learning pandas python data discovery and analysis made easy pdf

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"Python Learning notes-data structures and algorithms" quick sort

value.Similarly, when an element of the RightMark position is greater than or equal to the base value, RightMark moves to the left one position to continue scanning, and the scan stops when the element of the RightMark position is less than the base value.After stopping the scan, we compare the size of the Leftmark and RightMark, if the Rightmark  After we have put the datum values in the correct position, we see that the elements on the left side of the base value are smaller than the datum va

"Python Learning notes-data structures and algorithms" Selection sorting Selection sort

"Select Sort"The selection sort is based on a bubbling sort (Bubble sort) that has been improved: each visit process (pass) needs to be exchanged at most.Each visit process, to find the maximum value, when the end of the visit, the maximum value is exchanged to the correct position;Then continue to repeat the process in the remaining sublist until the n-1 visit is completed (n is the length of the list);At this point, the remaining elements in the list are automatically aligned to the correct po

Old boy Python learning data type collection

object ' abc ', and this method, although named Replace, does not change the contents of the string ' abc '. Instead, the Replace method creates a new string ' abc ' and returns, if we point to the new string with variable B, it's easy to understand that variable a still points to the original string ' abc ', but the variable B points to the new string ' abc ':Therefore, for an immutable object, any method that invokes the object itself does not chan

Python Learning--data serialization

Json/pickle Serialization of dataSerialization definition: The process of changing a variable from memory to a storage or transport is called serialization.Deserialization: Re-reading the contents of a variable from the serialized object into memory is called the anti-sequence hu.--pickle of the serialization moduleNote: In Python3, once serialized, and then deserialized, do not repeat multiple serialization, otherwise it cannot be deserialized.Pickle: is a

8 Python techniques for Efficient data analysis

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

"Machine learning experiment" learns python to classify real-world data

IntroducedCan a machine tell the variety of flowers according to the photograph? In the machine learning angle, this is actually a classification problem, that is, the machine according to different varieties of flowers of the data to learn, so that it can be unmarked test image data classification.This section, we still start from Scikit-learn, understand the ba

Fifth day of Learning Big data: Python implementation of least squares (ii)

fake_func (P, x):f = np.poly1d (P) #多项式分布的函数return f (x)#残差函数def residuals (p, y, x):Return Y-fake_func (p, x)#随机选了9个点, as Xx = Np.linspace (0, 1, 9)A lot of points #画图的时候需要的 "continuous"X_show = Np.linspace (0, 1, 1000)y0 = Real_func (x)#加入正态分布噪音后的yy1 = [Np.random.normal (0, 0.1) + Y for y in y0]#先随机产生一组多项式分布的参数P0 = Np.random.randn (M)PLSQ = LEASTSQ (residuals, P0, args= (y1, x))Print (' Fitting Parameters: ', plsq[0]) #输出拟合参数Pl.plot (X_show, Real_func (x_show), label= ' real ')Pl.plot (X_show

(Data Science Learning Codex) a detailed introduction to the RE module in Python

First, IntroductionAs for regular expressions, I have already made a detailed introduction in the previous (Data Science Learning Codex 31), which summarizes the common functions of the self-contained module re in Python.As a module supported by Python for regular expression related functions, re provides a series of m

"Python Data Analysis"

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

Some knowledge points related to Python data processing (learning points)

), and proficient at least one of them and used in multiple projects and have their ownexperiences and experiences;Other references:A. Familiar with common class libraries * proficient in Django architecture and development, and commonly used third-party packages * Familiar with restful API design and use, familiar with nonblocking io and asynchronous IO technologyB. Python fundamentals: Familiar with Io, multithreading and other basic technologiesPS:

"Python Learning notes-data structures and algorithms" bubble sorting Bubble sort

Recommend a Visual Web site "Visual Algo": Url= ' https://visualgo.net/en/sorting 'This website gives the principles and processes of various sorting algorithms, which are visualized through dynamic forms. The related pseudo-code are also given, as well as the specific steps to execute to code."Bubble Sort"You need to repeatedly visit the sequence of columns that need to be sorted. The size of the adjacent two items is compared during the visit, and if the order is not correct, two items are exc

Start machine learning with Python (3: Data fitting and generalized linear regression)

Prediction problems in machine learning are usually divided into 2 categories: regression and classification .Simply put, regression is a predictive value, and classification is a label that classifies data.This article describes how to use Python for basic data fitting, and how to analyze the error of fitting results.This example uses a 2-time function with a ra

Python vs machine learning-data preprocessing

attribute in the data set. The general situation is somewhere between the two.D. High-dimensional mappingMap properties to high-dimensional space. This is the most precise approach, which completely retains all the information and does not add any additional information. For example, Google, Baidu's CTR Prediction model, pre-processing will be all the variables to deal with this, up to hundreds of millions of dimensions. The benefit of this is that t

Python Learning note day3 (data type)

Python data type: int type Float decimal Type String strings Boolean type a = True B = False1. A list, also known as an array or a list or array. Its expression is rendered by subscript or index or number.students=[' Zhang San ', ' John Doe ', ' Harry ', ' Zhao Liu ']Print (Students[0])Note: The subscript for the first element is 0, and the last element is subscript 1Cities = []#增加: (Two

"Python Learning notes-data structures and algorithms" merge sort

"Merge Sort" Here we use recursive algorithm to keep the list in two, base case is no element in the list or only one element, because this sub-list is bound to be a positive sequence, and then gradually merge the two sorted sub-list into a new positive sequence table, until all the elements sorted."This is a process from the bottom up (bottom-up)Divides the list from the middle into two sub-lists until it reaches the bottom, with only one element in the sub-list  Then, the two sub-lists are mer

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