Generating Data and create visualizations of that data

1. Installing Matplotlib

python3 -m pip install --user matplotlib

2. Plotting a Simple Line Graph

import matplotlib.pyplot as plt

squares = [1, 4, 9, 16, 25]

fig, ax = plt.subplots()
ax.plot(squares)

plt.show()

3. Changing the Label Type and Line Thickness

mpl_squares.py

import matplotlib.pyplot as plt

squares = [1, 4, 9, 16, 25]

fig, ax = plt.subplots()

# the linewidth parameter controls the thickness of the line that plot() generates.

ax.plot(squares, linewidth=3)

# Set chart title and label axes.
# the set_title() method sets an overall title for the chart.
ax.set_title("Square Numbers", fontsize=24)

# the set_xlabel() and set_ylabel() methods allow you to set a title for each of the axes
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)


plt.show()

4. Correcting the Plot

import matplotlib.pyplot as plt

input_values = [1, 2, 3, 4, 5]
squares = [1, 4, 9, 16, 25]

fig, ax = plt.subplots()

ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)


plt.show()

5. Using Built-in Styles

to see the full list of available styles, run the fillowing lines in a terminal session:

To use any of these styles, add one line of code before calling subplots():

import matplotlib.pyplot as plt

input_values = [1, 2, 3, 4, 5]
squares = [1, 4, 9, 16, 25]

plt.style.use('seaborn-v0_8')

fig, ax = plt.subplots()

ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)


plt.show()

6.Plotting and Styling Individual Points with scatter()

import matplotlib.pyplot as plt

#input_values = [1, 2, 3, 4, 5]
#squares = [1, 4, 9, 16, 25]

plt.style.use('seaborn-v0_8')
fig, ax = plt.subplots()
ax.scatter(2, 4, s=200)


#ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)

plt.show()

7.Plotting a Series of Points with Scatter()

import matplotlib.pyplot as plt

x_values = [1, 2, 3, 4, 5]
y_squares = [1, 4, 9, 16, 25]

plt.style.use('seaborn-v0_8')
fig, ax = plt.subplots()
ax.scatter(x_values, y_squares, s=100)


#ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)

plt.show()

8.Calculating Data Automatically

import matplotlib.pyplot as plt

x_values = range(1, 1001)
y_squares = [x**2 for x in x_values]

plt.style.use('seaborn-v0_8')
fig, ax = plt.subplots()
ax.scatter(x_values, y_squares, s=10)


#ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)

# Set the range for each axis.
ax.axis([0, 1100, 0, 1_100_000])

plt.show()

9.Customizing Tick Labels

import matplotlib.pyplot as plt

x_values = range(1, 1001)
y_squares = [x**2 for x in x_values]

plt.style.use('seaborn-v0_8')
fig, ax = plt.subplots()
ax.scatter(x_values, y_squares, s=10)


#ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)

# Set the range for each axis.
ax.axis([0, 1100, 0, 1_100_000])
ax.ticklabel_format(style='plain')

plt.show()

10.Defining Custom Colors

import matplotlib.pyplot as plt

x_values = range(1, 1001)
y_values = [x**2 for x in x_values]

plt.style.use('seaborn-v0_8')
fig, ax = plt.subplots()
ax.scatter(x_values, y_values, s=10)


#ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)

# Set the range for each axis.
ax.axis([0, 1100, 0, 1_100_000])
ax.ticklabel_format(style='plain')

# defining custom colors
ax.scatter(x_values, y_values, color=(0, 0.8, 0), s=10)

plt.show()

11. Using a Colormap

12.Saving Your Plots Automatically

import matplotlib.pyplot as plt

x_values = range(1, 1001)
y_values = [x**2 for x in x_values]

plt.style.use('seaborn-v0_8')
fig, ax = plt.subplots()
ax.scatter(x_values, y_values,cmap=plt.cm.Blues, s=10)


#ax.plot(input_values, squares, linewidth=3)

# Set chart title and label axes.
ax.set_title("Square Numbers", fontsize=24)
ax.set_xlabel("Value", fontsize=14)
ax.set_ylabel("Square of Value", fontsize=14)

# Set size of tick labels
ax.tick_params(labelsize=14)

# Set the range for each axis.
ax.axis([0, 1100, 0, 1_100_000])
ax.ticklabel_format(style='plain')

# defining custom colors
ax.scatter(x_values, y_values, color=(0, 0.8, 0), s=10)

plt.show()
plt.savefig('square_plot.png', bbox_inches='tight')

上一篇:克魔助手工具详解、数据包抓取分析、使用教程


下一篇:2024-04-08