Featured Post

Best Practices for Handling Duplicate Elements in Python Lists

-
Image
Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni
Post a Comment

R language five useful real functions

-
In Data Science R language plays a crucial role. In the R language, there are five top functions present. These functions I have explained in this post.
#5-key-points-in-r

1. Storing Values

  • Stores a value to variable. The value can be same or mixed data type.
  • It is available /* */ to give comments for your scripts inside
  • Char, Double, Boolean and Decimal are more frequently used data types

2. Reading data from files

  • Large data objects will usually be read as values from external files rather than entered during an R session at the keyboard. 
  • R input facilities are simple and their requirements are fairly strict and even rather inflexible. There is a clear presumption by the designers of R that you will be able to modify your input files using other tools, such as file editors or Perl1 to fit in with the requirements of R. Generally this is very simple.
  • If variables are to be held mainly in data frames, as we strongly suggest they should be, an entire data frame can be read directly with the read.table() function. 
  • There is also a more primitive input function, scan(), that can be called directly. For more details on importing data into R and also exporting data, see the R Data Import/Export manual.

3. Accessing builtin datasets

  • Around 100 datasets are supplied with R (in package datasets), and others are available in packages (including the recommended packages supplied with R). To see the list of datasets currently available use data().
  • All the datasets supplied with R are available directly by name. However, many packages still use the obsolete convention in which data was also used to load datasets into R, for example data(infert) and this can still be used with the standard packages (as in this example). 
  • In most cases this will load an R object of the same name. However, in a few cases it loads several objects, so see the on-line help for the object to see what to expect.

4. Grouped expressions

  • R is an expression language in the sense that its only command type is a function or expression which returns a result. Even an assignment is an expression whose result is the value assigned,and it may be used wherever any expression may be used; in particular multiple assignments are possible. 
  • Commands may be grouped together in braces, {expr_1; ...; expr_m}, in which case the value of the group is the result of the last expression in the group evaluated. Since such a group is also an expression it may, for example, be itself included in parentheses and used a part of an even larger expression, and so on

5. Writing your own functions

  • R language allows the user to create objects of mode function. These are true R functions that are stored in a special internal form and may be used in further expressions and so on. In the process, the language gains enormously in power,convenience and elegance, and learning to write useful functions is one of the main ways to make your use of R comfortable and productive. 
  • It should be emphasized that most of the functions supplied as part of the R system, such as mean(), var(), postscript() and so on, are themselves written in R and thus do not differ materially from user written functions.

Comments

Post a Comment

Thanks for your message. We will get back you.

Popular posts from this blog

Explained Ideal Structure of Python Class

-
Image
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
Read more

6 Python file Methods Real Usage

-
Image
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
Read more

How to Decode TLV Quickly

-
Image
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
Read more