• Pandas和numpy如何显示全部数据


    # 显示所有的列
    pd.set_option('display.max_columns', None)
    
    # 显示所有的行
    pd.set_option('display.max_rows', None)
    
    # 设置value的显示长度为100,默认为50
    pd.set_option('max_colwidth', 1000)
    
    pd.set_option('display.width', None)
    np.set_printoptions(precision=None, threshold=None, edgeitems=None, linewidth=None, suppress=None, nanstr=None, infstr=None)

    precision : int, optional,float输出的精度,即小数点后维数,默认8( Number of digits of precision for floating point output (default 8))

    threshold : int, optional,当数组数目过大时,设置显示几个数字,其余用省略号(Total number of array elements which trigger summarization rather than full repr (default 1000).)

    edgeitems : int, optional,边缘数目(Number of array items in summary at beginning and end of each dimension (default 3)).

    linewidth : int, optional,The number of characters per line for the purpose of inserting line breaks (default 75).

    suppress : bool, optional,是否压缩由科学计数法表示的浮点数(Whether or not suppress printing of small floating point values using scientific notation (default False).)

    nanstr : str, optional,String representation of floating point not-a-number (default nan).

    infstr : str, optional,String representation of floating point infinity (default inf).

    np.set_printoptions(threshold=np.nan)
    设置打印时显示方式,threshold=np.nan意思是输出数组的时候完全输出,不需要省略号将中间数据省略

    >>> np.set_printoptions(precision=4)
    >>> print np.array([1.123456789])
    [ 1.1235]
    
    >>> np.set_printoptions(threshold=5)
    >>> print np.arange(10)
    [0 1 2 ..., 7 8 9]
    
    >>> eps = np.finfo(float).eps
    >>> x = np.arange(4.)
    >>> x**2 - (x + eps)**2
    array([ -4.9304e-32,  -4.4409e-16,   0.0000e+00,   0.0000e+00])
    >>> np.set_printoptions(suppress=True)
    >>> x**2 - (x + eps)**2
    array([-0., -0.,  0.,  0.])
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  • 原文地址:https://www.cnblogs.com/xinmomoyan/p/15166479.html
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