Need to open .rmd file and conduct data analysis using R
Budget ₹1500-12500 INR
Job Description:
The output must be in the .rmd file and the data analysis has to be done in the CSV file given
All requirements must be met. The first part is ""Project `owid_tb` on demographic columns, eliminate duplicate rows, so that you obtain one row per geographical entity. Call the resulting tibble `demog_tb` " "
No teams or companies please.
10 freelancere byder i gennemsnit ₹8700 timen for dette job
Need to open .rmd file and conduct data analysis using R Good evening , Hi I am a very experienced statistician, data scientist and academic writer. I have completed several PhD level thesis projects involving advance Flere
Top 1% in Freelancer.com Hi, Greetings! ✅checked your project details: ✅Completed Time: In project deadline We have worked on 850 + Projects. I have 6 + years of the experience in same kind of projects. I am a Flere
Hi, I have a lot of experience with the R language. I also have a master's degree in data science. My reviews prove to you that I worked well on R projects. Your project is a challenge for me. Let's discuss it. For th Flere
Dear employer, I noticed your project which can be achieved completely without a delay. Being a data engineer with core skills in python, pyspark, sql, hadoop, keras, pytorch, tensorflow, SPSS ,and R studio. Besides, I Flere
I had already work on a project which was on data analysis using r studio and there also i did same thing.
Hola: mi nombre en Heidi; soy Ingeniera de sistemas con énfasis en Telecomunicaciones. Soy muy buena en trabajos de redacción, transcripción y traducción, en inglés, español, portugués, frances. trabajo óptimamente en Flere
I am a PhD in Operations Research with 12 years of experience in developing and deploying R/ Econometrics solutions for various organisations and institutions. Currently, I am working as a Lead AI Scientist in a top ti Flere
I have done a project like this earlier also which not only included to remove duplicates but also remove null values. Splitting columns and a lot more functions.
