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
Markdown cell in Jupyter Notebook Read More »
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 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
Variables in Python: Read More »
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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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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Google Colab is an incredible online browser-based platform that allows us to train our models on machines for free! Sounds too good to be true, but thanks to Google, we can now work with large datasets, build complex models, and even share our work seamlessly with others. That’s the power of Google Colab. Colab is
Accessing Python Through Google Colab: Read More »
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 :
Installation of Python: Read More »
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
R is incredible software for statistics and data science. But while the bits and bytes of software are an essential component of its usefulness, software needs a community to be successful. As we came to Know that R Language is growing rapidly and Extremely used and there are lots of new things happening all the
Few Important Things to know More about R Language: Read More »
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
Real Time scenario Read More »
1.Which function did we use to import a csv file into R? A. write.csv () B.read.csv () C. import.csv () D. read. File () 2. What is the core difference between a data frame and a matrix? A. A Data Frame can have Named rows & columns, but a matrix Cannot B.A Data Frame can
Time for Quiz on Dataframes in R Read More »
As we have seen the data in Plots and Box plot. We have different Plotting shapes available in R Language: If shape given as 0 the data is represented in square plots. If shape given as 2 the data will be represented in triangle shape Now let’s take a small example: We will be using
Visualize the Data by using More advanced Functions: Read More »
First check Packages related to qplot function are installed or not How do we check?🤔🤔 Type? qplot and run this line of code As we can see the information in console pane that No documentation available for qplot in specified packages, so now we are clear that the packages related to qplot function are not
Introduction to a Powerful Function qplot in R Language: Read More »
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
Working with Basic Operations and Filtering Dataframes Read More »
Assume that You are employed as a Data Scientist by the World Bank and you are working on a project to analyze the World’s demographic trends. You are required to produce a scatterplot illustrating Birth Rate and Internet Usage statistics by Country. The scatterplot needs to also be categorized by Countries’ Income Group You have
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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
Dataframes in R Language Read More »
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
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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Scenario: Assume that You are working as a data scientist for a consulting firm E&Y. One of your colleagues from the Auditing department has asked you to help them assess the financial statement of organization. You have been supplied with two vectors of data: monthly revenue and monthly expenses for the financial year. Input: Please
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Can we Name the Rows & Columns in R Matrix? Yes It is possible to name the rows and columns of the matrix during creation with the dimnames argument of the matrix () function Let’s look at this below example: Here I have assigned a Variable my_data to print elements from 1 to 5 and
Naming Dimensions in Matrices/Matrix: Read More »
