New PDF release: Python for data analysis : [agile tools for real-world data]

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Extra info for Python for data analysis : [agile tools for real-world data]

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12 ? -> %quickref -> help -> object? -> -- An enhanced Interactive Python. Introduction and overview of IPython's features. Quick reference. Python's own help system. ' for extra details. In [1]: a = 5 In [2]: a Out[2]: 5 You can execute arbitrary Python statements by typing them in and pressing . 2228955458351768} 46 | Chapter 3: IPython: An Interactive Computing and Development Environment Many kinds of Python objects are formatted to be more readable, or pretty-printed, which is distinct from normal printing with print.

Matching the characters you have typed so far: In [1]: an_apple = 27 In [2]: an_example = 42 In [3]: an an_apple and an_example any In this example, note that IPython displayed both the two variables I defined as well as the Python keyword and and built-in function any. ). These, too, can be tab-completed but you must first type an underscore to see them. If you prefer to always see such methods in tab completion, you can change this setting in the IPython configuration. py Combined with the %run command (see later section), this functionality will undoubtedly save you many keystrokes.

DataFrame'> Int64Index: 1690784 entries, 0 to 1690783 Data columns: name 1690784 non-null values sex 1690784 non-null values births 1690784 non-null values year 1690784 non-null values prop 1690784 non-null values dtypes: float64(1), int64(2), object(2) When performing a group operation like this, it's often valuable to do a sanity check, like verifying that the prop column sums to 1 within all the groups. sum(), 1) Out[379]: True Now that this is done, I’m going to extract a subset of the data to facilitate further analysis: the top 1000 names for each sex/year combination.

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