Jupyter/Python with Binder
Budget: $50 – $100 USD
I need 6 to 10 Jupyter/Python notebooks created that will run on a Binder server from a repository on GitHub. The notebooks will load time series data from a web API and display analytic analysis in the notebooks and will use Pandas and Matplotlib libraries and possibly others if needed and agreed.
I have created a sample notebook that demonstrates the loading of data from the API and this notebook will be used as the basis of all new notebooks. The sample loads two time series into Pandas and creates daily and monthly frequency charts.
I want to create 10 new Python notebooks showing easy to advanced analytics based on this sample notebook. Please note that users can change the datasets used in the report (and other parameters including frequency) so the notebook comments must help the user to understand the range of the result - regardless of the datasets used.
All notebooks must be made to work on Binder from our GitHub repository ( as our demo notebook does)
These notebooks are to be an introduction to the API and to demonstrate how easy it is to use. This means that each section in the report must have a comment section that explains in English:
a). the purpose of the code in the section
b). if analytical, what the ideal output range is and what a result outside these ranges means (statistically).
c). A link to a wiki page showing details of the report
You MUST be familiar with Python 3.X and Jupyter AND Binder.
1). Please also supply a list of 6-10 report types that you feel we should create as training reports.
I suggest a list something like:
001 Load and chart 1 data series
002 Load and chart 2 data series in Pandas with daily and Monthly charts
003 Two data series with Moving Averages (MA), RSI and MACD
004 Seasonal Arima
005 Auto-correlation and Partial Auto-correlation
006 Detailed Time Series Analysis 1 series
007 Detailed Time Series Comparison/Analysis 2 series
008 Determine if multiple input series affect one series
009 Determine if multiple series affect each other
010 Machine Learning = Tensorflow ???
2). Please state your experience with Binder, Jupyter and why this project i
3). Please state your experience (if you have any) with "R" and Julia
So the project is to create 10 analytic Python/Jupyter notebooks with detailed comments in each notebook section and get them tested and running on the Binder server page we use.
I have created a sample notebook that demonstrates the loading of data from the API and this notebook will be used as the basis of all new notebooks. The sample loads two time series into Pandas and creates daily and monthly frequency charts.
I want to create 10 new Python notebooks showing easy to advanced analytics based on this sample notebook. Please note that users can change the datasets used in the report (and other parameters including frequency) so the notebook comments must help the user to understand the range of the result - regardless of the datasets used.
All notebooks must be made to work on Binder from our GitHub repository ( as our demo notebook does)
These notebooks are to be an introduction to the API and to demonstrate how easy it is to use. This means that each section in the report must have a comment section that explains in English:
a). the purpose of the code in the section
b). if analytical, what the ideal output range is and what a result outside these ranges means (statistically).
c). A link to a wiki page showing details of the report
You MUST be familiar with Python 3.X and Jupyter AND Binder.
1). Please also supply a list of 6-10 report types that you feel we should create as training reports.
I suggest a list something like:
001 Load and chart 1 data series
002 Load and chart 2 data series in Pandas with daily and Monthly charts
003 Two data series with Moving Averages (MA), RSI and MACD
004 Seasonal Arima
005 Auto-correlation and Partial Auto-correlation
006 Detailed Time Series Analysis 1 series
007 Detailed Time Series Comparison/Analysis 2 series
008 Determine if multiple input series affect one series
009 Determine if multiple series affect each other
010 Machine Learning = Tensorflow ???
2). Please state your experience with Binder, Jupyter and why this project i
3). Please state your experience (if you have any) with "R" and Julia
So the project is to create 10 analytic Python/Jupyter notebooks with detailed comments in each notebook section and get them tested and running on the Binder server page we use.