Markdown cell in Jupyter Notebook

Jupyter Notebook(formerly IPython Notebook) is a web-based interactive computational environment for creating Jupyter notebook documents. Markdown is a light weight and popular Markup language which is a writing standard for data scientists and analysts. It is often converted into the corresponding HTML by which the Markdown processor allows it to be easily shared between different …

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Data Types in python:

Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data. Since everything is an object in Python programming, data types are classes and variables are instance (object) of these classes. The variable in Python is used to store …

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Variables in Python:

Variables are nothing but reserved memory locations to store values. This means that when you create a variable you reserve some space in memory. Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to variables, you …

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Get Started with Python Syntax

Python Indentation: The indentation in Python is very important. Indentation refers to the spaces at the beginning of a code line. Where in other programming languages the indentation in code is for readability only, the indentation in Python is very important. Python uses indentation to indicate a block of code. Let’s quickly look into few examples how Python indentation works. Example 1: From the …

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Python Keyboard Shortcuts

If You haven’t Installed or downloaded Anaconda yet, please refer the Below URL to Install Anaconda. After successful Installation , you will Find the Anaconda Command Prompt from the start menu. Open the Anaconda Command Prompt and type jupyter Notebook and Press Enter. Python Workspace will be Opened in the Browser, Minimize this Command Prompt …

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Installation of Python:

Setup & Installation: Anaconda is a distribution of Python, it includes not only python, but many libraries that we are going to use in our posts, as well as its own Virtual environment system. It’s an all-in-one install that is extremely popular in data science and Machine learning. Installation Process: Go to this URL : …

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R Vs Python

This is the Most Trending debut of Aspiring data scientists Here we will try to understand the differences between both programming Language In the battle of data science tools, python and R both have their pros and cons. Selecting one over the other will depend on the use-cases, the cost of learning, and other common …

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Real Time scenario

The World Bank requires scatterplot depicting Life Expectancy (y-axis) and Fertility Rate (x-axis) statistics by Country. The scatterplot needs to also be categorized by Countries’ Regions. we have been supplied with data for 2 years: 1960 and 2013 and we are required to produce a visualization for each of these years. Some data has been …

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Working with Basic Operations and Filtering Dataframes

We will be using the same  dataset used in my previous post (https://sritechstudio.com/demographic-analysis-using-dataframes/) Now let us work on some basic and essential operations in Dataframe Subsetting : Subsetting in R is a useful indexing feature for accessing object elements. It can be used to select and filter variables and observations. You can use brackets to …

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Dataframes in R Language

A data frame is a table or a two-dimensional array-like structure in which each column contains values of one variable and each row contains one set of values from each column. Following are the characteristics of a data frame. The column names should be non-empty. The row names should be unique. The data stored in …

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Subsetting in R:

Subsetting in R is a useful indexing feature for accessing object elements. It can be used to select and filter variables and observations. You can use brackets to select rows and columns from your dataframe. subset () function in R Language is used to create subsets of a Data frame. This can also be used …

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Visualization with Matplot ():

Matplot Function is useful for quickly plotting multiple sets of observations from the same object, particularly from a matrix, on the same graph. It Plots the columns of one matrix against the columns of another (which often is just a vector treated as 1-column matrix). Syntax: Matplot (x, y, type = “p”, lty = 1:5, …

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