Hi! My name is Ezekiel Adebayo Ogundepo and I am a certified RStudio instructor 😄. You can find more about me on my website.

• 🔭 I’m an innovator and inventor.

• 😄 I love wrangling data, building tools, and automating processes.

• 🌱 I work with 54gene as a senior data specialist. I also work with the Virus Outbreak Data Network (VODAN Africa and Asia) as a Data Steward.

• 👯 I’m open to collaborating on Projects and StartUps.

• 💬 Talk to me about R and Python for Everyone, Data Science, Business Analytics, Data Engineering, Automation, Research Software Engineering (RSE), and Open Source.

• bulkreadr package:

bulkreadr is an R package that simplifies and streamlines the process of reading and processing large volumes of data. It allows users to efficiently read multiple sheets from Microsoft Excel/Google Sheets workbooks and multiple CSV files from a directory.

• forstringr package:

Forstringr enables complex string manipulation in R, especially for those more familiar with LEFT(), RIGHT(), and MID() function in Microsoft Excel. The package combines the power of stringr with other manipulation packages such as dplyr and tidyr.

• Mastering Shiny Solutions Book:

A book that offers solutions to the exercises from Hadley Wickham’s book Mastering Shiny.

• ralger R package:

The goal of ralger is to facilitate web scraping in R. The user has the ability to extract a vector with scrap(), a tidy data frame using tidy_scrap(), a table with table_scrap() and web links with weblink_scrap().

• Big Book of R:

The biggest collection of R books.

• Co-Editor:

Beginners’ Artificial Intelligence & Python Programming Book for Primary and Junior Secondary.

• COVID-19, healthcare facilities, and economic related data in Nigeria, Mendeley Data. DOI: http://dx.doi.org/10.17632/8h5rtbbx7m.2

• Location-based Tweets in Africa on COVID-19 Pandemic, Mendeley Data. DOI: http://dx.doi.org/10.17632/c8x5tpvzmk.1

• Ogundepo, E. A., & Yahya, W. B. (2023). Performance analysis of supervised classification models on heart disease prediction. Innovations in Systems and Software Engineering, 1-16. doi: https://doi.org/10.1007/s11334-022-00524-9

• OGBUJU E., BANJO O., OGUNDEPO E.A., FOLORUNSO S., OLADIPO F. (2022). A DATASET OF LOCATION-BASED TWEETS IN AFRICA ON COVID-19 OUTBREAK. The Journal of Information Systems & Operations Management, 16(1), pp. 200-208.

• Folorunso, S.O., Ogundepo, E.A., Awotunde, J.B., Ayo, F.E., Banjo, O.O., Taiwo, A.I. (2022). A Multi-Step Predictive Model for COVID-19 Cases in Nigeria Using Machine Learning. In: Hassan, S.A., Mohamed, A.W., Alnowibet, K.A. (eds) Decision Sciences for COVID-19. International Series in Operations Research & Management Science, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-030-87019-5_7

• Folorunso, S. O., Awotunde, J. B., Banjo, O. O., Ogundepo, E. A., & Adeboye, N. O. (2022). Comparison of Active COVID-19 Cases per Population Using Time-Series Models. International Journal of E-Health and Medical Communications (IJEHMC), 13(2), 1-21. http://doi.org/10.4018/IJEHMC.20220701.oa6

• Folorunso, S., Ogundepo, E., Basajja, M., Awotunde, J., Kawu, A., Oladipo, F., & Abdullahi, I. (2022). FAIR machine learning model pipeline implementation of COVID-19 data. Data Intelligence, 1-32.

• Oladipo, Francisca, Sakinat Folorunso, Ezekiel Ogundepo, Obinna Osigwe, and Akinyinka Akindele. "Curriculum development for FAIR data stewardship." Data Intelligence (2022): 1-42.

• Ghardallou, M., Wirtz, M., Folorunso, S., Touati, Z., Ogundepo, E., Smits, K., ... & van Reisen, M. (2022). Expanding Non-Patient COVID-19 Data: Towards the FAIRification of Migrants' Data in Tunisia, Libya and Niger. Data Intelligence, 1-24.

• Adekanmbi, Olubayo; Oyewusi, Wuraola Fisayo; Ogundepo, Ezekiel Adebayo (2020). Real-Time Crowdsourcing of Health Data in a Low-Income Country: A Case Study of Human Data Supply on Malaria First-Line Treatment Policy Tracking in Nigeria. Proceedings of the Crowd Science Workshop: Remoteness, Fairness, and Mechanisms as Challenges of Data Supply by Humans for Automation co-located with 34th Conference on Neural Information Processing Systems (NeurIPS), Vancouver, BC, Canada (Online), http://ceur-ws.org/Vol-2736/paper3.pdf

• Ogundepo, E., Folorunso, S., Adekanmbi, O., Akinsande, O., Banjo, O., Ogbuju, E., Oladipo, F., Abimbola, O., Oseghale, E., & Babajide, O. (2020). An Exploratory Assessment of a Multidimensional Healthcare and Economic Data on COVID-19 in Nigeria. Data in brief, 106424. doi: https://doi.org/10.1016/j.dib.2020.106424

• Ogundepo, E. A. & Fokoué, E. (2020). An empirical demonstration of the no free lunch theorem. Mathematics for Applications, 8(2), 173–188. doi: https://doi.org/10.13164/ma.2019.11

• Akande, O.K., Olagunju, R.E., Aremu, S.C., & Ogundepo, E.A. (2018). Exploring Factors Influencing Project Management Success in Public Building Projects in Nigeria. YBL Journal of Built Environment, 6(1), 47-62. doi: https://doi.org/10.2478/jbe-2018-0004