PYTHON

import matplotlib.pyplot as plt

from matplotlib import pyplot as plt

import matplotlib.pyplot as plt 

Import matplotlib python

import matplotlib.pyplot as plt
plt.plot([1,2,3,4])
plt.ylabel('some numbers')
plt.show()

import matplotlib.pyplot as plt

from matplotlib import pyplot as plt

import matplotlib.pyplot as plt1

print(dir(plt) == dir(plt1))
True

Use matplotlib in python

import matplotlib.pyplot as plt # Import the matplotlib module
from matplotlib import style # Optionally you dont need to use style
style.use('ggplot') # Just for style

x = [10, 20, 30, 40, 50] # Get points to plot on graph

plt.plot(x) # We want to plot x on our graph
plt.show()

matplotlib.pyplot

import matplotlib.pyplot as plt 
x=[0,10,20,30,60,90]
y=[-4.39,-4.69,-4.99,-5.30,-6.21,-7.13]
fig=plt.figure()
ax=fig.add_axes([0,0,1,1]) #grand
plt.plot(x,y)
plt.show()

matplotlib.pyplot

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0, 5, 0.1);
y = np.sin(x)
plt.plot(x, y)

matplotlib.pyplot

import matplotlib.pyplot as plt 
import numpy as np 

# Generate pseudo-random numbers:
np.random.seed(0) 

# Sampling interval:    
dt = 0.01 

# Sampling Frequency:
Fs = 1 / dt  # ex[;aom Fs] 

# Generate noise:
t = np.arange(0, 10, dt) 
res = np.random.randn(len(t)) 
r = np.exp(-t / 0.05) 

# Convolve 2 signals (functions):
conv_res = np.convolve(res, r)*dt
conv_res = conv_res[:len(t)] 
s = 0.5 * np.sin(1.5 * np.pi * t) + conv_res

# Create the plot: 
fig, (ax) = plt.subplots() 
ax.plot(t, s) 
# Function plots phase spectrum:
ax.phase_spectrum(s, Fs = Fs)

plt.title(“Phase Spectrum Plot”)
plt.show()

import matplotlib pyplot as plt

from matplotlib import pyplot as plt
df.plot()

how to import matplotlib in python

import matplotlib

matplotlib.pyplot

plt.plot([1, 2, 3, 4], [1, 4, 9, 16]) # plot x against y