Data research and entry for climatological and geographical data
$30-250 USD
Pago na entrega
Hello,
I have a data search and collection order to place. What I need is an importable and structured .xls file with climatological and geographical data.
The geographical data will be broken down to city level. The first step is to collect the information, based on the amount of data, up to one level above:
Continents -> Countries -> Climatological regions -> Federal states / regions / provinces
The following average values per month (January, February, March, etc...) are required for each entry and each level of this list:
- Temperature Maximum (in Celsius)
- Temperature Minimum (in Celsius)
- Water temperature (in Celsius)
- Number of rainy days
- Number of hours of sunshine
- Best travel time from month X to month Y
It is important that all entries contain complete and accurate data sets. The names and designations must correspond to the German spelling.
The result is an importable .xls file which can be used to create diagrams / statistics as well as automatically generated subpages of a website.
Before awarding the contract, I need reference work, a flat-rate offer or an hourly wage (each with a time estimate of the scope of the order) and a time frame for implementation from the interested persons.
In addition, a file with a few data records for test import and estimation of the structuring of the data is required before placing the order.
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ID do Projeto: #18893102
Sobre o projeto
9 freelancers estão ofertando em média $140 nesse trabalho
Hi there, I can data search and collection order to place. If you have questions or doubts about anything, please feel free to ask me. Sincerely, Mir
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Hello. I would really like to work with you on this if possible. First, I would like to make you an offer and some background. My name is Sara and I am an experienced Data Entry Specialist and very good at Excel, Wo Mais
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A Statistician by profession, Lecturer and Data Science for more than 8 years, with extensive experience in research and statistics, forecasting, building, optimizing and econometric modeling using machine learning tec Mais