The following are some of the libraries of Python:
Pandas and numpy for data manipulation.
savReaderWriter for importing data that was originated from some statistical software.
Sklearn, scipy, statsmodels, for statistical tests, clustering, etc.
Some specific libraries when more usual libraries like sklearn don’t offer some features, e.g. kmodes.
TextBlob, NLTK, and language detection libraries (e.g. langid) for working with various textual data.
If you are a beginner and want to know more about the use of Python for Data Science then do refer the following video tutorial:
You can get a hands-on project by referring to Data Scientist which will teach you Data Science from scratch to advance.
And if you are more into videos then do check out the following video tutorial which will help you in mastering in the field of Data Science:
If you want a detailed explanation of Data Science then do check out Intellipaat’s Data Science tutorial which will help you in understanding DS.
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