How to write to json file using Dask?
This recipe helps you write to json file using Dask
Recipe Objective
How to write json file using Dask.
We can create many random sets of recorded data and store it to disk as many JSON files
Table of Contents
Step 1- Importing Libraries.
import dask.bag as db
import json
Step 2- We will read the files.
We will be processing the data by filtering out those required records of interest, by using mapping functions over the processed data.
b = db.read_text('data/*.json').map(json.loads)
b
```
dask.bag<loads, npartitions=10>
```
Step 3- computing the json file.
json_data = dd.read_json(self.input_s6, orient='columns').compute()
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
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.
Build a Review Classification Model using Gated Recurrent Unit
In this Machine Learning project, you will build a classification model in python to classify the reviews of an app on a scale of 1 to 5 using Gated Recurrent Unit.
Mastering A/B Testing: A Practical Guide for Production
In this A/B Testing for Machine Learning Project, you will gain hands-on experience in conducting A/B tests, analyzing statistical significance, and understanding the challenges of building a solution for A/B testing in a production environment.
Build Regression (Linear,Ridge,Lasso) Models in NumPy Python
In this machine learning regression project, you will learn to build NumPy Regression Models (Linear Regression, Ridge Regression, Lasso Regression) from Scratch.
Build a Logistic Regression Model in Python from Scratch
Regression project to implement logistic regression in python from scratch on streaming app data.
Deep Learning Project for Text Detection in Images using Python
CV2 Text Detection Code for Images using Python -Build a CRNN deep learning model to predict the single-line text in a given image.
Build Regression Models in Python for House Price Prediction
In this Machine Learning Regression project, you will build and evaluate various regression models in Python for house price prediction.
GCP MLOps Project to Deploy ARIMA Model using uWSGI Flask
Build an end-to-end MLOps Pipeline to deploy a Time Series ARIMA Model on GCP using uWSGI and Flask
Topic modelling using Kmeans clustering to group customer reviews
In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.
MLOps Project on GCP using Kubeflow for Model Deployment
MLOps using Kubeflow on GCP - Build and deploy a deep learning model on Google Cloud Platform using Kubeflow pipelines in Python