wes mckinney python for data analysis

# #之前已经有很多人写过相关内容, but I have not read before, this crawler is also in accordance with their own ideas written, may be more ugly, please forgive me!I as a novice Python crawler and stock market leek, because of time every night no way to turn billboard data, so I hope to use the Crawler to filter out useful information for my analysis (in fact, I want to lazy ...

element is the index of the item whose index number is smaller than the previous one. So we see that the value of index 2,3 is 1, and the value of index 1 If you want to use the element following the newly inserted index, you need to use the Bfill method The replacement index can be extended from series to dataframe, not only to replace the row index, but also to replace the column index or even replace both Second, delete ① Deleting a series Pandas specificall

first, the initial knowledge of pandas Pandas is a very useful library based on NumPy, which has two unique basic data Structures series (one-dimensional) and dataframe (two-dimensional) that make data operations simpler. Although pandas has two data structures, it is still a library of Python, so some

, time data. And there are calendar features. The datetime, time, and calendar modules are used primarily. #-*-coding:utf-8-*-ImportNumPy as NPImportPandas as PDImportMatplotlib.pyplot as PltImportdatetime as DT fromDatetimeImportDatetimenow=DateTime.Now ()#datetime stores time in millisecondsPrintNow,now.year,now.month,now.day,now.microsecond,'\ n'#print datetime (2015,12,17,20,00,01,555555) #设置一个时间#Datetime.timedelta represents a time difference bet

one-dimensional array in column form5. Row-StackedSplitting numpy arraysRelated functions Hsplit (), Vsplit (), Dsplit (), and split (). We can either divide the array into an array of the same shape, or we can begin to cut the array from the specified position.1. Split horizontallyThe split () function equivalent to calling the parameter Axis=1:2. Split verticallyWhen the parameter Axis=0,split () function also decomposes the array along the vertical axis3. Deep splitThe premise is that there

#-*-coding:utf-8-*-#analysis of food and beverage sales data statistics from __future__ Importprint_functionImportPandas as Pdcatering_sale='.. /data/catering_sale.xls' #Dining Datadata = Pd.read_excel (Catering_sale, Index_col = u'Date')#reading data, specifying "date" as index columndata =

I recently started to learn Python, numpy, scipy, etc. I want to do some data projects, but I have no experience in this area. So I want to know what interesting projects have been done by everyone, or if I have any good options to start with, I recommend the following reply content: (Note: what channels do you use to obtain the knowledge and information that the average person does not know? -He mingke's a

1, NumpyInstallation: Pip Install NumPy[[email protected] work]#Cat numpy_test.py#!/usr/bin/env python#Coding:utf-8 from __future__ Importprint_function#import modules and add aliasesImportNumPy as NP#Create an arrayA = Np.array ([2,0,1,7])Print(a)Print(A[:3])Print(A.min ()) A.sort ()Print(a)#Create two-dimensional datab = Np.array ([[1,2,3],[4,5,6]])Print(b)Print(b*b) [[email protected] work]#python numpy_

Chapter Nineth Analysis of text data and social media 1 Installation NLTK slightly 2 Filter Stop word name and number The sample code is as follows: ImportNLTK # Load English stop word corpus SW = set (Nltk.corpus.stopwords.words (' 中文版 ')) print (' Stop words ', list (sw) [: 7]) # Get the part of the Gutenberg Corpus File GB = Nltk.corpus.gutenberg print (' Gutenberg files ', gb.fileids () [-5:]) # Tak

Pandas is the preferred library for subsequent content in this book. The pandas can meet the following requirements: Data structure with automatic or explicit data alignment by axis. This prevents many common errors caused by data misalignment and data from different data