[amp_mcq option1=”Quandl” option2=”PyDatastream” option3=”PyData” option4=”None of the mentioned” correct=”option1″]<\/p>\n
The correct answer is: A. Quandl<\/strong><\/p>\n Quandl is a financial data marketplace that provides historical and real-time financial data for over 100,000 datasets. The Quandl API for Python wraps the Quandl REST API to return Pandas DataFrames with time series indexes. This makes it easy to access and analyze financial data in Python.<\/p>\n PyDatastream is a Python library that provides access to financial data from a variety of sources, including Quandl. PyDatastream is a higher-level API than Quandl, and it provides more features, such as the ability to create custom queries and to store data in a database.<\/p>\n PyData is a community of Python developers who are interested in data science. PyData hosts conferences and meetups, and it provides resources for learning about Python for data science.<\/p>\n None of the mentioned is not the correct answer.<\/p>\n","protected":false},"excerpt":{"rendered":" [amp_mcq option1=”Quandl” option2=”PyDatastream” option3=”PyData” option4=”None of the mentioned” correct=”option1″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[737],"tags":[],"class_list":["post-48588","post","type-post","status-publish","format-standard","hentry","category-data-analysis-with-python","no-featured-image-padding"],"yoast_head":"\n