The correct answer is: A. pandaSDMX
pandaSDMX is a Python package that makes it easy to work with data from the Statistical Data and Metadata Exchange (SDMX). It provides a high-level API for reading, writing, and manipulating SDMX data, as well as a number of tools for working with SDMX metadata.
pandaSDMX uses pandas to represent SDMX data, which makes it easy to work with the data in a familiar way. pandas is a Python package that provides high-performance, easy-to-use data structures and data analysis tools for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.
When you read SDMX data with pandaSDMX, the data is automatically converted into a pandas DataFrame. A DataFrame is a two-dimensional data structure that can be used to store data in a table format. It is similar to a spreadsheet, but it is more powerful and flexible.
You can use pandas to manipulate and analyze SDMX data in a variety of ways. For example, you can use pandas to filter data, calculate statistics, and create charts and graphs.
pandaSDMX also provides a number of tools for working with SDMX metadata. Metadata is information about data, such as the data’s source, format, and structure. pandaSDMX can be used to read, write, and manipulate SDMX metadata.
Overall, pandaSDMX is a powerful and flexible tool for working with SDMX data. It provides a high-level API for reading, writing, and manipulating SDMX data, as well as a number of tools for working with SDMX metadata.
The other options are incorrect because they do not make use of pandas or return data in a series or DataFrame.
- freedapi is a Python package that provides a high-level API for working with the Freebase knowledge base. It does not make use of pandas or return data in a series or DataFrame.
- OutPy is a Python package that provides a high-level API for working with the OpenAPI specification. It does not make use of pandas or return data in a series or DataFrame.