oreilly python for data analysis

I'm writing this article to show the basic ways to use Instagram programmatically. My approach can be used for data analysis, computer vision, and any cool projects you can think of. Instagram is the largest picture-sharing social media platform, with about 500 million active users per month, with 95 million of images and videos being uploaded to Instagram every day. Its

SummaryNumPy is the basis that must be mastered in data analysis using Python. is the foundation package for high-performance Scientific computing and data analysis. By using numpy, we can perform fast standard mathematical function calculation without loop, and can do linea

SummaryThe use of Python for data analysis, you need to install some common tools, such as numpy,pandas,scipy, etc., during the installation process, often encountered some installation details problems, such as version mismatch, need to rely on the package is not installed properly, etc. This article summarizes the next few necessary installation package install

RPY2 Environment Configuration　Recently, I want to integrate R into a web system with flask as a back-end framework, and perform data statistics analysis on the server side. The R language needs to be integrated into Python, and it is found that Rpy2 in Python can invoke the R language, so it took some time to configur

行一次测试frame4 = DataFrame ([[ Columns=[' A ', ' B ']) frame4.index.names = [' C ', ' d ']print frame4print frame4.reset_index (). Sort_index (axis = 1)Other topics related to pandas#-*-encoding:utf-8-*-import numpy as Npimport Osimport pandas as Pdfrom pandas import Series,dataframeimport matplotlib. Pyplot as Pltimport Pandas.io.data as web# here are some egg-ache problems: integer index and integer tag ser = Series (Np.arange (3.)) #print Ser[-1] #报错 because the ambiguity of the integer index

]])Mathematical and statistical methods:NumPy also provides a number of statistical functions to perform statistical operations on data, such as averaging, variance, and so on. Refer to the following table for detailsin [+]: arrOUT[35]:Array ([[0, 1, 2, 3, 4],[5, 6, 7, 8, 9],[10, 11, 12, 13, 14]])In [approx]: Np.mean (arr)OUT[36]: 7.0In [PNS]: np.std (arr)OUT[37]: 4.3204937989385739In []: Np.var (arr)OUT[38]: 18.666666666666668With these methods, we c

mature frame or wheel that can meet my needs? (Multi-threading, and can run at 7x24 hours, because the number of acquisitions is huge) In addition to ask, how to store the collected content (million to tens of millions), the data there are some digital data, the need for statistical analysis, with MySQL can it? Or is there any other more mature and simple wheels

Download address: Network disk download Introduction to the content More than 10 data mining senior experts and researchers, more than 10 years of large data mining consulting and implementation experience crystallization. From the application of data mining, based on the real cases of power, aviation, medical, Internet, manufacturing and public service, th

[Python Data Analysis] Python3 multi-thread concurrent web crawler-taking Douban library Top250 as an example, python3top250 Based on the work of the last two articles [Python Data Analysis] Python3 Excel operation-Take Douban lib

Most of the students who Do data analysis start with excel, and Excel is the most highly rated tool in the Microsoft Office Series.But when the amount of data is very large, Excel is powerless, python Third-party package pandas greatly extend the functionality of excel, the entry takes a little time, but really is the

Data volume: 3,289,329 people.Data acquisition tool: Distributed Python crawlerAnalysis tool: ElasticSearch + KibanaAnalysis angle: geographical location, gender ratio, all kinds of rankings, universities, active level.Please note:All of the following analysis results are based on the personal information of the 3 million users I crawl, non-authoritative

The Pandas object has some common mathematical and statistical methods. For example, the sum () method, which makes the column subtotal: the sum () method passed in Axis=1 is specified as a horizontal summary, which is subtotal: Idxmax () gets the index of the maximum value: There is also a rollup that is cumulative, cumsum (), compared to it and Su The difference between M ():The unique () method is used to return only values in the data: the Value_

[Python Data Analysis] solve and optimize some problems in Python3 Excel (2), pythonpython3 After the previous article titled "Python Data Analysis" and "Excel in Python3"-taking Douban book Top250 as an example to crawl the top P

QQ space Python crawler v2.0 -- thumb up data analysis, pythonv2.0 -- After remembering the previous v1.0 space crawler, I want to write another crawler to analyze my likes. FirstAnalyze Json: You can find that the node for thumb ups isData --> vFeeds (list) --> like --> likemans (list) --> user --> nickname uin The Code is as follows: 1 for I in range (0, pa

Numpy (numerical Python) Foundation package for high performance scientific computing and data analysis; Ndarray, multi-dimensional Array (matrix), with vector computing ability, fast, save space; Matrix operations, without loops, can be done similar to MATLAB in the vector operation; Linear algebra, random send generation; Ndarray, n-di

Using Python for data analysis--numpy basics: Arrays and Vector computing Ndarry, a multidimensional array with vector operations and complex broadcast capabilities for fast space-saving Standard mathematical function for fast operation of whole set of data without For-loop Tools for reading an

array corresponds to a one-dimensional array, the slice of a two-dimensional array is a fragment of one-dimensional array: multidimensional Arrays index of multidimensional arraysIn a one-dimensional array, a single index value returns the corresponding scalar, and in a two-dimensional array, a single index value returns the corresponding one-dimensional array; In a multidimensional array, a single index value returns an array of a lower latitude, for example: Boolean index A Boolean index

-Axis notes -Mp.ylabel (' Price') to #Drawing Graphs +Mp.plot (DT, Price, label="Year :"+Year ) -Mp.plot (DT2, Price2, label="Year :"+year2) the #tip marker line and position distance *Mp.legend (bbox_to_anchor=[0.8, 1]) $ #grid linesPanax Notoginseng Mp.grid () - #Save the resulting picture theMp.savefig ('e:\practice\cqhouseprice\static\img/'+ year +'. PNG', dpi = 100) + #show the resulting picture A mp.show () the #Close +Mp.close ()Input: Outputdata ana