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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