Merge 3 csv files, show table and create charts in Shiny in R

$10-30 USD

Terminado

Publicado

hace más de 5 años

$10-30 USD

Pagado a la entrega

I have 3 csv files. Characteristics of the files: - there have varying number of rows and columns - columns names are not unique and differ in each files Steps required: 1. Merge files dynamically, and in a specific order. There must not be duplicates in rows and no duplicates in columns in the merge. Once all files are merged, create this as a dataframe. 2. Using this dataframe, create functions for separate charts, which I will provide details for once you show interest. 3. Call these created functions when creating shiny app

R Programming Language

ID del proyecto: 18079334

Información sobre el proyecto

3 propuestas

Proyecto remoto

Activo hace 6 años

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@FedericoRiva

Hello! I have experience using R and some experience using Shiny... If you want message me and tell me a little more about your job... we can even work out some samples if you want.... Good luck!

$35 USD en 2 días

5,0

(11 comentarios)

3,7

3 freelancers están ofertando un promedio de $52 USD por este trabajo

@shivampanchal

I have a good hands on working with Advanced R and Python and BI tools and technologies, AI, Big Data. I have quite a good knowledge of DL/ML Algorithm , have also developed Dashboards and Web Applications using flask/django. My area of expertise is building financial models (Stock Markets) , Image Processing and building models for food, healthcare and telecom sector, Classification/Prediction/Clustering, NLP and Chatbots. Specifically, I have worked for log on stock data and model building for the same. I understand the project requirement and will deliver the desired product within the time specified. I would like to hear from you. Thanks Shivam

$100 USD en 1 día

4,8

(57 comentarios)

6,4

@caffery07

Hi, I am interested in this project. I have experience in this. Been working on data analysis for like 2 years. So i can finish it ASAP. Thanks in advance.

$20 USD en 2 días