Python client - Add dimensions labels to dataframes

• As a Python client user
• I want to see dimensions labels and dimensions values labels in the dataframe
• in order to create nice charts (for example).

Acceptance criteria

• The downloaded dataframe MUST have a column for each dimension which header is the dimension label, and the body cells are the dimensions values labels
• The tutorial notebook MUST be updated

Tasks

• After the commit corresponding to the feature addition, update the link to Binder in the README to use the previous commit SHA-1 (because it is not possible for now with Binder to specify master branch, see https://github.com/jupyterhub/binderhub/issues/675) Now Binder supports any Git repo!

Analysis

As an example, I'll take the first request of tutorial notebook

Corresponding series in DBnomics UI is here: https://db.nomics.world/AMECO/ZUTN?dimensions=%7B%22freq%22%3A%5B%22a%22%5D%2C%22geo%22%3A%5B%22ea19%22%5D%7D&q=EA19.1.0.0.0.ZUTN

Before:

@frequency	provider_code	dataset_code	dataset_name	series_code	series_name	original_period	period	original_value	value	freq	geo	unit
annual	AMECO	ZUTN	Unemployment rate: total :- Member States: def...	EA19.1.0.0.0.ZUTN	Annually – (Percentage of active population) –...	1960	1960-01-01	NA	NaN	a	ea19	percentage-of-active-population

After

We'll keep all those columns as it and add to the end:

Frequency	Unit	Country
Annualy	Percentage of active population	Euro area