Tag: Python
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AI seminars — just one of the big changes at LernerPython
July and August are often when people take a break or go on vacation. But for me, this summer has been super busy, full of writing and improving LernerPython based on feedback I’ve gotten from people around the world. And so, I’m here with some big changes I’m making at LernerPython World Headquarters: 1. AI…
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Pandas Series filtering: Chaining loc for multiple conditions
My favorite way to apply multiple filters to a Python Pandas series? Method chaining calling loc 2x: But: This can break! Tomorrow, a better way.
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Pandas Series filtering: Split long conditions across lines
When applying multiple filters to a Python Pandas series, it’s often best to use multiple lines: This is easier to read, write, and maintain.
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Pandas boolean filtering: Wrap each condition in parentheses
Want to filter a Python Pandas series with two conditions? One option: Combine two boolean series with &. But careful: Put () around each boolean condition.
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Pandas boolean indexing: Selecting series items with a mask
Retrieve selected items from a Python Pandas series by broadcasting a condition, then using it as a boolean (“mask”) index:
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Pandas Series .loc: Selecting with labels and booleans
Retrieve from a Python Pandas series with .loc and indexes: If you pass booleans, True means “return a value,” and False means “ignore it.”
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Pandas Series broadcasting: Arithmetic and comparisons with scalars
Apply an operator to a Python Pandas series, with a scalar value, *broadcasts*: Arithmetic is most obvious: s + 5 # [15, 25, 35]s ** 2 # [100, 400, 900] But comparisons work, too: s >= 20 # [False, True, True]
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Pandas Series selection speed: iloc[:2] beats loc and head
What’s the fastest way to retrieve the first 2 items from a Python Pandas series?
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.loc vs .iloc in Pandas: Convenience versus speed
Using .loc to retrieve from a Python Pandas series is more convenient. But .iloc is faster: %timeit s.loc[‘a’] # 2.09 μs%timeit s.iloc[0] # 1.5 μs %timeit s.loc[[‘a’, ‘b’]] # 105 μs%timeit s.iloc[[0, 1]] # 26.4 μs
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Pandas iloc vs loc: Selecting series values by position
Retrieve from a Python Pandas series by position, rather than the index, with iloc: