Regular expressions (regex) are powerful tools for pattern matching and text manipulation in Python. Here are five Python regex examples with explanations: 01 Matching a Simple Pattern import re text = "Hello, World!" pattern = r"Hello" result = re.search(pattern, text) if result: print("Pattern found:", result.group()) Output: Output: Pattern found: Hello This example searches for the pattern "Hello" in the text and prints it when found. 02 Matching Multiple Patterns import re text = "The quick brown fox jumps over the lazy dog." patterns = [r"fox", r"dog"] for pattern in patterns: if re.search(pattern, text): print(f"Pattern '{pattern}' found.") Output: Pattern 'fox' found. Pattern 'dog' found. It searches for both "fox" and "dog" patterns in the text and prints when they are found. 03 Matching Any Digit import re text = "The price of the
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2 Top Tableau Unique Features
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Tableau is one of the most popular tools in data analysis. Learning the Tableau gives you so many options in data analysis career.
You can download Tableau Software free version here. Get a complete understanding document on how Tableau works here. Read this post for advancing in your Tableau Career.
Unique functionality in Tableau
Tableau Software was founded on the idea that analysis and visualization should not be isolated activities but must be synergistically integrated into a visual analysis process. Visual analysis means specifically:
1). Data Exploration
Visual analysis is designed to support analytical reasoning. The goal of the visual analysis is to answer important questions using data and facts. In order to support analysis, it is not enough to only access and report on the data.
Analysis requires computational support throughout the process. Typical steps in the analysis include such operations as
filtering to focus on items of interest
sorting to rank and prioritize
grouping and aggregating to summarize
creating on-the-fly calculations to express numbers in useful ways. A visual analysis application exposes these exploratory operations to ordinary people through easy-to-use interfaces.
Visual analysis means presenting information in ways that support visual thinking. Data is displayed using the best practices of information visualization. The right presentation makes it easy to organize and understand the information.
For example, critical information may be quickly found, and features, trends, and outliers may be easily recognized. One powerful way to evaluate any analysis tool is to test its effectiveness in answering specific questions.
At the most fundamental level, does the tool have the analytical power needed to answer the question?
At another level, how long does it take to answer the question? A successful visual analysis application unites data exploration and data visualization in an easy-to-use application that anyone can use.
When you are designing a class, you need to ensure that the classification of its critical parts is outlined at the beginning. The clearer the initial design, the more performant and scalable the class is. Some of the components in the order in which they should be defined in the class are mentioned as follows. Ideal structure of a class Class variables Constants or default variables are usually defined at the top of the class. For someone who is reading the code, it comes as an easy-to-view consolidated list, and for the interpreter it ensures that all such variables are processed before diving into the main logic of the class, including any other Instance method or constructor. The __init__ method The __init__ method provides information about inputs needed and how to instantiate the class. It is also the constructor of the class, which the very first method called while initializing the class . Special Python methods These methods change the functionality of the class or provide add
Files always have data in them. For different purposes, you need methods to deal with them. These six file methods of use in this case. Related: 5 top file modes in python. Python file methods Below are the top six file methods in python: Tell() Seek() Flush() Fileno() truncate() isatty() 1. tell() The usage of tell method is it returns the cursor-position of the file-pointer from the beginning of the file. It tells the current cursor position. The position starts from zero, which is same as of an index. Syntax: fileobject.tell() 2. seek() The usage of seek method is cursor position, from one position to the specified position from the beginning of the file, it moves. Here, the cursor will be sought to a particular location. Syntax: fileobject.seek(position) 3. flush() The usage of flush method is clean out the internal buffer. Before writing the text in the file, it is best practice to clear out that the internal buffer can be cleared. Syntax: fileobject.flush() 4. fileno() The
TLV format contains three parts Tag, Length, and value. In a credit card or financial transactions, the TLV protocol supports this format. Below, you will find the ideas to decode TLV data quickly. According to IBM , the tag tells what type of data it is. The length field denotes the length of the value. The value-field denotes the actual value. Structure of TLV. TLV comprises three field values. Tag Length Value How to Decode TLV The EMV labs developed tags which in turn part of EMV protocol. Each tag has an unique meaning. And the Tag and Length together takes 1 to 4 bytes of memory. 1. The Best example for TLV. Below is the way to decode the EMV tag. The first part of the TLV format is TAG. The second part is LENGTH, and finally the VALUE. Syntax of EMV tag: [Tag][Value Length][Value] (ex. " 9F40 05 F000F0A001 ") where, Tag Name = 9F40 Value Length (in bytes) = 05 Value (Hex representation of bytes. Example, "F0" – 1-byte) = F000F0A001 Finally, what is 9F40
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