The correct answer is D. All of the mentioned.
Pandas represents timestamps in microsecond resolution. This means that the timestamps in a Pandas DataFrame are stored with a precision of up to 1 microsecond. This is useful for applications that require high-precision timestamps, such as financial trading or scientific research.
Pandas is 100% thread safe. This means that multiple threads can safely access and modify a Pandas DataFrame at the same time without causing any data corruption. This is important for applications that need to process large amounts of data in parallel.
For Series and DataFrame objects, var normalizes by N-1 to produce unbiased estimates. This means that the variance of a Series or DataFrame is calculated by dividing the sum of the squared differences from the mean by N-1, where N is the number of observations. This is the correct way to calculate the variance of a sample, and it produces unbiased estimates.
In conclusion, all of the statements in the question are correct. Pandas represents timestamps in microsecond resolution, Pandas is 100% thread safe, and for Series and DataFrame objects, var normalizes by N-1 to produce unbiased estimates.