Numpy学习笔记练习代码 ——（二）

import numpy as np

A = np.array([(1,'First',0.5,1+2j),(2,'Second',1.5,1+3j),(3,'Third',0.8,1-2j)],dtype=('i2,a6,f4,c8'))

A
Out[3]: 
array([(1, b'First',  0.5       ,  1.+2.j),
       (2, b'Second',  1.5       ,  1.+3.j),
       (3, b'Third',  0.80000001,  1.-2.j)],
      dtype=[('f0', '<i2'), ('f1', 'S6'), ('f2', '<f4'), ('f3', '<c8')])

A[1]
Out[4]: (2, b'Second',  1.5,  1.+3.j)

A['f2']
Out[5]: array([ 0.5       ,  1.5       ,  0.80000001], dtype=float32)

A['f1']
Out[6]: 
array([b'First', b'Second', b'Third'],
      dtype='|S6')

A = np.array([(1,'First',0.5,1+2j),(2,'Second',1.5,1+3j),(3,'Third',0.8,1-2j)],dtype=[('id','i2'),('position','a6'),('value','f4'),('complex','c8')])

A
Out[8]: 
array([(1, b'First',  0.5       ,  1.+2.j),
       (2, b'Second',  1.5       ,  1.+3.j),
       (3, b'Third',  0.80000001,  1.-2.j)],
      dtype=[('id', '<i2'), ('position', 'S6'), ('value', '<f4'), ('complex', '<c8')])

A = np.array([(1,'First',0.5,1+2j),(2,'Second',1.5,1+3j),(3,'Third',0.8,1-2j)])

A
Out[10]: 
array([['1', 'First', '0.5', '(1+2j)'],
       ['2', 'Second', '1.5', '(1+3j)'],
       ['3', 'Third', '0.8', '(1-2j)']],
      dtype='<U11')

A.dtype.names = ('id','position','value','complex')
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-11-4f156499990d> in <module>()
----> 1 A.dtype.names = ('id','position','value','complex')

ValueError: there are no fields defined

A = np.array([(1,'First',0.5,1+2j),(2,'Second',1.5,1+3j),(3,'Third',0.8,1-2j)],dtype=[('id','i2'),('position','a6'),('value','f4'),('complex','c8')])

A
Out[13]: 
array([(1, b'First',  0.5       ,  1.+2.j),
       (2, b'Second',  1.5       ,  1.+3.j),
       (3, b'Third',  0.80000001,  1.-2.j)],
      dtype=[('id', '<i2'), ('position', 'S6'), ('value', '<f4'), ('complex', '<c8')])

A.dtype.names = ('id','order','value','complex')

A['order']
Out[15]: 
array([b'First', b'Second', b'Third'],
      dtype='|S6')

data = np.arange(1,17).reshape(4,4)

data
Out[17]: 
array([[ 1,  2,  3,  4],
       [ 5,  6,  7,  8],
       [ 9, 10, 11, 12],
       [13, 14, 15, 16]])

np.save('saved_data',data)

loaded_data = np.load('saved_data.npy')

loaded_data
Out[20]: 
array([[ 1,  2,  3,  4],
       [ 5,  6,  7,  8],
       [ 9, 10, 11, 12],
       [13, 14, 15, 16]])

data = np.genfromtxt('E:.0pythondemodemo1	demo.csv',delimiter=',',names=True)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-21-dacc8747616f> in <module>()
----> 1 data = np.genfromtxt('E:.0pythondemodemo1	demo.csv',delimiter=',',names=True)

D:ProgramDataAnaconda3libsite-packages
umpylib
pyio.py in genfromtxt(fname, dtype, comments, delimiter, skip_header, skip_footer, converters, missing_values, filling_values, usecols, names, excludelist, deletechars, replace_space, autostrip, case_sensitive, defaultfmt, unpack, usemask, loose, invalid_raise, max_rows)
   1549                 fhd = iter(np.lib._datasource.open(fname, 'rbU'))
   1550             else:
-> 1551                 fhd = iter(np.lib._datasource.open(fname, 'rb'))
   1552             own_fhd = True
   1553         else:

D:ProgramDataAnaconda3libsite-packages
umpylib\_datasource.py in open(path, mode, destpath)
    149 
    150     ds = DataSource(destpath)
--> 151     return ds.open(path, mode)
    152 
    153 

D:ProgramDataAnaconda3libsite-packages
umpylib\_datasource.py in open(self, path, mode)
    492 
    493         # NOTE: _findfile will fail on a new file opened for writing.
--> 494         found = self._findfile(path)
    495         if found:
    496             _fname, ext = self._splitzipext(found)

D:ProgramDataAnaconda3libsite-packages
umpylib\_datasource.py in _findfile(self, path)
    335 
    336         for name in filelist:
--> 337             if self.exists(name):
    338                 if self._isurl(name):
    339                     name = self._cache(name)

D:ProgramDataAnaconda3libsite-packages
umpylib\_datasource.py in exists(self, path)
    440 
    441         # Test local path
--> 442         if os.path.exists(path):
    443             return True
    444 

D:ProgramDataAnaconda3libgenericpath.py in exists(path)
     17     """Test whether a path exists.  Returns False for broken symbolic links"""
     18     try:
---> 19         os.stat(path)
     20     except OSError:
     21         return False

ValueError: stat: embedded null character in path

data = np.genfromtxt(r'E:.0pythondemodemo1	demo.csv',delimiter=',',names=True)
---------------------------------------------------------------------------
UnicodeDecodeError                        Traceback (most recent call last)
<ipython-input-22-bbff58f6826a> in <module>()
----> 1 data = np.genfromtxt(r'E:.0pythondemodemo1	demo.csv',delimiter=',',names=True)

D:ProgramDataAnaconda3libsite-packages
umpylib
pyio.py in genfromtxt(fname, dtype, comments, delimiter, skip_header, skip_footer, converters, missing_values, filling_values, usecols, names, excludelist, deletechars, replace_space, autostrip, case_sensitive, defaultfmt, unpack, usemask, loose, invalid_raise, max_rows)
   1605     if names is True:
   1606         names = validate_names([_bytes_to_name(_.strip())
-> 1607                                 for _ in first_values])
   1608         first_line = b''
   1609     elif _is_string_like(names):

D:ProgramDataAnaconda3libsite-packages
umpylib
pyio.py in <listcomp>(.0)
   1605     if names is True:
   1606         names = validate_names([_bytes_to_name(_.strip())
-> 1607                                 for _ in first_values])
   1608         first_line = b''
   1609     elif _is_string_like(names):

D:ProgramDataAnaconda3libsite-packages
umpylib\_iotools.py in _bytes_to_name(s)
     23 
     24     def _bytes_to_name(s):
---> 25         return s.decode('ascii')
     26 else:
     27     _bytes_to_complex = complex

UnicodeDecodeError: 'ascii' codec can't decode byte 0xd0 in position 0: ordinal not in range(128)

data = np.genfromtxt(r'E:.0pythondemodemo1	demo.csv',delimiter=',',names=True)

data
Out[24]: 
array([( 1.,  123.,  1.4,  23.), ( 2.,  110.,  0.5,  18.),
       ( 3.,  164.,  2.1,  19.)],
      dtype=[('id', '<f8'), ('value1', '<f8'), ('value2', '<f8'), ('value3', '<f8')])

# 内容为空的项填充为nan值

data['id']
Out[26]: array([ 1.,  2.,  3.])

data[1]
Out[27]: ( 2.,  110.,  0.5,  18.)