python for data analysis 2nd edition pdf

1.1. Foreword This way we use the memory analysis framework pandas to analyze the daily PV.1.2. Praise to Pandas In fact, personal to pandas this module is quite favorable. I use pandas to complete many of the day-to-day practical gadgets, such as the production of Excel reports, simple data migration, and so on. To me, pandas is a memory MySQL, I usually call him the program SQL. 1.3. Pandas

)#Display OutputFigure () Gray () forIinchRange (File_len): Subplot (3,4,i + 1) pic= Immatrix[i].reshape (180,360) pic= Pic[::-1]#picshow = rot90 (pic,4)imshow (pic) Colorbar () show ()#Convert to sample populationX =Immatrix. T#get to this sizeM,n = X.shape[0:2]#obtain the average of each sampleMeanval = mean (X,axis =0)#Tempmean = Tile (Meanval, (64800,1))#Sample matrix de -CentralizedX = X-tile (Meanval, (64800,1))#Calculate covarianceS = dot (x.t,x)/(m-1)#calculate eigenvalues eg and eigenve

First, Brief introduction matplotlib1. Matplotlib is a powerful toolkit for Python drawing and data visualization2. Installation method: Pip Install Matplotlib3. Citation method: Import Matplotlib.pyplot as Plt4. Drawing function: Plt.plot ()5. Display Image: Plt.show () --Linetype LineStyle (-,-.,--,.. ) -colour color (b,g,r,y,k,w,... 2, plot function draw multiple curves 3, Pandas package

ordered data such as time series, it may be necessary to do some interpolation when re-indexing, the method option can achieve this purpose:For ordered data such as time series, it may be necessary to do some interpolation when re-indexing, the method option can achieve this purpose: Method Parameter Introduction Parameters Description Ff

The tenth chapter of the book, "Python For Data Analysis", focuses on the processing of time series data.Label1. DateTime object, timestamp object, period object2. Two special indexes for pandas series and Dataframe object: Datetimeindex and Periodindex3. Time zone expression and processing4. Imestamp The frequency concept of object, period object, and its freque

DataFrame.hist(Data,Column=none,By=none,grid=true,Xlabelsize=none,Xrot=none,Ylabelsize=none,Yrot=none,Ax=none,Sharex=false,Sharey=false,Figsize=none,Layout=none,bins=10,**kwds)Data : DataFramecolumn : string or sequence strings or sequences by: object, optional If passed, then used to form histograms (histogram) for separate groups Grid : Boolean, default True grid line, defaul

Date-time data types and tools from Import = datetime.now ()print(now.year,now.month,now.day)# stores time in milliseconds Delta = now-datetime (1992,2,2)print(delta)print(delta.days) # You can subtraction from import timedeltaprinton the timestamp ( Delta+timedelta (12))String and DateTime conversions#Time Turn strTime_str = Now.strftime ('%y-%m-%d')Print(TIME_STR)#Str Turn TimeTIME_STR2 = Datetime.strptime (Time_str,'%y-%m-%d')Print(TIME_STR2)#wo

NumPy:NdarrayPandas:DataFrameMatplotlib:SciPy:IntegrateLinalgOptimizeSignalSparseSpecialStatsWeaveCanopy InstallationPython variable typeNumbers (digital)--int,long,float,complexString (String)-counting starting at 0, starting bit, ending (excluding end)List (lists)--can be changed, assignedTuple (tuple)--Non-changing assignmentDictionary (dictionary)--can be changed, assigned valuePython Data type conversionsPython operator--arithmetic operator, comp

Size of rental room (area)　　　　　　　　　 Rental Rate (price) Compare informationCode1 ImportMatplotlib as Mpl2 ImportMatplotlib.pyplot as Plt3 ImportPandas as Pad4 ImportSeaborn as SNS5 ImportNumPy as NP6 7Sns.set_style ('Dark')8KF = Pad.read_csv ('Kf.csv')9 Ten defSinplotone (): OneFig,ax =plt.subplots () AAx.violinplot (kf[' Price']) - plt.show () - the defsinplottwo (): -Sns.set_style ('Whitegrid') -Sns.boxplot (kf[' Price'],palette=' Deep') - #sns.despine (left=true) + plt.show (

C, C + +, FORTRAN code integration into Python tools Pandas: A large number of data structures and functions that handle structured data Precise indexing, reshaping, slicing, chopping, aggregating, selecting subsets High performance time series features and tools Matplotlib: The most popular library for plotting

The way of thinking is mainly based on this article, linking:Http://www.jb51.net/article/78667.htmBut when the installation of brew, it may be the problem of the site, has been an errorSo looking for information from the Internet, brew installation needs a new window, non-root developmentSpecific methods refer to connection: http://jingyan.baidu.com/article/335530da8b2b0419cb41c338.htmlThe command line is as follows: Ruby-e "$ (curl-fssl https://raw.githubusercontent.com/Homebrew/install/m

Vectorization refers to using an array expression instead of a loop to manipulate each element in the array.The general functions provided by NumPy (both Ufunc functions) are functions that perform element-level operations on data in Ndarray. For example, the square function computes the square of each element, and the rint function rounds each element:There are also some functions that accept 2 parameters, called two ufunc, such as the Add function a

, the normal function can generate a sample array of 4*4: Samples = np.random.normal (size = (bis)) samplesout[]: Array ([[-1.22102285, 2.08688133, 1.15874399, 0.14342708], [-0.29772372, 0.36137871, 0.60243437, -0.09287792], [-0.49263459, 0.69445334, 1.02035894, -1.18263174], [-0.07184985,- 1.11834445, 0.89547984, 0.0585053]]) 3. ExampleRandom Walk 1000:nsteps = np.random.randint (0,2,size= Np.where (draws>0,1,-1= steps.cum

This blog is used to record learning and facilitate review review.PyplotIn the Matplotlib object-oriented drawing library, Pyplot is a convenient interface.Basic drawing functionsMp.plot (array of horizontal coordinates, array of vertical coordinates) 1 from __future__ import unicode_literals 2 import NumPy as NP 3 import Matplotlib.pyplot as MP 4 x = Np.linspace (-np.pi, Np.pi, 1000) 5 cos_y = Np.cos (x)/26 sin_y = Np.sin (x) 7 mp.plot (x, cos_y) 8 mp.plot (x, sin_y) 9 m

Before doing data analysis, many are using Oracle or MySQL, SQL to complete the query and statistical data analysis, but with the increase in data volume, the database with the development of a NoSQL database, due to the changes in the database and its underlying technology