Overview of the Quantmod R package to retrieve stock data and display charts. Video cover basic commands in the Quantmod package that can be used to pull financial data and then display it on charts along with technical indicators and other charting parameters to filter for the data and change the charting theme
Views: 23498 Melvin L
See how easy it is to download, visualize and manipulate daily stock market data and how to use it to build a complex market model. Code and walkthrough: http://amunategui.github.io/wallstreet/ Note: for those that can't use XGBoost - I added an alternative script using GBM in the walkthrough: http://amunategui.github.io/wallstreet/ Top of the page under resources look for link: "Alternative GBM Source Code - for those that can't use xgboost" MORE: Signup for my newsletter and more: http://www.viralml.com Connect on Twitter: https://twitter.com/amunategui My books on Amazon: The Little Book of Fundamental Indicators: Hands-On Market Analysis with Python: Find Your Market Bearings with Python, Jupyter Notebooks, and Freely Available Data: https://amzn.to/2DERG3d Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud: https://amzn.to/2PV3GCV Grow Your Web Brand, Visibility & Traffic Organically: 5 Years of amunategui.github.Io and the Lessons I Learned from Growing My Online Community from the Ground Up: Fringe Tactics - Finding Motivation in Unusual Places: Alternative Ways of Coaxing Motivation Using Raw Inspiration, Fear, and In-Your-Face Logic https://amzn.to/2DYWQas Create Income Streams with Online Classes: Design Classes That Generate Long-Term Revenue: https://amzn.to/2VToEHK Defense Against The Dark Digital Attacks: How to Protect Your Identity and Workflow in 2019: https://amzn.to/2Jw1AYS CATEGORY:DataScience HASCODE:True
Views: 44380 Manuel Amunategui
Learn Financial Programming and Timeseries Analysis Basics in R and R Studio Not enough for you? Want to learn more R? Our friends over at DataCamp will whip you into shape real quick if you need help: https://www.datacamp.com/courses/free-introduction-to-r?tap_a=5644-dce66f&tap_s=84932-063f71 Or if you're more of a Python guy, we have an intro to finance for Python course live on DataCamp right now: https://www.datacamp.com/courses/introduction-to-portfolio-analysis-in-r?tap_a=5644-dce66f&tap_s=84932-063f71 Join the Quants by taking our Quant Course at http://quantcourse.com 1) Basics of R Programming / Downloading R 2) Using Data Frames 3) An Intro to the Quantmod Package 4) Reading in Financial Data from Quantmod 5) Using Vectors in R 6) Reading and Writing Data as CSV Files 7) Plotting Timeseries Data in R 8) Working with Split / Dividend Adjusted Data 9) Calculating Log Returns 10) Converting Log Returns to Arithmetic and Vice-Versa 11) Apply Function in R / Working With Multivariate Data 12) Intro to the Performance Analytics Package 13) XTS and Zoo Objects for Financial Data 14) Chart the Cumulative Return of an Asset 15) Chart the Drawdown and Daily Returns of an Asset 16) Charting Multiple Assets at Once in R 17) Merging Different Datasets With Different Indexes 18) Calculating Sharpe Ratios and other Performance Metrics
Views: 27681 QuantCourse
We use the Quandl Package which allows us to use a vast collection of datasets. We look at the average global temperature dataset, which we plot and perform a regression on using the inbuilt standard commands. This is the most basic model fit command we have but a good place to start. We will get to using time series to study financial data in a matter of weeks!
Views: 790 Quant Channel
http://bit.ly/1is7pzM Nelson, a supervisor out of Tampa, FL describes his experience with the Ultimate Traders Package and the Wealth and Freedom Experience LIVE. He touches on how the fibonacci sequence was a real eye opener and that the psychological aspects of trading were brought to light and helped him understand trading even better. He also discusses Analyst on Demand and how their alerts and assistance has allowed him to make pip gains while he is learning. At the time of recording Nelson's trading account had grown 200%. To see more student success stories and learn more about Market Traders Institute, click here: http://bit.ly/1is7pzM
Views: 881 Market Traders Institute
Google Tech Talk October 22, 2010 Presented by Dirk Eddelbuettel and Romain Francois. ABSTRACT The R Intergrouplet has invited long-time R contributors Dirk and Romain to give a joint tech talk about some of the recent developments on their open-source R packages. The Rcpp package provides a consistent C++ class hierarchy that maps various types of R objects to dedicated C++ classes. Object interchange between R and C++ is managed by simple, flexible, and extensible concepts which include broad support for popular C++ idioms from the Standard Template Library. RInside is used to embed R in C++ applications, and RProtobuf is the Protocol Buffers API for R.
Views: 25564 GoogleTechTalks
This tutorial is on openair package in R which is developed for air pollution data analysis. It provides many interesting visualization functions. In the tutorial we will explore following functions - summaryPlot, scatterPlot, timeVariation, trendLevel, smoothTrend, calendarPlot, windRose, polarPlot, pollutionRose, polarAnnulus, importKCL and importTraj, trajPlot, selectByDate and timeAverage. This tutorial is for those who know basics of R. Openair Project Description - The openair project was a Natural Environment Research Council (NERC) knowledge exchange project that aimed to provide a collection of open-source tools for the analysis of air pollution data. The project was also supported by Defra. The project was led by the Environmental Research Group at King's College London, supported by the University of Leeds and is now hosted at: http://davidcarslaw.github.io/openair/ openair package citation - Carslaw, D. C. and K. Ropkins, (2012) openair --- an R package for air quality data analysis. Environmental Modelling & Software. Volume 27-28, 52-61. Links - 1. openair project website - www.openair-project.org 2. github repo - http://davidcarslaw.github.io/openair/ 3. openair manual - http://www.openair-project.org/PDF/OpenAir_Manual.pdf 4. importKCL Description - https://davidcarslaw.github.io/openair/reference/importKCL.html Thanks to openair project researchers and developers for providing wonderful open source tool for air pollution data analysis.
Views: 534 Environment Statistics
Asset returns based on low frequency prices (e.g. end-of-day quotes) are still dominating modern portfolio analysis. To make portfolio metrics more relevant intraday and improve precision of estimates, new data frequency needs to be explored. In this presentation we demonstrate how using high frequency market data for portfolio risk management and optimization could improve the classic variance-bias trade-off and bring new insights to strategy backtesting. We illustrate our examples using PortfolioEffectHFT package for R statistical software. Since high frequency prices require special handling, we discuss key components of a model pipeline for microstruture noise, price jumps, outliers, fat tails and long-memory. We conclude our presentation with an introduction to high frequency portfolio optimization built on top of intraday portfolio metrics. Stephanie Toper is a director of portfolio analytics at PortfolioEffect. Stephanie spent 8 years as a quantitative developer at Karya Capital, UBS and Societe Generale and was a senior risk analyst at MF Global. She has extensive experience in interest rate derivatives and quantitative library development. She holds a Master’s degree in Mathematics of Finance from Columbia University and a Master’s in Applied Mathematics and Computer Science from ENSIMAG, France.
Views: 1222 NYC Data Science Academy
quantmod is a package within R which adds functionality for finance. We take a quick look at it here before we go more deeply into it over the next while. We want to look for patterns, to guide out algorithm design and improve our trading for example?
Views: 1437 Quant Channel
Modern microbiome research is producing datasets that are difficult to manipulate and visualize due to the hierarchical nature of taxonomic classifications. The “taxa” package provides a set of classes for the storage and manipulation of taxonomic data. Classes range from simple building blocks to project-level objects storing multiple user-defined datasets mapped to a taxonomy. It includes parsers that can read in taxonomic information in nearly any form. It also provides functions modeled after dplyr for manipulating a taxonomy and associated datasets such that hierarchical relationships between taxa as well as mappings between taxa and data are preserved. We hope taxa will provide a basis for an ecosystem of compatible packages. We have also developed the metacoder package for visualizing hierarchical data. Metacoder implements a novel visualization called heat trees that use the color and size of nodes and edges on a taxonomic tree to quantitatively depict up to 4 statistics. This allows for rapid exploration of data and information-dense, publication-quality graphics. This is an alternative to the stacked barcharts typically used in microbiome research.
Views: 539 R Consortium
Presenter: Rory Winston Venue: Deloitte, Melbourne Slides for talk: http://www.slideshare.net/rorywinston/creating-r-packages Original meetup page: http://www.meetup.com/MelbURN-Melbourne-Users-of-R-Network/events/16172691/ Walk through creating an R package from scratch - setting up the package skeleton, adding functions and data, and creating package documentation. If time permits, show an example of using C/C++ to interface the package with a 3rd party library. About the presenter: Rory Winston did an MSc in Applied Computing in Galway in Ireland. Set up and ran a training and consulting company before moving to London in 2001. Worked in the telecomms and finance sectors in London for 10 years, obtained an Masters in Finance from London Business School in 2007. Since 2005 Rory has worked as a consultant in the financial sector building real-time trading systems. Moved to Oz in Jan 2010 and work in one of the big 4 banks doing software development on foreign exchange trading systems.
Views: 4991 Jeromy Anglim
Thank you so much lps rainy days! I love the LPS and hope you enjoy your lps too! Anyways, hope you guys enjoyed this video and if you did, make sure to leave a like, subscribe and hit the bell, and comment if you want more videos like this! I'll see you in my next video!~Moon✧
Views: 872 lpsmoonstone126
http://goo.gl/w1h145 Ray, a bartender out of Rochester, New York describes his experience with the Ultimate Traders Package on Demand and the Wealth and Freedom Experience LIVE. Ray talks about how he got started trading penny stocks and his journey from options to the Forex. He describes how the UTP and the Wealth and Freedom Experience LIVE helped him go from a gambling, "novice" mentality to one of proper equity management and a serious trader. To see more student success stories and learn more about Market Traders Institute, click here: http://goo.gl/w1h145
Views: 662 Market Traders Institute
Using quantmod package in R to retrieve Financial Time Series data from Yahoo and Google Finance
Views: 1477 Chuc Nguyen Van
Cette vidéo vous permettra de voir comment concevoir de A à Z un package R dans les règles de l'art.Un article détaillé accompagne cette vidéo : https://thinkr.fr/creer-package-r-quelques-minutes/ Bonne vidéo.
Views: 752 ThinkR Rstats
A pythonic tour of Facebook's time series package. Intermediate level with basic statistics and time data familiarity required. Jonathan Balaban is a senior data scientist, strategy consultant, and entrepreneur with ten years of private, public, and philanthropic experience. He currently teaches business professionals and leaders the art of impact-focused, practical data science at Metis. Founded in 2003, Chicago Python User Group is one of the world's most active programming language special interest groups with over 1,000 active members and many more prestigious alumni. Our main focus is the Python Programming Language. ~~ Connect with us! ~~ chipymentor.org @ChicagoPython chipy.slack.com chipy.org
Views: 12720 ChiPy - Chicago Python Users Group
http://www.Cppcon.org — Presentation Slides, PDFs, Source Code and other presenter materials are available at: https://github.com/cppcon/cppcon2015 — R is an open-source statistical language designed with a focus on data analysis. While its historical roots are in statistical applications, it is currently experiencing a rapid growth in popularity in all fields where data matters: from data science, through bioinformatics and finance, to machine learning. Key strengths contributing to this growth include its rich libraries ecosystem (over 6 thousands packages at the moment of writing) – often authored by the leading researchers in the field, providing early access to the latest techniques; beautiful, high-quality visualizations – supporting seamless exploratory data analysis and producing stunning presentations; all of this available in an interactive environment resulting in high productivity through fast iteration times. At the same time, there are no free lunches in programming: the dynamic, interactive nature of R does have its costs, including a significant impact on run-time performance. In an era of growing data sizes and increasingly realistic models this concern is only becoming more important. In this talk we provide an introduction to Rcpp – a library allowing smooth integration of R with C++, combining the productivity benefits of R for data science together with the performance of C++. First released in 2005, today it’s the most popular language extension for R -- used by over 400 packages. We'll also discuss challenges (as well as possible solutions) involved in integrating modern C++ code, and demonstrate the usage of popular C++ libraries in practice. We’ll conclude the talk with the RInside package allowing to embed R in C++. — Matt P. Dziubinski is an Assistant Professor at the Department of Mathematical Sciences, Aalborg University, Denmark and a Junior Fellow at Center for Research in Econometric Analysis of Time Series (CREATES). His fascination with computers started in the late 1980s with an 8-bit Atari. His current research interests include Quantitative Finance and High Performance Scientific Computing, with a focus on applied cross-platform parallel computing -- targeting multi-core CPUs as well as many-core GPGPUs. Practical implementation of these research ideas is made easier, more accessible, and even fun thanks to modern C++. Since 2008 Matt has also been sharing his passion introducing modern C++ to his students -- with computational applications in math, finance, statistics, and economics. C++ interests include generic programming, numerics, networking, and performance optimization -- while also enjoying learning about computer architecture in his spare time :-) — Videos Filmed & Edited by Bash Films: http://www.BashFilms.com
Views: 6384 CppCon
How to purchase a trading package in Omnia, and how to set up your trading account and make a deposit. Omnia Trading has an exclusive algorithm which has been producing an average 10% to 15% profit each month. Register with Omnia here: https://omniatek.com/r/25908 Send an email to me here: [email protected] Connect with me on Facebook (send me a message) here:https://www.facebook.com/realkarenrobinson Get your own crypto wallet here: https://www.coinbase.com/join/57cfe40b2a6e94008244408b
Views: 465 Karen Robinson
Simple example of using R to extract structured content from web pages. There are several options and libraries that can be considered. if your webpage has data in HTML tables you can use readHTMLTable however in this example the web pages doesnt use HTML tables so we use a straightforward XPath technique to extract page content. We will in the end turn content from web pages into a data frame in R
Views: 39017 Melvin L
Archaeologists often wish to plot the chronological frequency distribution of a given entity – for example a feature category, a plant or animal species, or an artefact type – within a specific site or region. Since each archaeological occurrence is subject to chronological uncertainty, and since dating resolution varies widely, estimating a single distribution from numerous occurences is a non-trivial task. This is particularly problematic where data are combined from multiple sites or interventions with a wide range of different chronological break points and sources of dating information - for example sites with a long history of excavation, or urban areas with complex stratigraphy and a high concentration of development-led archaeology. Researchers are often forced to fall back on a lowest-common-denominator approach, trading resolution for comparability by combining data into broad period categories. This paper presents an R package for dealing with this situation without surrendering the original dating resolution. Designed originally for meta-analysis of zooarchaeological remains from numerous historical-period sites across London (used here as a case study), archSeries is built around functions for estimating frequency distributions using either (a) aoristic analysis or (b) simulation. Initially based upon uniform probability distributions within archaeologically defined limits, the simulation approach is currently being expanded to allow integration of archaeological chronologies with radiocarbon dates. The package also features a variety of functions for plotting the resulting frequency distributions along with their associated uncertainty. Finally, there is a tool for adjusting results according to the chronological distribution of research intensity. With raw, context-level archaeological datasets increasingly being made publicly available, it is hoped that archSeries will facilitate transparent re-use and meta-analysis of frequency data while allowing researchers to retain the full available chronological resolution. Author – Dr. Orton, David, University of York, York, United Kingdom (Presenting author)
Views: 112 Recording Archaeology
Views: 1061 Bryan Downing
Which is your algo trading preference non programming or langiages like R or Python Which is it? Your choices https://www.dukascopy.com/swiss/english/forex/Visual/features/ https://www.r-project.org https://www.python.org Let me know via my Facebook groups or page: https://www.facebook.com/quantlabsnet/ https://www.facebook.com/groups/quantlabsnet/ Or get to no more product or courses http://quantlabs.net/blog/2018/05/algro-trading-preference-non-programming-langiages-like-r-python/
Views: 62 Bryan Downing
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Views: 35 XTRADECHAIN INCORPORATION
Mining Difficulty Simplified Please refer back to the person that shared with you this video. Any questions? http://facebook.com/nguyen.b.toan Want to become a customer? Create a free account - https://omniatek.com/r/114057 Want to join the team and get personal coaching from us? Here are the steps! 1. Create a free account - https://omniatek.com/r/114057 2. Purchase your trading package 3. Contact us via facebook and introduce yourself. We will setup a game plan for you to grow your business and achieve your financial goals!
Views: 107 TOAN NGUYEN
Omnia has EXCLUSIVE use of an amazing algorithm for trading BTC/USD, with plans to add many new coins. The return for the last 8-9 months has been 10%-15% per month. Watch this zoom meeting with the trader, the Founder, and CEO giving very exciting information about this new addition to Omnia- The Future of Blockchain Technology Register for Omnia here: https://omniatek.com/r/25908 Send me an email here: [email protected] Connect with me on Facebook (please send me a message)https://www.facebook.com/realkarenrobinson Get your own crypto wallet here: https://www.coinbase.com/join/57cfe40b2a6e94008244408b
Views: 67 Karen Robinson
Nothing in this video is financial advice or intended to be. Take your own risks in life and only invest your gambling money. Crypto and investing is risky - risks can lead to huge profits. The more we know the better we will do. If you would like to help support the channel please consider using the links below if you are going to participate any of these services. Thanks for watching!! If you have any questions please leave a comment or message me directly as I am happy to help. I enjoy it. Happy investing! https://tessline.com/en/checkin?upliner=37788205 Novachain - Trading Bot Platform https://novachain.cc/register?ref=CAXB External Exchange listing Nova P2PB2B https://p2pb2b.io/referral/7441c28d-6a09-4230-905c-b2b5f03dd8d0 Arbitraging https://www.arbitraging.co/platform/register/affiliate/QVtIEwCg Crystal Token - Trading Bot Platform https://www.crystaltoken.co/register/CryptoMusic Arbistar- Best new service is the Arbistar Community Bot http://app.arbistar.com/signup/K4OGCXH3VC Weenzee -About 1% a day https://weenzee.com/WR1780A6C0E Napston - Stable Passive Income from traders 1% On trading days https://www.napston.com/?ref=N725917 Crest Token -post- Investment plans coming soon https://cresttoken.com/?ref=96waez32 EliteFinFX 0.5% A Day from forex traders - https://elitefinfx.com/?ref=E6380077 Tessline- Investments 1.6% a day for 30 Working Days https://tessline.com/en/checkin?upliner=37788205 Bitaeon- 3% a day HYIP https://www.bitaeon.io/r/cryptomusic PayOutPro- Variable reliable income https://payoutpro.net/register.aspx?u=8659 MASTERNODE/STAKING Platforms Midas Investments https://midas.investments/?p=cryptomusic Simple POS - Masternodes and Pooled Staking https://simplepospool.com/?ref=CryptoMusic Snode https://app.snode.co/signup?ref=8c1gfp StakeCube https://stakecube.net/?team=CryptoMusic Cryptohashtank https://www.cryptohashtank.com/ZVNK My favorite bot trading and marketing platform Bots working on your Exchange nor Broker Zukul https://zukul.com/xref/CryptoMusic Passive income crypto trading arbitraging home business money on line stay at home hyip
Views: 980 Crypto Music
Hope you enjoyed this video!! Make sure to like, comment, subscribe if your not already! And also turn on post notifications so you know when I upload!💗 Also follow my social medias down below! https://www.instagram.com/pancake.shopkins/ https://www.instagram.com/pancaketoyreviews/ Snapchat: pancake.shopkins Also go check out Sydney's social medias! https://www.instagram.com/shopkinsfan/ • Also go check out my last video if you haven't already! https://youtu.be/2lxQOoy_GFE Bye guys!💕 • • • What are shopkins? Shopkins are cute rubber toys that's are fun to collect! You can get five seasons! Ans also get them in lots of stores like:Target, Walmart, toys r us, and even five below! You can get them in five packs, two packs, twelve packs, and even singer packs! There are over 148 shopkins in about each season! Because once you shop, you can't stop! • • • A little bit about myself😄 I started collecting shopkins in the 2014 Summer! I got my very first season one give pack at toys r us I was inspired to buy them because I was watching Chad Alan and it made me want to buy some! Since then I collected like crazy! I currently have my own Instagram where I take my time to post for you guys! I started my YouTube account sometime in August😊 I have so much fun filming and editing for you guys😘 Have a nice day💗💗 Check ya later❤️👟 Disclaimer: I do not own this music! And video intro is made by my brother His company is https://youtu.be/WSdEp6ubGiw Go check him out!✨ • • • If you have any questions on a product I review on my channel then fill free to leave a comment down below! - [ ] And I will answer as soon as I can
Views: 44 Gabslife
Got in two packages recently. One all the way from Korea and another from more nearby from Jonny R! Jonny, thanks so much for the awesome card!
Views: 1202 kg sportscards
2017 Topps Wacky Packages 50th Anniversary Trading Card Stickers (Hobby Collector) delivers (1) HIT from the following: Artist Autographs, Printing Plates, Sketch Cards, Shaped Sketch Cards, Double Artist Panoramic Sketch Cards, Medallion Cards and (48) Parallels in Every Hobby Collector Box! For more details, please visit, www.GoGTS.net
Views: 1583 GTS Sports&Entertainment
Data wrangling is too often the most time-consuming part of data science and applied statistics. Two tidyverse packages, tidyr and dplyr, help make data manipulation tasks easier. Keep your code clean and clear and reduce the cognitive load required for common but often complex data science tasks. http://tidyr.tidyverse.org/reference/ - http://tidyr.tidyverse.org/reference/gather - http://tidyr.tidyverse.org/reference/spread - http://tidyr.tidyverse.org/reference/unite - http://tidyr.tidyverse.org/reference/separate ---------------- Pt. 1: What is data wrangling? Intro, Motivation, Outline, Setup https://youtu.be/jOd65mR1zfw - /01:44 Intro and what’s covered Ground Rules - /02:40 What’s a tibble - /04:50 Use View - /05:25 The Pipe operator: - /07:20 What do I mean by data wrangling? Pt. 2: Tidy Data and tidyr https://youtu.be/1ELALQlO-yM - 00:48 Goal 1 Making your data suitable for R - 01:40 `tidyr` “Tidy” Data introduced and motivated - 08:10 `tidyr::gather` - 12:30 `tidyr::spread` - 15:23 `tidyr::unite` - 15:23 `tidyr::separate` Pt. 3: Data manipulation tools: `dplyr` https://youtu.be/Zc_ufg4uW4U - 00.40 setup - /02:00 `dplyr::select` - /03:40 `dplyr::filter` - /05:05 `dplyr::mutate` - /07:05 `dplyr::summarise` - /08:30 `dplyr::arrange` - /09:55 Combining these tools with the pipe (Setup for the Grammar of Data Manipulation) - /11:45 `dplyr::group_by` - /15:00 `dplyr::group_by` Pt. 4: Working with Two Datasets: Binds, Set Operations, and Joins https://youtu.be/AuBgYDCg1Cg Combining two datasets together - /00.42 `dplyr::bind_cols` - /01:27 `dplyr::bind_rows` - /01:42 Set operations `dplyr::union`, `dplyr::intersect`, `dplyr::set_diff` - /02:15 joining data `dplyr::left_join`, `dplyr::inner_join`, `dplyr::right_join`, `dplyr::full_join`, ______________________________________________________________ Cheatsheets: https://www.rstudio.com/resources/cheatsheets/ Documentation: `tidyr` docs: tidyr.tidyverse.org/reference/ - `tidyr` vignette: https://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html `dplyr` docs: http://dplyr.tidyverse.org/reference/ - `dplyr` one-table vignette: https://cran.r-project.org/web/packages/dplyr/vignettes/dplyr.html - `dplyr` two-table (join operations) vignette: https://cran.r-project.org/web/packages/dplyr/vignettes/two-table.html ______________________________________________________________
Views: 8626 RStudio
COMING SOON! Email Chad: craigs1669 @ gmail dot com / +1 773- 829 -0737 It is important to understand that in an affiliate plan that offers a crypto trading package, the money that comes in can go towards trading or towards operations and commissions; however, the same money can’t go into both. We understand this with Eyeline Trading and want to be as transparent as possible. 50% of all trading packages go towards operations and commissions, and 50% goes directly into your trading account! BTC Trading Packages: You make up to .66% per day of all the money that goes into your trading account for 365 days. After the 365 days, your package expires, and you get your original balance back plus all the profits you have earned for 365 days. Example on a $40 package (approximately .00555 BTC), $20 (approximately .00275 BTC) goes towards the trading package and $20 (approximately .00275 BTC) goes towards operations and commissions. So once your package starts paying out, you would earn approximately 13 cents per day for 365 days or approximately $48 (approximately .0066 BTC). And then at the end of the contract, you would also get your $20 that was in your trading account back for a total of $68 (approximately .009 BTC). (NOTE: In this example, I am using dollars; this would actually be in BTC as we do not take payment in dollars, or payout in dollars. This was just to try to make it as easy as possible to understand. If BTC goes down, your profits would be less. And if BTC goes up your profits would be more.) Bitcoin Bot Alt Coin Daytrading Cryptocurrency daytrade day Gunbot Haasbot Cryptotrader Cryptohopper Zenbot crypto exchange crypto bot python review results free open source gekko tutorial java binance trading bot Stocks arbitrage cryptocurrency trader bitcoin core litecoin core electrum bitcoin-qt litecoin-qt coinone Automated Cryptocurrency Exchange Trading Bot Poloniex Bitfinex GDAX Bittrex HitBTC BitStamp YoBit CEX.IO Cryptopia Livecoin Liqui C-CEX Kraken OKCoin Consecure Coinbase Blockchain Block Blocks TuxExchange Vaultoro Bter arbitrage mycelium coinomi bitcoinwisdom LocalBitcoins CampBX Vircurex coindesk bitpay btcchina BTCC wex.nz Gemini bitX lakeBTC meXBT zaif bx.in.th bitcoin.co.id debug API bitcoin litecoin altcoin exchange bot crypto trading bot trading software Litecoin Market btc bitcoins trade trading forex coins litecoins hash miners xbt wallet tumbler cryptography automatic doge 2017 opensource private key public key secret bip38 bip0038 seed stealth addresses bitcoin cash BCH free pgp paypal 2 factor two factor 2FA indicator charts candlestick alarm investment Huobi marginal average analysis stop-loss finance bank fiat windows exchange bot crptography dogecoin USD EUR RUB key ftp gmail reddit /r/bitcoin two qt currency Trader Bot Client simple curent price barter market bitcoin litecoin ppc btc trade bot cryptocurrency wallet blockchain bitcointalk litecointalk money privkey stocks currency RUB EUR USD FTC LTC Trader Automatic ford chevrolet Miner simple e-commerce lag time volume TRC proxy sha256 scrypt private key Mt youtube PP Coin Easy email commerce CNC stratum opensource open source platform Stock Business darkwallet dark wallet mining cold storage indicators short long high frequency trilateration macd bit millibit chart college Double Block scypt multisig coinjoin banking portfolio "free bitcoin" pool dark trustless decentralized privacy NYSE Trader Bot trade bot 2018 Kucoin Binance new
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Learn how to use the ggplot2 library in R to plot nice-looking graphs and find out how to customize them in this step-by-step guide. Downloadable data is available to use with this tutorial at https://deltadna.com/blog/plotting-in-r-tutorial/ as is a written version. Please note that the data source has now changed from 'demo-co.deltacrunch' to 'demo-account.demo-game' & all login details have been changed. Loading in the data 01:10 Working with times using lubridate 03:05 Your first ggplot 05:58 Different geoms 08:37 Fixed variables and aesthetics 09:05 Faceting 11:44 Histograms 13:00 Converting a variable into a factor and accessing help 14:05 Bar graphs 16:05 Stacked bar graphs 17:07 Grouped bar graphs 18:34 Proportion bar graphs 20:06 Basic heatplot 21:30 Advanced heatplot, including labels, new colours and text 25:54
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