Backend Development
Python Tutorial
Django Prophet: Building time series analysis applications from beginner to advanced
Django Prophet: Building time series analysis applications from beginner to advanced
Django Prophet: From entry to advanced, building a time series analysis application requires specific code examples
Time series analysis is an important statistical analysis method. It is used to study the changing trends, periodicity, seasonality and outliers of time series data. With the development of data science and machine learning, time series analysis has become increasingly important in areas such as forecasting and studying market trends and economic indicators.
Django Prophet is a Python-based time series analysis tool that combines statistical methods and machine learning technology to provide easy-to-use and highly customizable time series forecasting functions. This article will introduce how to use Django Prophet to build a time series analysis application and provide specific code examples.
- Installing Django Prophet
First, we need to install Django Prophet. Open a terminal or command prompt and run the following command:
pip install django-prophet
- Create a Django project
Next, we need to create a Django project. Run the following command in the command line:
django-admin startproject timeseries_app cd timeseries_app
- Create a Django application
Run the following command in the timeseries_app directory to create a Django application named timeseries:
python manage.py startapp timeseries
Then add 'timeseries' in the INSTALLED_APPS list in the settings.py file as follows:
INSTALLED_APPS = [
...
'timeseries',
...
]- Create a time series model
In Create a models.py file in the timeseries directory and define a model class named TimeSeries, as shown below:
from django.db import models
class TimeSeries(models.Model):
timestamp = models.DateTimeField()
value = models.FloatField()
def __str__(self):
return self.timestamp.strftime('%Y-%m-%d %H:%M:%S')This model class contains two fields: timestamp and value, which respectively represent the timestamp and the corresponding value.
- Data preparation
In Django projects, we usually use the Django management background to manage data. Write the following code in the admin.py file in the timeseries directory to be able to add and manage TimeSeries model data in the management background:
from django.contrib import admin from timeseries.models import TimeSeries admin.site.register(TimeSeries)
- Data upload
Start Django develops the server and logs in to the management background to upload time series data. Enter the following URL in the browser:
http://localhost:8000/admin
Then log in with the administrator account, click the "Time series" link, and click the "ADD" button in the upper right corner of the page to add a time series object.
- Time Series Analysis
Next, we will write code in the view function to analyze and predict the uploaded time series data. Open the timeseries/views.py file and add the following code:
from django.shortcuts import render
from timeseries.models import TimeSeries
def analyze_time_series(request):
time_series = TimeSeries.objects.all()
# 将时间序列数据整理为Prophet所需的格式
data = []
for ts in time_series:
data.append({'ds': ts.timestamp, 'y': ts.value})
# 使用Django Prophet进行时间序列分析和预测
from prophet import Prophet
model = Prophet()
model.fit(data)
future = model.make_future_dataframe(periods=365)
forecast = model.predict(future)
# 将分析结果传递到模板中进行展示
context = {
'time_series': time_series,
'forecast': forecast,
}
return render(request, 'analyze_time_series.html', context)In the above code, we first get all the time series data from the database and organize it into the format required by Django Prophet. Then create a Prophet instance to fit and predict the data. Finally, the analysis results are passed to the template.
- Template design
Create a template file named analyze_time_series.html to display the analysis results of time series. Write the following HTML code:
<!DOCTYPE html>
<html>
<head>
<title>Analyze Time Series</title>
</head>
<body>
<h1>Time Series Data</h1>
<ul>
{% for ts in time_series %}
<li>{{ ts }}</li>
{% empty %}
<li>No time series data available.</li>
{% endfor %}
</ul>
<h1>Forecast</h1>
<table>
<tr>
<th>Timestamp</th>
<th>Predicted Value</th>
<th>Lower Bound</th>
<th>Upper Bound</th>
</tr>
{% for row in forecast.iterrows %}
<tr>
<td>{{ row.ds }}</td>
<td>{{ row.yhat }}</td>
<td>{{ row.yhat_lower }}</td>
<td>{{ row.yhat_upper }}</td>
</tr>
{% endfor %}
</table>
</body>
</html>In the above template, we use the template engine provided by Django to display time series data and prediction results.
- URL configuration
The last step is to configure the URL routing so that we can access the analysis page through the browser. Add the following code to the urls.py file in the timeseries_app directory:
from django.contrib import admin
from django.urls import path
from timeseries.views import analyze_time_series
urlpatterns = [
path('admin/', admin.site.urls),
path('analyze/', analyze_time_series),
]- Run the application
You can now run the Django application and view the time series analysis results. Run the following command in the command line:
python manage.py runserver
Then enter the following URL in the browser:
http://localhost:8000/analyze
You will see the page of time series data and forecast results.
The above is all about using Django Prophet to build a time series analysis application from entry to advanced. Hopefully this article will provide you with practical code examples about time series analysis and Django Prophet, and help you further explore the world of time series analysis.
The above is the detailed content of Django Prophet: Building time series analysis applications from beginner to advanced. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
AI Hentai Generator
Generate AI Hentai for free.
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1386
52
How to check django version
Dec 01, 2023 pm 02:25 PM
Steps to check the Django version: 1. Open a terminal or command prompt window; 2. Make sure Django has been installed. If Django is not installed, you can use the package management tool to install it and enter the pip install django command; 3. After the installation is complete , you can use python -m django --version to check the Django version.
Quantile regression for time series probabilistic forecasting
May 07, 2024 pm 05:04 PM
Do not change the meaning of the original content, fine-tune the content, rewrite the content, and do not continue. "Quantile regression meets this need, providing prediction intervals with quantified chances. It is a statistical technique used to model the relationship between a predictor variable and a response variable, especially when the conditional distribution of the response variable is of interest When. Unlike traditional regression methods, quantile regression focuses on estimating the conditional magnitude of the response variable rather than the conditional mean. "Figure (A): Quantile regression Quantile regression is an estimate. A modeling method for the linear relationship between a set of regressors X and the quantiles of the explained variables Y. The existing regression model is actually a method to study the relationship between the explained variable and the explanatory variable. They focus on the relationship between explanatory variables and explained variables
Django vs. Flask: A comparative analysis of Python web frameworks
Jan 19, 2024 am 08:36 AM
Django and Flask are both leaders in Python Web frameworks, and they both have their own advantages and applicable scenarios. This article will conduct a comparative analysis of these two frameworks and provide specific code examples. Development Introduction Django is a full-featured Web framework, its main purpose is to quickly develop complex Web applications. Django provides many built-in functions, such as ORM (Object Relational Mapping), forms, authentication, management backend, etc. These features allow Django to handle large
Time Series Forecasting NLP Large Model New Work: Automatically Generate Implicit Prompts for Time Series Forecasting
Mar 18, 2024 am 09:20 AM
Today I would like to share a recent research work from the University of Connecticut that proposes a method to align time series data with large natural language processing (NLP) models on the latent space to improve the performance of time series forecasting. The key to this method is to use latent spatial hints (prompts) to enhance the accuracy of time series predictions. Paper title: S2IP-LLM: SemanticSpaceInformedPromptLearningwithLLMforTimeSeriesForecasting Download address: https://arxiv.org/pdf/2403.05798v1.pdf 1. Large problem background model
Django Framework Pros and Cons: Everything You Need to Know
Jan 19, 2024 am 09:09 AM
Django is a complete development framework that covers all aspects of the web development life cycle. Currently, this framework is one of the most popular web frameworks worldwide. If you plan to use Django to build your own web applications, then you need to understand the advantages and disadvantages of the Django framework. Here's everything you need to know, including specific code examples. Django advantages: 1. Rapid development-Djang can quickly develop web applications. It provides a rich library and internal
How to check django version
Nov 30, 2023 pm 03:08 PM
How to check the django version: 1. To check through the command line, enter the "python -m django --version" command in the terminal or command line window; 2. To check in the Python interactive environment, enter "import django print(django. get_version())" code; 3. Check the settings file of the Django project and find a list named INSTALLED_APPS, which contains installed application information.
What is the difference between django versions?
Nov 20, 2023 pm 04:33 PM
The differences are: 1. Django 1.x series: This is an early version of Django, including versions 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8 and 1.9. These versions mainly provide basic web development functions; 2. Django 2.x series: This is the mid-term version of Django, including 2.0, 2.1, 2.2 and other versions; 3. Django 3.x series: This is the latest version series of Django. Including versions 3.0, 3, etc.
How to upgrade Django version: steps and considerations
Jan 19, 2024 am 10:16 AM
How to upgrade Django version: steps and considerations, specific code examples required Introduction: Django is a powerful Python Web framework that is continuously updated and upgraded to provide better performance and more features. However, for developers using older versions of Django, upgrading Django may face some challenges. This article will introduce the steps and precautions on how to upgrade the Django version, and provide specific code examples. 1. Back up project files before upgrading Djan
