How to make Bullet charts in plotly?
MACHINE LEARNING RECIPES DATA CLEANING PYTHON DATA MUNGING PANDAS CHEATSHEET     ALL TAGS

How to make Bullet charts in plotly?

How to make Bullet charts in plotly?

This recipe helps you make Bullet charts in plotly

0

Recipe Objective

How to make Bullet charts in plotly.

Bullet charts It is used to replace dashboard guages and meters, combining both types of charts into simple bar charts with qualitative bars which are nothing but the steps, quantitative bar which are nothing but the bar and performance line which is threshold all into one simple layout. The steps typically are broken into several values, which are defined with an array. The bar represents the actual value that a particular variable reached, and the threshold usually indicate a goal point relative to the value achieved by the bar.

Step 1 - Import library

import plotly.graph_objects as go

Step 2 - Plot graph

fig = go.Figure(go.Indicator( mode = "number+gauge+delta", gauge = {'shape': "bullet"}, value = 320, delta = {'reference': 400}, domain = {'x': [0, 1], 'y': [0, 1]}, title = {'text': "Profit"})) fig.update_layout(height = 280) fig.show()

Relevant Projects

Time Series Forecasting with LSTM Neural Network Python
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

Predict Churn for a Telecom company using Logistic Regression
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.

Loan Eligibility Prediction in Python using H2O.ai
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.

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.

Data Science Project - Instacart Market Basket Analysis
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.

Human Activity Recognition Using Multiclass Classification in Python
In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.

Build a Similar Images Finder with Python, Keras, and Tensorflow
Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.

Ecommerce product reviews - Pairwise ranking and sentiment analysis
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

Forecast Inventory demand using historical sales data in R
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.

Deep Learning with Keras in R to Predict Customer Churn
In this deep learning project, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.