IASC - bulkreadr: The Ultimate Tool for Reading Data in Bulk
| Date | 24 Nov 2023 |
| Time | 14:00 GMT+01:00 - 15:30 GMT+01:00 |
| Level of instruction | Beginner |
| Instructor |
Ezekiel Adebayo Ogundepo
|
| Registration fee | |
The bulkreadr package is designed to simplify and streamline the process of reading and processing large volumes of data in R. With a collection of functions tailored for bulk data operations, the package allows users to efficiently read multiple sheets from 'Microsoft Excel'/'Google Sheets' workbooks and multiple CSV files from a directory. It returns the data as organized data frames, making it convenient for further analysis and manipulation. Whether dealing with extensive data sets or batch processing tasks, 'bulkreadr' empowers users to effortlessly handle data in bulk, saving time and effort in data preparation workflows.
This webinar will take you through the workflow in bulkreadr package.
Instructors
About the instructor
Ezekiel Adebayo Ogundepo is a bright and innovative professional with a passion for using mathematics and statistics to solve real-world problems. He is a skilled data analyst with a strong track record of success. His research interests are aligned with the United Nations Sustainable Development Goals, and he is committed to using his skills to make a positive impact on the world.
Education:
- First-class degree in Statistics from the University of Ilorin, Nigeria, with FSB scholarship
- Master’s degree in mathematical sciences from the African Institute for Mathematical Sciences (AIMS), Rwanda, with a Mastercard scholarship
Experience:
- Data Analytics Manager at 54gene
- Conducted data analysis for a variety of organizations, including NGOs
- Contributions to various open-source packages within the statistical community
Skills:
- Proficient in R, Python, Spreadsheets, SPSS, and STATA
- Experienced in data science, big data, business intelligence, and research software engineering
- Created packages to automate data cleaning and statistical analysis
Research Interests:
- Using mathematics and computer science techniques to address SDG 3 (good health and well-being) and SDG 4 (quality education)
Notable Accomplishments:
- Promising young researcher selected for the 10th Heidelberg Laureate Forum (HLF) in Germany among 200 peers from 70 nations.
- Member of R Contributors in the United Kingdom (UK)
- Developed the CRAN package "forstringr" for string manipulation
- Developed the "bulkreadr" package for processing large-scale data sets
- Reduced human intervention in data cleaning and statistical analysis by 80% at 54gene.