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❯ 3.4 Statistics
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EXPECTED COMPLETION TIME
❲▹❳ Video 4m 7s
☷ Interactive readings 5m
Computing Aggregate Statistics
Here, we generate some normally distributed random data and compute some aggregate statistics:
Computing Statistics on Rows & Columns
Functions like mean and sum take an optional axis argument that computes the statistic over the given axis, resulting in an array with one fewer dimension.
Performing Non-Aggregate Statistics
Other methods like cumsum and cumprod do not aggregate, instead producing an array of the intermediate results:
Descriptive and Summary Statistics
count Number of non-NA values
decsribe Compute set of summary statistics for Series or each DataFrame column
min, max Minimum and maximum
cumsum Cumulative sum of elements starting from 0
cumprod Cumulative product of elements starting from 1
Extras
Calculating all Statistics using describe
Instead of specifying each statistics, the method describe is useful if you want to get all the essential statistics at once.
Calculation Speed: Custom Formula vs Pandas Methods
While you can always calculate manually for mean or standard deviation, we will see which method is faster to compute both of them.
Calculation Speed: Custom Formula vs Pandas Methods
While you can always calculate manually for mean or standard deviation, we will see which method is faster to compute both of them.