Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Testing of various Data Frame operations and manipulations is now enhanced by a rich set of fixtures designed for various use cases.
This is because this fixture is very vital in testing of functions that involve time-based indexing and date manipulation. It is a random float generator with the values of which are indexed by the business dates thus making it possible to simulate the real-time data processing.
This fixture has a column of strings together with numerical values in it, to serve the purpose of a data type with string and numeric column. The Data Frame has a unique string index and an additional column which contains a constant string “bar” to test string operations and check the stability.
This setup allows to test how various float precision and their conversions are being dealt with in Data Frames for proper calculations and types management.
This fixture is quite essential when testing operations that involve different integer types and integer-related calculations.
It is especially helpful in testing time zone conversion and handling of missing data so that the time-based data gets processed properly in all the time zones.
[ ] closes #xxxx (Replace xxxx with the GitHub issue number)
Testing of various Data Frame operations and manipulations is now enhanced by a rich set of fixtures designed for various use cases.
This is because this fixture is very vital in testing of functions that involve time-based indexing and date manipulation. It is a random float generator with the values of which are indexed by the business dates thus making it possible to simulate the real-time data processing.
This fixture has a column of strings together with numerical values in it, to serve the purpose of a data type with string and numeric column. The Data Frame has a unique string index and an additional column which contains a constant string “bar” to test string operations and check the stability. This setup allows to test how various float precision and their conversions are being dealt with in Data Frames for proper calculations and types management.
This fixture is quite essential when testing operations that involve different integer types and integer-related calculations.
It is especially helpful in testing time zone conversion and handling of missing data so that the time-based data gets processed properly in all the time zones.
doc/source/whatsnew/vX.X.X.rst
file if fixing a bug or adding a new feature.