link ：https://pan.baidu.com/s/1PlSosvbXm_jiNQYZ-VK6MA
Extraction code ：y8ma
1. graphics
2. Chart
3. Box chart
4.2D
5.Anaconda
1.√
2.×
3.×
4.×
1.C
2.C
3.D
4.D
5.A,B,C,D
1. answer ： Data visualization aims to use graphical means , Represent a set of data in a graphical form , And using data analysis and development tools to find the processing process of unknown information .
2. answer ： Line chart is to mark data into points , And connect these points in a certain order through a straight line , It reflects the changing trend of things along a certain dimension in the form of broken lines , It can clearly show the trend of data increase and decrease 、 rate 、 Characteristics such as regularity and peak value ; A column chart consists of a series of equal widths 、 A chart composed of uneven vertical rectangular bars , It uses the height of the rectangular bar to indicate how much data , To reflect the differences between different classification data ; The pie chart is composed of several areas of different sizes 、 A circular chart composed of sectors of different colors , It uses circles to represent the total amount of data , Each sector forming a circle represents the proportion of each item in the total data , It is mainly used to display the ratio between the size of each item and the sum of each item in the data .
3. answer ： When using pyplot API When drawing , Users need to use “import matplotlib.pyplot as plt” Statement import pyplot modular , Then use this module to call the drawing function to draw charts in the current canvas and drawing area ; When using object-oriented API When drawing , Users need to create canvas first （pyplot.Figure Class object ）, Then create a coordinate system style drawing area on the canvas （pyplot.Axes Class object ）, Then call the drawing method to create the graph , These created objects are combined to complete a complete drawing .
answer ：
# ———— The object-oriented approach
import numpy as np
import matplotlib.pyplot as plt
x_data = np.linspace(-np.pi, np.pi, 256, endpoint=True)
y_sin, y_cos = np.sin(x_data), np.cos(x_data)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x_data, y_sin)
ax.plot(x_data, y_cos)
plt.show()
# ———— Function oriented approach
import numpy as np
import matplotlib.pyplot as plt
x_data = np.linspace(-np.pi, np.pi, 256, endpoint=True)
y_sin, y_cos = np.sin(x_data), np.cos(x_data)
plt.plot(x_data, y_sin)
plt.plot(x_data, y_cos)
plt.show()
1.Line2D
2. Stacked graph
3.10
1.×
2.√
3.×
1.D
2.C
3.B
4.D
5.C
1. graphics
2. identification
3. Indicating arrow
4. Reference line
5. The mathematical formula
1.×
2.√
3.×
4.√
5.√
1.B
2.C
3.B
4.A
5.D
1. answer ： Directional annotation text refers to the text that interprets the graphics in the drawing area through the annotation method of indicating arrows , It usually uses lines to connect the annotation text pointed by the description point and the arrow ; Non directional annotation text refers to the text that simply uses the annotation method of text to explain the graphics in the drawing area .
2. answer ： A coordinate axis is a set of lines or curves used to define a coordinate system ; The title is the name of the chart , It can quickly make readers understand what the chart is about ; The legend is a block diagram of each group of graphic identification methods listed , It can help users clarify the meaning of each group of graphics ; The grid starts from the scale of the coordinate axis 、 Several lines running through the drawing area , Used as a standard for estimating the values shown in the graph ; The reference line is a straight line marking the special value on the coordinate axis ; The reference area is an area marking a special range on the coordinate axis ; Note text is some notes and descriptions of graphics ; Tables are mainly used to emphasize data that are difficult to understand .
img_gray = cv2。cv2 cvtColor (img cv2.COLOR_BGR2GRAY)。錯誤:OpenCV (4.2.0) C: \ \ opencv-python項目
@solve img_gray = cv2.cvtColor
