s i n ( x ) y=sin(x) y=sin(x)，请从以下选项中选出你认为正确的答案：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 100)
y_1 = np.square(x)
y_2 = np.log(x)
y_3 = np.sin(x)
fig = plt.figure()
plt.plot(x,y_1)
fig = plt.figure()
plt.plot(x,y_2)
fig = plt.figure()
plt.plot(x,y_3)
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 100)
y_1 = np.square(x)
y_2 = np.log(x)
y_3 = np.sin(x)
fig = plt.figure()
plt.plot(x,y_1)
plt.plot(x,y_2)
plt.plot(x,y_3)
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 100)
y_1 = np.square(x)
y_2 = np.log(x)
y_3 = np.sin(x)
plt.plot(x,y_1, y_2, y_3)
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 100)
y_1 = np.square(x)
y_2 = np.log(x)
y_3 = np.sin(x)
fig = plt.figure()
plt.plot(x,y_1, y_2, y_3)
plt.show()
正确答案： B
2. 第 2 题：散点图的绘制
知识点描述：绘制散点图。
问题描述：绘制函数 y = s i n ( x ) y=sin(x) y=sin(x)上的点，请从以下选项中选出你认为正确的答案：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 50)
y = np.sin(x)
fig = plt.figure()
plt.plot(x, y)
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 50)
y = np.sin(x)
fig = plt.figure()
plt.barh(x, y)
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 50)
y = np.sin(x)
fig = plt.figure()
plt.bar(x, y)
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0.1, 2 * np.pi, 50)
y = np.sin(x)
fig = plt.figure()
plt.scatter(x, y)
plt.show()
正确答案： D
3. 第 3 题：条形图的绘制
知识点描述：绘制条形图。
问题描述：绘制多组条形图，比较不同年份相应季度的销量，请从以下选项中选出你认为正确的选项：
A.
import numpy as np
import matplotlib.pyplot as plt
data = [[10., 20., 30., 20.],[40., 25., 53., 18.],[6., 22., 52., 19.]]
x = np.arange(4)
colors = ['r', 'g', 'b']
for i in range(len(data)):
plt.bar(x + i * 0.25, data[:i], color = colors[i], width = 0.25)
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
data = [[10., 20., 30., 20.],[40., 25., 53., 18.],[6., 22., 52., 19.]]
x = np.arange(4)
colors = ['r', 'g', 'b']
for i in range(len(data)):
plt.plot(x + i * 0.25, data[:i], color = colors[i], width = 0.25)
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
data = [[10., 20., 30., 20.],[40., 25., 53., 18.],[6., 22., 52., 19.]]
x = np.arange(4)
colors = ['r', 'g', 'b']
for i in range(len(data)):
plt.bar(x + i * 0.25, data[i], color = colors[i], width = 0.25)
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
data = [[10., 20., 30., 20.],[40., 25., 53., 18.],[6., 22., 52., 19.]]
x = np.arange(4)
colors = ['r', 'g', 'b']
for i in range(len(data)):
plt.plot(x + i * 0.25, data[i], color = colors[i], width = 0.25)
plt.show()
正确答案： C
4. 第 4 题：饼图的绘制
知识点描述：使用饼图对比数量间的相对关系。
问题描述：绘制饼图，对比列表 [10, 15, 30, 20] 数量间的相对关系，请从以下选项中选出你认为正确的选项：
A.
import matplotlib.pyplot as plt
data = [10, 15, 30, 20]
sum_data = sum(data)
plt.pie(data / sum_data)
plt.show()
B.
import matplotlib.pyplot as plt
data = [10, 15, 30, 20]
plt.pie(sum(data))
plt.show()
C.
import matplotlib.pyplot as plt
data = [10, 15, 30, 20]
plt.pie(range(len(data)), data)
plt.show()
D.
import matplotlib.pyplot as plt
data = [10, 15, 30, 20]
plt.pie(data)
plt.show()
正确答案： D
5. 第 5 题：直方图的绘制
知识点描述：使用直方图表示概率分布。
问题描述：根据构造数组绘制直方图，请从以下选项中选出你认为正确的答案：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.random.randn(1024)
plt.hist(x, bins = 20)
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.random.randn(1024)
plt.hist(x, bins=x.shape)
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.random.randn(1024)
plt.hist(x.shape, x)
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.random.randn(1024)
plt.hist(x, x.shape)
plt.show()
正确答案： A
6. 第 6 题：添加标题
知识点描述：在图形中添加标题。
问题描述：为所绘制的图形添加中文标题，请从以下选项中选出你认为正确的答案：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-4, 4, 10005)
y = 5 * (x + 4.2) * (x + 4.) * (x - 2.5)
plt.title('曲线')
plt.plot(x, y, c = 'm')
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-4, 4, 10005)
y = 5 * (x + 4.2) * (x + 4.) * (x - 2.5)
plt.title('曲线')
plt.plot(x, y, c = 'm')
plt.rcParams['font.sans-serif'] = ['SimSun']
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-4, 4, 10005)
y = 5 * (x + 4.2) * (x + 4.) * (x - 2.5)
plt.plot(x, y, c = 'm', title='曲线')
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-4, 4, 10005)
y = 5 * (x + 4.2) * (x + 4.) * (x - 2.5)
plt.plot(x, y, c = 'm', title='曲线')
plt.rcParams['font.sans-serif'] = ['SimSun']
plt.show()
正确答案： B
7. 第 7 题：为坐标轴添加标签
知识点描述：为图形坐标轴的添加适当描述标签帮助用户理解图形所表达的含义。
问题描述：已知一函数用于描述加速运动，请绘制一图形表示时间与距离间关系：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
plt.xtitle('Time')
plt.ytitle('distance')
plt.plot(x, y, c = 'c')
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
plt.plot(x, y, c = 'c', xlabel = 'Time', ylable = 'distance')
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
plt.plot(x, y, c = 'c', xtitle = 'Time', ytitle = 'distance')
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
plt.xlabel('Time')
plt.ylabel('distance')
plt.plot(x, y, c = 'c')
plt.show()
正确答案：D
8. 第 8 题：在图形中添加文本说明
知识点描述：在图形中添加说明文本，凸显图中点或线的重要性。
问题描述：使用文本显式标记函数图像的中点，请从以下选项中选出你认为正确的答案：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = x[0]
y_mid = y[0]
plt.scatter(x_mid, y_mid)
plt.text(x_mid, y_mid, 'mid')
plt.plot(x, y, c = 'c')
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = (x[-1] - x[0]) / 2
y_mid = 2.0 * ((x[-1] - x[0]) / 2) + 0.5 * 5 * ((x[-1] - x[0]) / 2) ** 2
plt.scatter(x_mid, y_mid)
plt.text('mid')
plt.plot(x, y, c = 'c')
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = x[-1]
y_mid = y[-1]
plt.scatter(x_mid, y_mid)
plt.text(x_mid, y_mid, 'mid')
plt.plot(x, y, c = 'c')
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = (x[-1] - x[0]) / 2
y_mid = 2.0 * ((x[-1] - x[0]) / 2) + 0.5 * 5 * ((x[-1] - x[0]) / 2) ** 2
plt.scatter(x_mid, y_mid)
plt.text(x_mid, y_mid, 'mid')
plt.plot(x, y, c = 'c')
plt.show()
正确答案：D
9. 第 9 题：在图形中添加箭头
知识点描述：使用箭头说明图形中的特定部分。
问题描述：使用箭头显式标记函数图像的中点，请从以下选项中选出你认为正确的答案：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = (x[-1] - x[0]) / 2
y_mid = 2.0 * ((x[-1] - x[0]) / 2) + 0.5 * 5 * ((x[-1] - x[0]) / 2) ** 2
plt.annotate('mid',
ha = 'center', va = 'bottom',
xytext = (5, 30.),
xy = (x_mid, y_mid),
arrowprops = {
'facecolor' : 'black', 'shrink' : 0.05 })
plt.plot(x, y, c = 'c')
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = (x[-1] - x[0]) / 2
y_mid = 2.0 * ((x[-1] - x[0]) / 2) + 0.5 * 5 * ((x[-1] - x[0]) / 2) ** 2
plt.annotate('mid',
ha = 'center', va = 'bottom',
xytext = (5, 30.),
x = x_mid,
y = y_mid,
arrowprops = {
'facecolor' : 'black', 'shrink' : 0.05 })
plt.plot(x, y, c = 'c')
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = (x[-1] - x[0]) / 2
y_mid = 2.0 * ((x[-1] - x[0]) / 2) + 0.5 * 5 * ((x[-1] - x[0]) / 2) ** 2
plt.annotate('mid',
ha = 'center', va = 'bottom',
xtext = 5,
ytext = 30.,
xy = (x_mid, y_mid),
arrowprops = {
'facecolor' : 'black', 'shrink' : 0.05 })
plt.plot(x, y, c = 'c')
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 8, 1000)
y = 2.0 * x + 0.5 * 5 * x ** 2
x_mid = (x[-1] - x[0]) / 2
y_mid = 2.0 * ((x[-1] - x[0]) / 2) + 0.5 * 5 * ((x[-1] - x[0]) / 2) ** 2
plt.annotate('mid',
ha = 'center', va = 'bottom',
xtext = 5,
ytext = 30.,
xy = (x_mid, y_mid),
arrowprops = {
'facecolor' : 'black', 'shrink' : 0.05 })
plt.plot(x, y, c = 'c')
plt.show()
正确答案：A
10. 第 10 题：在图形中添加图例
知识点描述：为图形中的曲线和点添加相应的图例，以进行准确的区分。
问题描述：一图形中包含多条曲线和散点，为它们添加图例，请从以下选项中选出你认为正确的答案：
A.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 6, 1024)
data = np.random.standard_normal((150, 2))
y_1 = np.sin(x)
y_2 = np.cos(x)
plt.plot(x, y_1, c = 'm', lw = 3., text = 'sin(x)')
plt.plot(x, y_2, c = 'c', lw = 3., ls = '--', text = 'cos(x)')
plt.scatter(data[:,0], data[:, 1], c = 'y', text = 'random')
plt.legend()
plt.show()
B.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 6, 1024)
data = np.random.standard_normal((150, 2))
print(data.size)
y_1 = np.sin(x)
y_2 = np.cos(x)
plt.plot(x, y_1, c = 'm', lw = 3., title = 'sin(x)')
plt.plot(x, y_2, c = 'c', lw = 3., ls = '--', title = 'cos(x)')
plt.scatter(data[:,0], data[:,1], c = 'y', title = 'random')
plt.legend()
plt.show()
C.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 6, 1024)
data = np.random.standard_normal((150, 2))
y_1 = np.sin(x)
y_2 = np.cos(x)
plt.plot(x, y_1, c = 'm', lw = 3., label = 'sin(x)')
plt.plot(x, y_2, c = 'c', lw = 3., ls = '--', label = 'cos(x)')
plt.scatter(data[:, 0], data[:, 1], c = 'y', label = 'random')
plt.legend()
plt.show()
D.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 6, 1024)
data = np.random.standard_normal((150, 2))
y_1 = np.sin(x)
y_2 = np.cos(x)
plt.plot(x, y_1, c = 'm', lw = 3., legend = 'sin(x)')
plt.plot(x, y_2, c = 'c', lw = 3., ls = '--', legend = 'cos(x)')
plt.scatter(data[:, 0], data[:, 1], c = 'y', legend = 'random')
plt.legend()
plt.show()
正确答案：C
试题代码地址
https://codechina.csdn.net/LOVEmy134611/python_problem