Using Matplotlib simple Drawing

each component name in a picture

Draw multiple pictures

Import NumPy as NP
import Matplotlib.pyplot as Plt
plt.style.use ("Ggplot") # display style
def f (t):
    return Np.exp (-T) *np.cos (2*np.pi*t)
t1 = Np.arrange (0.0,5.0,0.1)
t2 = Np.arrange (0.0,5.0,0.02)

plt.figure (1) # Create a figure
Plt.subplot (211) # Create a 2-row 1-column diagram on the figure, and currently select 1th Figure
# Draw (t1,f (T1)) and (T2,f (T2)), one in a curved form, one in the form of a point.
Plt.plot (t1,f (T1), ' Bo ', T2,f (T2), ' K ') 

Plt.subplot (212) # Continue to select the second figure in the 2 row 1 column diagram
plt.plot (t2,np.cos NP.PI*T2), ' r--') # on the second figure shows the figure plt.show of Cos
()

The results are shown in the following illustration:

Set Axis information

Import NumPy as NP
import Matplotlib.pyplot as Plt
plt.style.use ("Ggplot")
np.random.seed (19680801)
Mu,sigma = 100,15
x = MU+SIGMA*NP.RANDOM.RANDN (10000) #生成10000服从正态分布的数
# Displays a histogram, divided into 50 groups,
n,bins,patches = Plt.hist (x,50,normed =1, Facecolor = ' g ', alpha=0.75)
# Set property information for x, y axes, information, font size, and color
plt.xlabel (' Smarts ', FontSize =14, color = ' red ')
Plt.ylabel ("probability", FontSize =, color = ' blue ')
plt.title ("Histogram of IQ" # Show Graph title
# Displays Latex formula at x = 60,y = 0.025
plt.text (. 025, R ' $\mu=100,\ \sigma=15$ ') # 
Plt.axis ([ 40,160,0,0.03]) # Set axis range, x range 40~160,y range 0~0.03
Plt.grid (True) # Show Squares
plt.tight_layout () # Eliminate the blank space around the picture
# Set the size of the scale
plt.xticks (fontsize =)
plt.yticks (fontsize =)

plt.show ()

The results are shown in the following illustration:


Text for more property information.
Text Information display mathematical formula

Set Display style

Import NumPy as NP
import Matplotlib.pyplot as Plt
plt.style.use (' Ggplot ') # Set the style of the R language Pack
# View available display styles, The style is as follows: You can try different styles yourself
print (plt.style.available) ""
[' Seaborn-darkgrid ', ' Seaborn-dark-palette ', ' Seaborn-deep ', ' seaborn-colorblind ', ' seaborn-bright ', ' Seaborn-whitegrid ', ' seaborn-poster ', ' seaborn-talk ', ' Seaborn-ticks ', ' Seaborn-pastel ', ' dark_background ', ' ggplot ', ' Seaborn-dark ', ' bmh ', ' seaborn-white ', ' grayscale ', ' Classic ', ' seaborn-muted ', ' seaborn-paper ', ' seaborn-notebook ', ' FiveThirtyEight ' '

set legend

Import Matplotlib.pyplot as Plt
import numpy as NP
plt.style.use ("FiveThirtyEight") # set style
x = Np.linspace ( 0,2,100)
Plt.plot (x, X, label= ' linear ') # label to display legend
plt.plot (x, x**2, label= ' quadratic ') # label to display legend
Plt.plot (x, x**3, label= ' Cubic ') # label is used to display legend
Plt.xlabel (' x label ') Plt.ylabel (
' y label ') plt.title (
" Simple plot ")
plt.legend () # Displays legend
plt.tight_layout () # Compact Layout
# Sets the display position of the legend and the font size
plt.legend (loc = ' Upper Right ', FontSize =)
plt.show ()

The results are shown in the following illustration:

display Chinese characters correctly

Import Matplotlib.pyplot as Plt
plt.rcparams[' font.sans-serif ']=[' Simhei '] #用来正常显示中文标签