Getting Better with Knowledge

Arrays are fundamental part of most programming languages. It is the collection of elements of a single data type, eg. array of  int , array of  string . However, in Python, there is no native array data structure. So, we use Python lists instead of an array. Note:  If you want to create real arrays in Python, you need to use NumPy's array data structure. For mathematical problems, NumPy Array is more efficient. Unlike arrays, a single list can store elements of any data type and does everything an array does. We can store an integer, a float and a string inside the same list. So, it is more flexible to work with. [10, 20, 30, 40, 50 ]  is an example of what an array would look like in Python, but it is actually a list. Create an Array We can create a Python array with comma separated elements between  square brackets[] . Example 1: How to create an array in Python? We can make an integer array and store it to ...

Although we don’t have to declare type for python variables, a value does have a type. This information is vital to the interpreter. Python supports the following Python data types. a. Numbers There are four numeric Python data types. 1. int – int stands for integer. This Python Data Type holds signed integers. We can use the type() function to find which class it belongs to. > > > a = - 7 > > > type ( a ) <class ‘int’> An integer can be of any length, with the only limitation being the available memory. > > > a = 9999999999999999999999999999999 > > > type ( a ) <class ‘int’> 2. float – This Python Data Type holds floating point real values. An int can only store the number 3, but float can store 3.25 if you want. > > > a = 3. 0 > > > type ( a ) < class 'float' > 3. long  – This Python Data Types holds a long integer of unlimited length. But this c...