A Data Science Central Community

It is common to use R language to group and summarize data of files. Sometimes we may find ourselves processing comparatively big files which have smaller computed result and bigger source data. We cannot load them wholly to the memory when we need to compute them. The only solutions could be batch importing and computing as well as result merging. We’ll use an example in the following to illustrate the way of R language to group and summarize data from big text files.

Here is a file,…

ContinueAdded by Jessica May on August 24, 2014 at 8:54pm — 2 Comments

- How to Compute Moving Average in R Language and Python
- A use case to read and analyze Excel data in Java
- Data alignment join in Java for easier text analytics
- Calculation cases of Link Relative Ratio and Year-on-year Comparison in data analytics
- Code Examples of cross database relational computing in Java
- A Method of Grouping and Summarizing Data of Big Text Files in R Language
- Some Cases illustrating drawbacks of SQL in data computing and analytics

- How to Compute Moving Average in R Language and Python
- A Method of Grouping and Summarizing Data of Big Text Files in R Language
- Some Cases illustrating drawbacks of SQL in data computing and analytics
- How to Process Text Files in the Data Analytics
- Code Examples of cross database relational computing in Java
- Data alignment join in Java for easier text analytics
- What difficulties SQL have in OLAP

- data (7)
- analytics (6)
- table (4)
- R (3)
- SQL (3)
- file (3)
- join (3)
- language (3)
- query (3)
- text (3)
- Java (2)
- Python (2)
- cross (2)
- esProc (2)
- grouping (2)
- programming (2)
- sequence (2)
- set (2)
- Excel (1)
- HDFS (1)
- OLAP (1)
- access (1)
- alignment (1)
- analyze (1)
- comparison (1)
- cursor (1)
- database (1)
- filtering (1)
- frame (1)
- in (1)
- java (1)
- left (1)
- link (1)
- object (1)
- on (1)
- operation (1)
- procedure (1)
- process (1)
- processs (1)
- ratio (1)
- read (1)
- reference (1)
- relational (1)
- relative (1)
- row (1)
- sorting (1)
- stored (1)
- summarizing (1)
- year (1)

© 2021 TechTarget, Inc. Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

- Book: Applied Stochastic Processes
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- How to Automatically Determine the Number of Clusters in your Data
- New Machine Learning Cheat Sheet | Old one
- Confidence Intervals Without Pain - With Resampling
- Advanced Machine Learning with Basic Excel
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Fast Combinatorial Feature Selection

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives:** 2008-2014 |
2015-2016 |
2017-2019 |
Book 1 |
Book 2 |
More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions