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You can test your Python skills with Codersarts Quiz.The test is just a nice way to see how much you know, or don't know, about Python. #python #pythonQuiz

Are you looking for Hadoop MapReduce and Spark Assignment Help? Codersarts Hadoop MapReduce and Spark expert offer the best quality Cloud Computing and Big Data Analytics assignment in java and python. Get MapReduce and Spark Assignment Help at an affordable price from the best professional experts Assignment Help. Order now at get 15% off. Introduction about Hadoop Platform? Hadoop is a data management and distributed processing system. It contains many components, including: HDFS is a file system that distributes data across many machines MapReduce for batch parallel computing MapReduce provides: Automatic parallelization and distribution Fault tolerance Input/Output Scheduling Monitoring and Status updates How MapReduce Data programming model works MapReduce has two main tasks: Map, Reduce The data blocks distributed across different machines are processed by Map tasks in parallel. Results are aggregated in Reducers Works only with KEY/VALUE pairs MapReduce Key/Value Pairs The data exchanged between Map and Reduce, and more, in the entire job are pairs (key, value): a key: it is any type of data: integer, text. . . a value: it is any type of data Everything is represented like this. For example : a text file is a set of (line number, line). a weather file is a set of (date and time, temperature) It is this notion that makes programs quite strange to beginners: the two functions Map and Reduce receive and transmit such pairs. MapReduce – Word count example: Pseudo-code: word count Map (Long input_key, String input_values) : foreach word w in input_values: EmitIntermediate (w, ‘1’); Reduce (String key, Iterator intermediate_values): int result=0; foreach v in intermediate_values: result += ParseInt( v ); Emit (key, String( result )); MAPREDUCE Examples Using MapReduce, calculate the sum of the odd and even numbers contained in a Text file: Using MapReduce, calculate the sum of a list of numbers contained in a Text file: Using MapReduce, determine the duplicate elements in a list of numbers contained in a file: Using MapReduce, determine the maximum and minimum of a list of numbers contained in a file: Using MapReduce, determine how many odd and even numbers in a list of numbers contained in a file: Using MapReduce, determine the total number of words in a in a Text file: Contact us for map-reduce assignment help and Solutions by Codersarts experts who can help you mentor and guide foe such MapReduce assignments. If you have project or assignment files, You can send at codersarts@gmail.com  directly

Suppose We have 3 files: 1. mapper.java 2. reducer.java 3.Driver.java So in this case you need to compile all java files as below: javac -cp $(hadoop classpath) *.java

You are going to write a Python program that represents a command line version of a hexadecimal editor. This program will be similar to the Linux built-in command line hexadecimal editors such as xxd and hexdump. The program will first ask the user to enter the name of any file you want to read. Your program will then print the binary contents of the file into the standard output (screen). The output will be divided into three main sections: the offset values in decimal, sixteen space-separated hexadecimal bytes, followed by the same sixteen bytes but in ASCII value. The figure below shows an example of the first 48 bytes of an output, and the three different sections: Notice that in the 2nd section there a space between the 8th and 9th byte. Each output line represents 16 bytes. The first column shows the decimal offset, where the first byte from the first line represents the 0th byte; the second line starts with byte 16th and so on. The final section only shows the printable ASCII characters. These are the ASCII characters can be printed on the screen (usually they are the characters with ASCII values between 0x20 and 0x7EThe rest of the unprintable bytes are replaced by a period ('.'). The following built-in Python functions will be useful in this situation: chr, hex, ord. More information about these functions can be found here: https://docs.python.org/3/library/functions.html Deliverable: Submit your program electronically through D2L. Please hand in the Python program (.py file or.ipynb) Need assignment related help or need other programming help, then you can contact us directly and get help at an affordable price within the due date.

First, open the command prompt and go to the directory in which you want to create a flask app. Here we go to our project directory "C:\Users\Admin\FlaskProjects", and then apply below command to create a virtual environment. Before start first you sure that python 3.X in installed or not if not then installed. Create a directory where you want to project live: C:\Users\Admin\FlaskProjects\mkdir site1 C:\Users\Admin\FlaskProjects\cd site1 Now creating the virtual environment C:\Users\Admin\FlaskProjects\site1\python3 -m venv venv you can create a virtual environment with the following command: C:\Users\Admin\FlaskProjects\site1\virtualenv venv Now you can go to the venv directory and inside the script, you can activate the virtual environment(C:\Users\Admin\FlaskProjects\site1\venv\Scripts) C:\Users\Admin\FlaskProjects\site1\venv\Scripts\activate Press Enter now your virtual environment activated, see below Virtual environment activate (venv) C:\Users\Admin\FlaskProjects\site1\venv\Scripts> After this install the flask (venv) C:\Users\Admin\FlaskProjects\site1\venv\Scripts>pip install flask Now creating a package which name is "app", it uses to execute your project Now go to the app directory and here u create two python files: __init__.py and routes.py __init.py Write below code in this file app/__init__.py: #----------------------- from flask import Flask app = Flask(__name__) from app import routes #----------------------- After this open the “routes.py” file and write below code inside it. #------------------------------------------ app/routes.py: from app importapp @app.route('/') @app.route('/index') def index(): return "Hello, World!" #------------------- After this create another python file “site1.py” where app folder exitst. It used to store application instance with single line code site1.py #-------------- from app importapp #------------------- Here Screenshots of file locations: site1.py: Now come into the Script directory and type below command to run the app: Now go to the Script dir and run below command: (venv) C:\Users\Admin\FlaskProjects\site1\venv\Scripts> set FLASK_APP=site1.py This is used to set the flask app Now run it using below command: (venv) C:\Users\Admin\FlaskProjects\site1\venv\Scripts>flask run *Serving Flask app "site1.py" * Environment: production WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Debug mode: off * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit) Good your app is ready and run. Copy url and paste it into our browser. See below result on the browser: Adding "Templates" files(html, css, etc) Now create “templates” dir where __init__.py and routes.py files Back to the app dir and ceate folder templates (venv) C:\Users\Admin\FlaskProjects\site1\venv\Scripts\app\mkdir templates Creating the index.html file and inside it write below code: app/templates/index.html: #------------------------ Hello, {{ user.username }}! #------------------------- Now edit routes.py file and add below code: #------------------------- from flask importrender_template from app import app @app.route('/') @app.route('/index') def index(): user = {'username': 'naveen'} return render_template('index.html',title='Home', user=user) #-------------------------- To render the template I had to import a function that comes with the Flask framework called render_template(). This function takes a template filename and a variable list of template arguments and returns the same template, but with all the placeholders in it replaced with actual values. The render_template() function invokes the Jinja2 template engine that comes bundled with the Flask framework. Jinja2 substitutes {{ ... }} blocks with the corresponding values, given by the arguments provided in the render_template() call. Template Inheritance In this we use the concept of inheritance, use one template file content in another by using "extend", keyword as per given below: app/templates/base.html: Base template with navigation bar #-------------------------- {% if title %} {% else %} {% endif %} site1: Home {% block content %}{% endblock %} #--------------------------------- Now using base.html content in index.html using below: app/templates/index.html: Inherit from base template #-------------------------- {% extends "base.html" %} {% block content %} Hi, {{ user.username }}! {% for post in posts %} {{post.author.username }} says: {{post.body }} {% endfor %} {% endblock %} #------------------------------- Thanks for reading our flask blog, I hope it may help for creating flask help. If you need any help related to flask projects then contact us.

In this post, we will learn how to draw the line graph using R Studio. # Define the cars vector with 5 values cars <- c(1, 3, 6, 4, 9) # Graph the cars vector with all defaults plot(cars) Output: Now joining the line using: # Define the cars vector with 5 values cars <- c(1, 3, 6, 4, 9) # Graph cars using blue points overlayed by a line plot(cars, type="o", col="blue") # Create a title with a red, bold/italic font title(main="Autos", col.main="red", font.main=4) Output: Drawing multiple lines # Define 2 vectors cars <- c(1, 3, 6, 4, 9) trucks <- c(2, 5, 4, 5, 12) # Graph cars using a y axis that ranges from 0 to 12 plot(cars, type="o", col="blue", ylim=c(0,12)) # Graph trucks with red dashed line and square points lines(trucks, type="o", pch=22, lty=2, col="red") # Create a title with a red, bold/italic font title(main="Autos", col.main="red", font.main=4) Data visualization using the legend # Define 2 vectors cars <- c(1, 3, 6, 4, 9) trucks <- c(2, 5, 4, 5, 12) # Calculate range from 0 to max value of cars and trucks g_range <- range(0, cars, trucks) # Graph autos using y axis that ranges from 0 to max plot(cars, type="o", col="blue", ylim=g_range, axes=FALSE, ann=FALSE) # Make x axis using Mon-Fri labels axis(1, at=1:5, lab=c("Mon","Tue","Wed","Thu","Fri")) # Make y axis with horizontal labels that display ticks at # every 4 marks. 4*0:g_range[2] is equivalent to c(0,4,8,12). axis(2, las=1, at=4*0:g_range[2]) # Create box around plot box() # Graph trucks with red dashed line and square points lines(trucks, type="o", pch=22, lty=2, col="red") # Create a title with a red, bold/italic font title(main="Autos", col.main="red", font.main=4) # Label the x and y axes with dark green text title(xlab="Days", col.lab=rgb(0,0.5,0)) title(ylab="Total", col.lab=rgb(0,0.5,0)) # Create a legend at (1, g_range[2]) that is slightly smaller # (cex) and uses the same line colors and points used by # the actual plots legend(1, g_range[2], c("cars","trucks"), cex=0.8, col=c("blue","red"), pch=21:22, lty=1:2); Output: Thanks for reading if you need any types of data visualization help like pie graph, bar graph, etc, you can contact us at given below link Get your project or assignment completed by R expert and experienced developers and researchers. Submit a proposal OR If you have project files, You can send at codersarts@gmail.com directly

Are you looking for R Programming Assignment Help? Codersarts R Assignment expert offer the best quality help with R assignment, coding or R programming Tutors. Get R Assignment Help at an affordable price from the best professional tutors Assignment Help. Order now at get 15% off. What is R Programming R is a programming language for statistical analysis, graphics representation and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac. R can be used for data mining, statistical computing and modelling, machine learning and even reporting upto some extent. we have team of expert who will help you in R programming assignment and comfortable with R to manage and manipulate data, familiar with some of R's most commonly used statistical procedures, Develop good analytical practices including documenting analysis and data manipulation, and collaborating with others in the R user/learner community. As a beginner, it may be common concern that students don’t know how to start, from where to learn and what topics should be explored. the Codersarts team has a perfect solution for you. We will be covering every topic related to R programming from basic to advanced level and we have something for everyone whether you are a newbie or an expert R programmer. R programming language is good choice for data analysts, data scientists, statisticians utilize to analyze data and perform statistical analysis using graphs and other forms of visualizations. Using R, one can analyze large datasets. It is an ever-expanding programming language with thousands of packages that provide support to a variety of applications. Working on a Project of your own is the best thing you can do to enhance & implement your R Programming skills. Let’s see the good R assignment ideas- Sentiment Analysis- R Project Credit Card Fraud Detection- R Project Uber Data Analysis- R Project - Project in R –Uber Data Analysis Project Census Data Analysis - Gather & analyze census data & predict whether the income exceeds $50K per year. Website/ Web apps - Create powerful website/ web apps that uses all R capabilities. Height & Weight datasets - Predict the height or weight of a person. Identify product bundles from sales data - Finding out product bundle that can be put together on sale. Besides the above mentioned projects in R that we can do; a website /Web app using R in backend using Shiny; deploy cool dashboards for your presentations;Web scrapping tool  using R. R has a excellent support for time series analysis; rstudio assignment help.

What is R Programming? R is a very flexible and powerful programming language, as well as a package that is written using that language (and others like C). R- Programming is a language and environment developed by Bell Laboratories (popularly known as AT&T) for statistical computing and graphics. List of topics which we have covered in this blog are: Random variables: definition, programming examples in R Bayesian statistics Mayor continuous and discrete probability distribution functions (PDF): normal (Gaussian), uniform, exponential, Pascal, binomial, etc; cumulative distribution (density) function (CDF) Linear univariate and multivariate regression and modeling Frequentist and Bayesian inference: p-values and confidence intervals Model selection; information criterionsNon-parametric statistics Statistical tests, such as ANOVA, Student's t-test, F-test, Chi-square test Analysis of variance Exploratory Data Analysis (EDA) High-dimensional data analysis (Singular value decomposition (SVD), Principal component analysis (PCA)) Data visualization techniques Basic Machine Learning concepts Other Sub-Topics for R Programming Assignment Robust regression Logistic regression Exact logistic regression Multinomial logistic regression Ordinal logistic regression Probit regression Poisson regression Negative binomial regression Zero-inflated Poisson regression Zero-inflated negative binomial regression Zero-truncated Poisson Zero-truncated negative binomial Censored and truncated regression To bit regression Truncated regression R Libraries in which is our team have an expertise tidyverse (general R library including some of the libraries below) ggplot2 dplyr tidyr readr purrr tibble stringr plotly (interactive graphs) stargazer (beautiful regression tables) R Markdown Reason for which you can take our services 100% Confidential Money-Back Guarantee On-Time Delivery 5+ year experienced team A+ Quality Assignments 10000+ Assignment Experts Get your project or assignment completed by Deep learning expert and experienced developers and researchers. Submit a proposal OR If you have project files, You can send at codersarts@gmail.com directly

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