Getting data from API with tokens
Budget: $10 – $30 USD
1. Get the data from the following apis source: https://analytics.deacero.com/api/expuesta/sqlexp/api_key
Note: Valid api_keys are secured by mail. If you are interested in applying to the test, you can send an email to blabla@.com
I got the following information
API / TOKEN
Lineas Aereas / fed214f3-332d-522c-97ac-da395a066dba
Pasajeros 2016 / 3689da48-d557-5e5f-8347-006ced354939
Pasajeros 2017 / 2a323bb8-0a6d-5bd5-8366-90041c4f1c8c
Vuelos 2016 / 2743ebad-f1e2-5eff-8c4d-f8c5191d1775
Vuelos 2017 / a6960833-d5a3-56dc-b125-da9e4e1fce69
2. There is a requirement to analyze passenger and travel data sources. As you can see, the lists have been running for years. In this first part of the challenge you are asked to:
- Join each dataset into a single list.
- Explain the process performed.
- In case of detecting anomalies generated by this union, you must indicate the type of anomaly that occurs, how it can be resolved and resolve it if possible.
3. From what was obtained previously, it is necessary to relate the lists of flights and passengers, which allow analyzing the profile of the passenger for each flight made. In such a way that consolidated data can be obtained. In this part you must:
- Explain the process used to match passengers and flights.
- What type of relationship and why?
The exercises must be done in Python, in addition to a document where the questions are answered and the results of the transformations are shown. In case of working with jupyter notebooks it can be exported in HTML.
Note: Valid api_keys are secured by mail. If you are interested in applying to the test, you can send an email to blabla@.com
I got the following information
API / TOKEN
Lineas Aereas / fed214f3-332d-522c-97ac-da395a066dba
Pasajeros 2016 / 3689da48-d557-5e5f-8347-006ced354939
Pasajeros 2017 / 2a323bb8-0a6d-5bd5-8366-90041c4f1c8c
Vuelos 2016 / 2743ebad-f1e2-5eff-8c4d-f8c5191d1775
Vuelos 2017 / a6960833-d5a3-56dc-b125-da9e4e1fce69
2. There is a requirement to analyze passenger and travel data sources. As you can see, the lists have been running for years. In this first part of the challenge you are asked to:
- Join each dataset into a single list.
- Explain the process performed.
- In case of detecting anomalies generated by this union, you must indicate the type of anomaly that occurs, how it can be resolved and resolve it if possible.
3. From what was obtained previously, it is necessary to relate the lists of flights and passengers, which allow analyzing the profile of the passenger for each flight made. In such a way that consolidated data can be obtained. In this part you must:
- Explain the process used to match passengers and flights.
- What type of relationship and why?
The exercises must be done in Python, in addition to a document where the questions are answered and the results of the transformations are shown. In case of working with jupyter notebooks it can be exported in HTML.