Data visualization and Plotting is an essential skill that allows us to spot trends in data and outliers. With the help of plots, we can easily discover and present useful information about the data. In this article, we are going to plot a sine and cosine graph using Matplotlib in Python. Matplotlib is a Python library for data visualization and plotting, if you don’t have Matplotlib installed on your system, please install it before Plotting Sine and Cosine Graph using Matplotlib. One can install Matplotlib using the below command on the terminal or Jupyter notebook.
pip install matplotlib
Plotting Sine Graph using Matplotlib in Python
Now let’s plot the sine curve using the sine function that is inbuilt into the NumPy library and plot it using Matplotlib.
Step 1: Import the necessary library for plotting.
Python3
#Importing required libraryimport numpy as npimport matplotlib.pyplot as plt |
Step 2: Create a list or load your own data for Plotting Sine Graph.
Python3
# Creating x axis with range and y axis with Sine# Function for Plotting Sine Graphx = np.arange(0, 5*np.pi, 0.1)y = np.sin(x) |
Step 3: Plotting Sine Graph with the created list or load data.
Python3
# Plotting Sine Graphplt.plot(x, y, color='green')plt.show() |
Output:
Sine Curve using Matplotlib
Plotting Cosine Graph using Matplotlib in Python
Now let’s plot the cosine curve using the cosine function that is inbuilt into the NumPy library and plot it using Matplotlib.
Python3
# Importing required libraryimport numpy as npimport matplotlib.pyplot as plt# Creating x axis with range and y axis with Sine# Function for Plotting Cosine Graphx = np.arange(0, 5*np.pi, 0.1)y = np.cos(x)# Plotting coine Graphplt.plot(x, y, color='green')plt.show() |
Output:
Cosine Curve using Matplotlib
Plotting Both Combined Sine and Cosine Graph
From the above two curves, one must think that both of them seem pretty similar. Let’s look at both of these curves on the same graph then we will be able to detect the difference between the graph of the two curves.
Python3
# Importing required libraryimport numpy as npimport matplotlib.pyplot as plt# Creating x axis with range and y axis # Function for Plotting Sine and Cosine Graphx = np.arange(0, 5*np.pi, 0.1)y1 = np.sin(x)y2 = np.cos(x)# Plotting Sine Graphplt.plot(x, y1, color='green')plt.plot(x, y2, color='darkblue')plt.show() |
Output:
Sine and Cosine Curve using Matplotlib
Plotting different waveforms using Numpy and Matplotlib:
The sine wave, square wave, triangle wave, and sawtooth wave are four different waveforms that are created and displayed. These waveforms are frequently utilized in signal processing, electronics, and several scientific and technical applications.
Code:
Python3
import numpy as npimport matplotlib.pyplot as plt# Define signal parametersT = 1 # period (seconds)fs = 1000 # sampling frequency (Hz)time = np.linspace(0, T, T * fs, endpoint=False)# Generate sine wavefrequency_sine = 5 # frequency (Hz)sine_wave = np.sin(2 * np.pi * frequency_sine * time)# Generate square wavefrequency_square = 2 # frequency (Hz)duty_cycle = 0.01 # percentage of the period where the signal is highsquare_wave = np.where( np.mod(np.floor(2 * duty_cycle * fs * time), 2) == 0, 1, -1)# Generate triangle wavefrequency_triangle = 1 # frequency (Hz)triangle_wave = 2 * np.abs((10 * frequency_triangle * time) % 2 - 1) - 1# Generate sawtooth wavefrequency_sawtooth = 10 # frequency (Hz)sawtooth_wave = 2 * (frequency_sawtooth * time - np.floor(frequency_sawtooth * time + 0.5))# Plot the wavesfig, axs = plt.subplots(4, 1, sharex=True, figsize=(8, 8))axs[0].plot(time, sine_wave)axs[0].set_title('Sine Wave')axs[1].plot(time, square_wave)axs[1].set_title('Square Wave')axs[2].plot(time, triangle_wave)axs[2].set_title('Triangle Wave')axs[3].plot(time, sawtooth_wave)axs[3].set_title('Sawtooth Wave')plt.xlabel('Time (s)')plt.show() |
Output:
