oreilly python for data analysis

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Python Data analysis----matplotlib

Matplotlib is a powerful toolkit for Python drawing and data visualization.Installation method: Pip Install MatplotlibReference method: Import Matplotlib.pyplot as PltDrawing function: Plt.plot ()Display Image: Plt.show ()Simple example:Import Matplotlib.pyplot as Pltin [269]: x = np.linspace (5,15,1000) in [+]: y = x*xIn [271]: PLT . plot (x, y) out[271]: []in [272]: Plt.show ()ImagePlot function:

Data analysis using Python d1--ch02 introduction

The Basic course has not finished, it came to this, because my usual research is based on data processing. Who says the woman is inferior to the male 650) this.width=650; "src=" Http://img.baidu.com/hi/jx2/j_0011.gif "alt=" J_0011.gif "/>do your own things well done carefully, Hee 650) this.width=650; "src=" Http://img.baidu.com/hi/jx2/j_0003.gif "alt=" J_0003.gif "/>Read the introductory section, download the dat

Python data Analysis-detailed daily Pv-pandas

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

Principal component analysis of Python remote sensing data

)#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

Data analysis using python: "Matplotlib"

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

Dataframe Application of Pandas Library of Python data analysis

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

Using Python for data analysis--histogram

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

Python Data Analysis-date processing

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

Python data analysis-first week

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

Python crawler (ii)--analysis of the rental data of Kaifeng 58 in the same city

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 (

Configuring the Python data Analysis environment in a MAC environment

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

Data analysis using Python (6) NumPy Basics: Vector Computing

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

-04-numpy Foundation for data analysis using Python

, 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

Matplotlib plotting of Python data analysis

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

Python Object System in-depth analysis, python system in-depth analysis

Python Object System in-depth analysis, python system in-depth analysis This article analyzes in detail the Python object system. Share it with you for your reference. The details are as follows: Guido uses C language to create Python

Variable assignment operation instance analysis in Python programming and python instance analysis

Variable assignment operation instance analysis in Python programming and python instance analysis This article describes how to assign values to variables in Python programming. We will share this with you for your reference. The details are as follows: # Coding = utf8''' i

Python read Excel Method Instance analysis, python instance analysis

Python read Excel Method Instance analysis, python instance analysis This example describes how to read an Excel file from Python. Share it with you for your reference. The details are as follows: This day, data is imported from a

Analysis of python coroutine concepts, analysis of python coroutine

Analysis of python coroutine concepts, analysis of python coroutine This article describes the learning experience of the python coroutine provided by readers. The following is all about it: The history of coroutine is long and must start with the generator. If you have read

Python iterator instance analysis, python instance analysis

Python iterator instance analysis, python instance analysis This article describes the simple usage of the python iterator for your reference. The specific analysis is as follows: Generator expressions are used to generate sequenc

Example Analysis of Class usage in Python and Analysis of python instances

Example Analysis of Class usage in Python and Analysis of python instances This example describes the usage of the Class in Python. We will share this with you for your reference. The details are as follows: Although Python has ad

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