wes mckinney python for data analysis

0.18Explode = (0, 0.1, 0, 0)9 Ten #Specify Canvas 1, instantiate plt.subplots () OneFIG1, ax1 =plt.subplots () A - #autopct is the specified percentage display specification, which retains one decimal place - #the last two keyword values are added shadows, and the starting angle is determined theAx1.pie (sizes, Explode=explode, Labels=labels, autopct='%1.1

How to: Enter in terminal Copy Code code as follows: Python weather.py http://www.weather.com.cn/weather/101010100.shtml Weather data in Beijing 6 days JSON format Copy Code code as follows: #coding =utf-8 #weather. py Import Urllib Import re Import Simplejson Import Sys If Len (SYS.ARGV)!= 2: print ' please enter:python ' + sys.argv[0] + ' Exit (0) url = sys.argv[1

This article records some of the knowledge that appears in the book, convenient to use when the query. Implied volatility rate The implied volatility is the value of those fluctuations in the price of different options and the market quotations measured on the maturity date under other conditions unchanged.In this case, the implied volatility is not the input parameter of the model/formula, but the result of a digital optimization process of the Formula 4.1 basic

1.1. Foreword Here we use the Python m/r framework mrjob to analyze.1.2. M/R Steps Mapper: The form of parsing the row data into Key=hh value=1Shuffle: The result of passing the Shuffle will generate a value iterator sorted with key valuesResults such as: 09 [1, 1, 1 ... 1, 1]Reduce: We're here to figure out 09 hours of traffic.Output such as: sum ([1, 1, 1 ...) 1, 1])1.3. Code Cat mr_pv_hour.py#-*-Codin

different passenger levels and survivalThe more advanced the class, the greater the proportion of survival. The proportion of those who were not rescued in class 3 was significantly increased. Indicates whether the class is related to the existence of the accommodation.The relationship between 3.2.2 Sex and survivalIt can be found that most are concentrated in the 20-50-year-old, from the box-line chart to see the average age of nearly 30 years.Because age is a continuous value, we consider the

= ' right '). SUM ())When closing the right, The statistic is the 5 - minute cycle with 00:00:00 as the end, because the time is ahead to 1999-12-31 23:55:00 . 1999-12-31 23:55:00 02000-01-01 00:00:00 152000-01-01 00:05:00 402000-01-01 00:10:00 11So left or right closing depends on the start and end of the timeIn the financial world there is an omnipresent time-series aggregation, that is, the calculation of the 4 values of each polygon , the first value open: Open, the last value close: Close,

Premise: If you have a hundreds of m file that needs to be parsed, a function needs to run many times (thousands of times), you need to consider performance issuesPerformance Analysis module: CProfileHow to use: Cprofile.run ("func ()"), where Func () is a function for profilingTest results: The results show how long each function was written, and when the built-in function was runAnalyze functions that run more times and take a lot of time to optimiz

I now need to perform automatic data collection on the list of articles on a website and the actual content in the list. the list can obtain the id of each article, each article uses a unified interface (with the article id included in the parameter to obtain the corresponding json... I now need to perform automatic data collection on the list of articles on a website and the actual content in the list. the

Problem Description: Run the following program to generate the hotel turnover simulation data file in the current folder Data.csvThen complete the following tasks:1) Use Pandas to read the data in the file Data.csv, create the Dataframe object, and delete all of the missing values;2) Use Matplotlib to generate line chart, reflect the daily turnover of the hotel, and save the graphic as a local file first.jp

, cookies = cookies, headers =headers) with open ('Douban_2.txt','wb+') as F:f.write (r.content)Two. Search with XPath import requests from lxml import etrees = requests. Session () for ID in range (0, 251, 25print (ID) ' https://movie.douban.com/top250/?start- ' + str (id) = s.get (URL) 'utf-8' = = Root.xpath ('//ol/li/div[@class = "item"] ')//Using XPath's tag selection # print (len (items)) for inch Items: = Item.xpath ('./div[@class = "Info"]//a/s