wes mckinney python for data analysis

I. Introduction of IPython IPython is an interactive Python interpreter, and it's more efficient. It differs from most traditional working modes (edit-and-compile-run),The working mode it uses is: Execute-and explore, and most of the code related to data analysis contains exploratory operations (such as trial and error methods and iterative methods), so IPython

Returns a Series that contains only non-empty data and index valuesRemove the missing field first: Cframe=frame[frame.a.notnull ()]Second, it calculates whether the rows are Windows based on the value of a, #np. The WHERE function is a vectorization ifelse functionOperating_system=np.where (cframe[' a '].str.contains (' windows '), ' windows ', ' no windows ')Next, the data is grouped according to the time

Use Python to connect to the central control attendance machine. Download and analyze the data and send the results to the personnel.Central Control SDK Package: x32 Address x64 AddressSDK Package recommended 32-bit, on the Win7 64-bit system with 64-bit development package does not, with 32 can.Python also pywin32 note version, I use the 32-bit Python 2.7 and th

which one is best for use, so let's review it.Concat allows the user to append one or more dataframe (depending on how you define the axis) below or next to the table.Merge merges multiple dataframe to specify the same row as the primary key (key).Join, like merge, incorporates two dataframe. But it does not merge by a specified primary key, but is merged by the same column name or row name.Pandas ApplyApply is designed for the pandas series. If you're not familiar with series, you can think of

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 internal relationship of data. The interactive GUI is a good choice for interactive support.MayaviThis is a 3D graphics toolkit based on the open source C + + graphics library VTK. can be integrated into Ipython for interactive use.Other librariesOther libraries or applications include: PYQWT, Veusz, Gnuplotpy, Biggles, and so on, and large libraries are developing to web-based technologies and moving away from desktop graphics technology.The fut

)Run Result: [' 1 ' 2 ' 5 ' 11 '](2) NumPy create a two-dimensional arraySyntax: Numpy.array ([[Element 1, Element 2,..., element n],[element 1, Element 2,..., element n],..., [element 1, Element 2,..., element N]])Import= Numpy.array ([[11,4,2],[2,6,1],[32,6,42]])print(y)Operation Result:[[11 4 2][2 6 1][32 6 42]](3) Sort by using sortImportNumPy#Numpy.array ([element 1, Element 2,..., element n])x = Numpy.array (["m","2","5"," One"])#sort xX.sort ()Print(x)#Numpy.array ([[Element 1, Element 2,

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

areas of the drawing method (one is using the above column chart that way Fig,ax = Plt.subplots), the other is the following, this can be customized to occupy the number of spaces)Fig = plt.figure () Ax1 = Plt.subplot2grid ((2,3), (0,0)) Ax1.bar (data_bar.index,data_bar.values) fig.set_size_inches ( 12,6) Ax2 = Plt.subplot2grid ((2,3), (0,1), colspan=2) #占据几个空额, can also be rowspan, one is horizontal, one is vertical ax2.scatter (data[' Tip '],

#-*-coding:utf-8-*-#Data IntegrationImportCSVImportNumPy as NPImportPandas as PDImportMatplotlib.pyplot as Plt#Customer InformationBasicinfo = PD. Dataframe.from_csv ('Datas/basicinfo_train.csv', header=0, sep=',', Index_col=0, Parse_dates=true, Encoding=none, Tupleize_cols=false, infer_datetime_format=False)#Historical Repayment RecordsHistoryinfo = PD. Dataframe.from_csv ('Datas/history_train.csv', header=0, sep=',', Index_col=0, Parse_dates=true, E

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 (

This article mainly introduces the real IP request Pandas for Python data analysis. in this article, we will introduce the example scheme in detail, I believe it has some reference value for everyone's learning or understanding. if you need it, you can refer to it. let's learn it together. Preface Pandas is a data

--pylabImport Pandasplot (Arange (10))The appearance of the tablet is the success:PS: often easy to appear during installation of Pandas error :' ASCII ' codec can ' t decode byte 0xd5 Workaround: Add in python/lib/site.py Import sysreload (SYS) sys.setdefaultencoding ('gbk')2. Install the Pycharm and install the pandas (you can also add a package such as NumPy, the same way)Download and install Pycharm, and then add Pandas in Pycharm: (The process

：import1 Import matplotlib.pyplot as Plt2 a=series (NP.RANDOM.RANDN (+), Index=pd.date_range (' 20100101 ', periods=1000)) 3 b= A.cumsum () 4 B.plot () 5 plt.show () #最后一定要加这个plt. Show (), or the graph will not appear.2.PNGYou can also use the following code to generate multiple time series diagrams:a=DataFrame(np.random.randn(1000，4),index=pd.date_range(‘20100101‘,periods=1000),columns=list(‘ABCD‘))b=a.cumsum()b.plot()plt.show()3.png 11, Import and Export filesWriting and reading Excel files

(Llen)) Dlen=Randrange (Llen, -) Dom= "'. Join (Choice (LC) forJinch Range(Dlen)) Result_data.append ('%s::%s@%s.%s::%d-%d-%d' %(DTSTR, login, DOM, choice (TLDs), Dtint, Llen, Dlen))#print (result_data)#test reRe_patt= ' ^ (\w{3}).*::(? P forIteminchResult_data:m=Re.match (Re_patt, item)ifM is not None:Print(' * '* -)Print(item)Print("Email:" +M.group (' Email '))Print(' number: ' +M.group (' number '))Tue Jan 15:34:09 1992::[emailprotected]::696584049-7-11email: [email Protected]number:6965840

Objective Pandas is a numpy built with more advanced data structures and tools than the NumPy core is the Ndarray,pandas is also centered around Series and dataframe two core data structures. Series and Dataframe correspond to one-dimensional sequence and two-dimensional table structure respectively. Pandas's conventional approach to importing is as follows: From pandas import series,dataframe impo

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