How to make a graph in Matplotlib with x label?
This recipe helps you make a graph in Matplotlib with x label
Recipe Objective
Make a graph with x label, y label and title mentioned in it using Matplotlib.
Step 1- Importing Libraries.
import matplotlib.pyplot as plt
import numpy as np
Step 2- Creating arrays.
x=np.array([2,5,6,4,7])
y=np.array([3,4,1,6,8])
Step 3- Plotting the graph with labels and title
plt.scatter(x,y)
plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.title('visualization of two arrays')
What Users are saying..
Jingwei Li
Graduate Research assistance at Stony Brook University
ProjectPro is an awesome platform that helps me learn much hands-on industrial experience with a step-by-step walkthrough of projects. There are two primary paths to learn: Data Science and Big Data.... Read More
Relevant Projects
Machine Learning Projects
Data Science Projects
Python Projects for Data Science
Data Science Projects in R
Machine Learning Projects for Beginners
Deep Learning Projects
Neural Network Projects
Tensorflow Projects
NLP Projects
Kaggle Projects
IoT Projects
Big Data Projects
Hadoop Real-Time Projects Examples
Spark Projects
Data Analytics Projects for Students
You might also like
Data Science Tutorial
Data Scientist Salary
How to Become a Data Scientist
Data Analyst vs Data Scientist
Data Scientist Resume
Data Science Projects for Beginners
Machine Learning Engineer
Machine Learning Projects for Beginners
Datasets
Pandas Dataframe
Machine Learning Algorithms
Regression Analysis
MNIST Dataset
Data Science Interview Questions
Python Data Science Interview Questions
Spark Interview Questions
Hadoop Interview Questions
Data Analyst Interview Questions
Machine Learning Interview Questions
AWS vs Azure
Hadoop Architecture
Spark Architecture
Relevant Projects
House Price Prediction Project using Machine Learning in Python
Use the Zillow Zestimate Dataset to build a machine learning model for house price prediction.
FEAST Feature Store Example for Scaling Machine Learning
FEAST Feature Store Example- Learn to use FEAST Feature Store to manage, store, and discover features for customer churn prediction machine learning project.
NLP and Deep Learning For Fake News Classification in Python
In this project you will use Python to implement various machine learning methods( RNN, LSTM, GRU) for fake news classification.
Build a CNN Model with PyTorch for Image Classification
In this deep learning project, you will learn how to build an Image Classification Model using PyTorch CNN
Recommender System Machine Learning Project for Beginners-2
Recommender System Machine Learning Project for Beginners Part 2- Learn how to build a recommender system for market basket analysis using association rule mining.
Multilabel Classification Project for Predicting Shipment Modes
Multilabel Classification Project to build a machine learning model that predicts the appropriate mode of transport for each shipment, using a transport dataset with 2000 unique products. The project explores and compares four different approaches to multilabel classification, including naive independent models, classifier chains, natively multilabel models, and multilabel to multiclass approaches.
Linear Regression Model Project in Python for Beginners Part 2
Machine Learning Linear Regression Project for Beginners in Python to Build a Multiple Linear Regression Model on Soccer Player Dataset.
Learn Hyperparameter Tuning for Neural Networks with PyTorch
In this Deep Learning Project, you will learn how to optimally tune the hyperparameters (learning rate, epochs, dropout, early stopping) of a neural network model in PyTorch to improve model performance.
NLP Project for Beginners on Text Processing and Classification
This Project Explains the Basic Text Preprocessing and How to Build a Classification Model in Python
Model Deployment on GCP using Streamlit for Resume Parsing
Perform model deployment on GCP for resume parsing model using Streamlit App.