《Python資料分析基礎教程：Numpy學習指南》 常用子產品與方法簡要記錄

第三章 numpy的常用函數1.savetxt

2.loadtxt (converters): datetime.datetime.strptime [p46]

3.average

4.mean

5.max

6.min

7.ptp

8.median

9.msort/sort

10.var

11.diff

12.std

13.where

14:take

15:argmax ----- *

16:argmin ----- *

17.ravel

18.split\hsplit\vsplit

19.apply_along_axis

20.maximum ----- *

21.minimum ----- *

22.convolve

23.eye

24.zeros

25.ones

26.linspace

27.exp

28.fill

29.linalg.lstsq

30.dot

31.ones_like

32.intersect1d

33.vstack\hstack\dstack\column_stack\row_stack

34.concatenate

ndarray常用函數和屬性ndarray的常用函數

1.mean

2.ravel

3.sum

4..clip

5.compress

6.prod

7.cumprod

8.tolist

9.astype

10.resh

ndarray的常用屬性

1.ndim

2.size

3.itemsize

4.shape

5.dtype

6.nbytes

7.T

8.real

9.imag

10.flat

第四章 numpy的便捷函數1.diagonal

2.trace

3.cov

4.corrcoef

5.std ddof=1

6.polyfit

7.polyval

8.roots

9.polyder

10.sign

11.piecewise

12.vectorize

13.hanning

14.polysub

15.isreal

16.select

17.trim_zeros

第五章 矩陣和通用函數1.mat

① 專用字元串： " "行間隔， ";"列間隔

② 數組

2.bmat

3.frompyfunc

4.zeros_like

5.add.reduce

6.add.accumulate

7.add.reduceat

8.add.outer

9.add\subtract\multiply\divide\true_divide\floor_division

10."/" "//"

11.mod\%\remainder\fmod

12.matrix

第六章 深入Numpy子產品1.np.dual

2.np.linalg.inv

3.np.mat 注意，矩陣乘法和數組乘法不相同，與數組dot方法相同

4.np.linalg.solve

5.np.linalg.eigvals

6.np.linalg.eig

7.np.linalg.svd

8.np.linalg.pinv

9.np.linalg.det

10.np.fft.fft

11.np.fft.ifft

12.np.all

13.np.linalg.fftshift

14.np.linalg.ifftshift

15.np.random.binomial

16.np.random.hypergeometirc

17.np.random.beta

chisquare

exponential

f

gamma

gumbel

laplace

lognormal

logistic

multivariate_nomal

noncentral_chisquare

noncentral_f

normal

第七章 Numpy專用函數1.np.sort

lexsort

argsort

ndarray.sort

msort

sort_complex

2.np.argmax

3.np.nanargmax

4.np.argmin

5.np.nanargmin

6.np.argwhere

7.np.searchsorted

8.np.extract

9.np.insert

10.np.nonzero

11.np.bartlett

12.np.blackman

13.np.hamming

14.np.hanning

15.np.kaiser

12.np.i0

13.np.sinc

第八章 品質控制1.np.testing.assert_almost_equal

2.np.testing.assert_approx_equal

3.np.testing.assert_array_almost_equal

4.np.testing.assert_array_equal

5.np.testing.assert_array_less

6.np.testing.assert_equal

7.np.testing.assert_raises

8.np.testing.assert_warns

9.np.testing.assert_string_equal

10.np.testing.assert_allclose

11.np.testing.assert_alloclose

12.np.testing.assert_array_almost_equal_nulp

13.np.testing.assert_array_max_ulp

14.import unittest

from numpy.testing.decorators import setastest

from numpy.testing.decorators import skipif

from numpy.testing.decorators import knownfailureif

from numpy.testing import decorate_methods

15.numpy.testing.decorators.deprecated

16.numpy.testing.decorators.knownfailureif

17.numpy.testing.decorators.setastest

18.numpy.testing.decorators.skipif

19.numpy.testing.decorators.slow

20.from numpy.testing import rundocs

第九章 使用Matplotlib1.import matplotlib.pyplot as plt

2.np.poly1d

3.plt.plot

4.plt.xlabel

5.plt.ylabel

6.plt.show

7.np.poly1d.deriv

8.plt.subplot

9.plt.title

10.plt.figure

11.plt.figure.add_subplot

12.axis.set_major_locator

13.axis.set_minor_locator

14.axis.set_major_fomatter

15.figure.autofmt_xdate

16.from datetime import date

17.date.today

18.plt.hist

19.plt.semilogx

20.plt.semilogy

21.plt.loglog

22.plt.scatter

23.figure.set_title

24.plt.grid

25.plt.fill_between

26.plt.legend

27.plt.annotate

28.np.meshgrid

29.plt.plot_surface

30.plt.contour/plt.contourf

31.np.random.rand

32. import matplotlib.animation as animation

33. animation.FuncAnimation

34. from mpl_toolkits.mplot3d import Axes3D

第十章 SciPy0.from scipy import stats

1. stats.norm.rvs

2.stats.norm.fit

3.stats.kurtosistest

4.stats.skewtest

5.stats.normaltest

6.stats.scoreatpercentile

7.stats.percentileofscore

8.stats.ttest_ind

9.stats.ks_2samp

10.from scikits.statsmodels.stattools import jarque_bera

11.from scipy import signal

signal.detrend

12.from scipy import fftpack

fftpack.fftshift

fftpack.rfft

ffpack.iffshift

ffpack.irfft

13.from scipy import optimize

optimize.leastsq

14.from scipy import integrate

integrate.quad

15.from scipy imprt interpolate

interpolate.interp1d

interpolate.interp2d

16.from scipy import ndimage

ndimage.median_filter

ndimage.rotate

ndimage.prewitt

17.from scipy import misc

image = misc.lena().astype(np.float)

18.plt.imshow(image,  cmap=plt.cm.gray)

19. from scipy.io import wavfile

wavfile.read

wavfile.write

20.np.tile

21.import urllib2

urllib2.urlopen