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   In the Introduction to   Data Science  post, we discussed about   Roadmap for Data Science . In which we learned about Pandas in Python. So, lets jump into Pandas introduction. What is Pandas in Python? Introduction to Pandas in Python are given below:- Pandas is a fast, powerful, flexible and easy to use open source Data Analysis and manipulation tool, built with Python Programing. Pandas is Python package that is widely used for Data Science/ Data Analysis and machine learning tasks. It is used for manipulation of 1-D Arrays as well as 2-D arrays.  It is one of the most popular Data Wrangling packages of Python Programming. Key features of Pandas in Python and Why should we learn Pandas? We should learn Pandas because it provides us magnificent Data operations in easy and advanced way. There are some key features of Pandas are given below:- Pandas has Fast and efficient DataFrame with default and customized indexing. Pandas provides us tools for Data Loading from momory and differ

Hello friends!   Codin India   here and in today's post we are going to learn Python's inbuilt functions that is Min Max Nested List So, Let us understand it one by one:-  min():- Python has an inbuilt function min() which finds the minimum value of the given list, tuples or something. It first calculates the biggest number one by one and provides the minimum value of the list. Syntax :- min(array_name) Code :- list1 = [1,2,3,4,5,6] print(min(list1)) Output:- 1 Explanation:-  First we created list that has name list1 and then we created called Python's inbuilt function min() and print it. Let us understand it by code:- max():- Python has an inbuilt function min() which finds the minimum value of the given list, tuples or something. It first calculates the biggest number one by one and provides the minimum value of the list. Syntax:-   max(array_name) Code :- list1 = [1,2,3,4,5,6] print(max(list1)) Output:- 6 Explanation:-  First we created list that has name list1 and then

 Hello! Welcome back to our tutorial. Today we will learn how to create array in tensorflow. What is tensorflow? Tensorflow is open source platform for machine learning. It has comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-art in ML and developing easily build and deploy ML powered applications.   How to import Tensorflow?    import tensorflow as tf import numpy as np  How to create array in tensorflow? We have 2 methods to create array in tensorflow:-  Using tensorflow inbuilt function Using numpy Let us understand it one by one. 1. Using Tensorflow's inbuilt function  We can create array in tensorflow using  tensorflow's inbuilt function i.e. constant arr  = tf.constant([1,2,3,4,5]) Let us understand by code:- What is constant? constant is useful for asserting that the value can be embedded that way. If the argument dtype is not specified, then the type is inferred from the type of value 2. Using Nump

  In the last post, we learned about reshaping the Numpy array. In this post, we will learn about the transpose of nd-array. Another very interesting reshaping method of Numpy is the   Transpose()   method.   Transpose is an very important topic when we talk about matrices and arrays. In linear algebra, the transpose of a matrix is an operator which flips a matrix over its diagonal. i.e.  It takes the input Array and swaps the rows and columns value and vica-versa. After transpose rows becomes columns and columns becomes rows.  Let us understand by code:-   Output:- It will convert rows into columns and columns to rows. I hope you will Like this post :) if you want to learn python then this tutorial will help you alot Python tutorial for beginners in hindi Please Subscribe to our Youtube Channel - Codin India

    Numpy is Python module that is used for array creation, modification and creating sub arrays for numpy arrays. Concatenation of arrays Concatenation or joining of two arrays in Numpy, is primarily accomplished through the routines np.concatenate, np.vstack and np.hstack. Let us see all of the one by one. Concatenate:- It will concatenate two arrays and gives the output as one array. Let us see by code:- From the above code, it is clear that np.concatenate takes two argument as input and adds the value of both array and return the output as one array. Concatenate 3 or more arrays:- we can concatenate as any array we want. Let us talk, where the case of 3 arrays, we will concatenate all the 3 arrays Concatenation of same array:- We can also concatenate same array together. Like we can concatenate x + x. Let's see the Code:- NOTE:-   point here to be noted that, the arguments should be passed in [] brackets only.  np.concatenate([x, y]) 2-D or multidimensional Array Concatenation:

  What is HTTP? HTTP stands for Hyper Text Transfer Protocol. HTML is a protocol which allows the fetching of resources, such as HTML documents. It is foundation of any data exchange on the web. It is client-server protocol which means requests are initiated by the recipient on web servers. It transfers data from one webpage to other web pages and from client side to server side and vice-versa.    What is HTTPS? HTTPS is an advanced version of HTTP. Where "s" in HTTPS stands for secure. It is used for a secure connections between web pages. It is used where there is any type of Data Transfers, transaction etc. You should always protect all of your websites with HTTPS, even if they don't handle sensitive data communications. Aside from providing critical security and data integrity for both your websites and users' personal information, Https is a requirement for many new browser features, particularly those required for progressive web pages. Summary:- Intruders both

   Linked List is a linear data structure. Unlike arrays, linked list elements are not stored at a contiguous location. The element are linked using pointers. Why Linked list is used:- Arrays can be used to store linear data of similar types, but arrays have the following limitations. Array's size is fixed. So we must know the highest limit of the array in advance. So we must declare the size of the array first and elements there after.  Inserting a new element is very expensive because the room has to be be created for the new elements and shift the existing elements. Ex :- Suppose we have arrays in sorted order   i.e. [1,2,3,4,6,7]  and we have to insert new element   i.e. [5]   in the array. So in order to maintain elements in sorted order, we have to place that element after suitable element. In this situation we have to shift the element   i.e. [6,7] by position 1. Now  we saw the arrays limitations. Let's understand the advantages of the Linked List over array.  Advantage

  Data Structure   is a particular way of organizing data in a Computer, so that it can be used effectively. For Example:-   We can store a list of items having the same data-type using arrays. Data structures are fundamental concepts of computer science which helps is writing efficient programs in any language. Python is a high-level, interpreted, interactive and object-oriented scripting language using which we can study the fundamentals of data structure in a simpler way as compared to other programming languages. Types of Data Structure Data structures in computer science are divided into two categories. We will discuss about each of the below data structures in detail one by one. In today's post we will only discuss about data structure definition and its types. We will learn and implement its various types one by one with example. Data Structure Linear Data Structure Non-Linear Data Structure Linear Data Structure A Linear data structure have data elements arranged in sequent