Jupyter notebooks for analysis of US federal debt, tax revenues, GDP, budget deficit, evolution of yields on treasury borrowings, treasury yield curves and inflation expectations, unemployment and participation rates, quantitative easing, industrial production, personal consumption and savings, stock market. Using APIs from FRED and Yahoo-Finance.

Best free, open-source datasets for data science and machine learning projects. Top government data including census, economic, financial, agricultural, image datasets, labeled and unlabeled, autonomous car datasets, and much more. Data.gov NOAA - https://www.ncdc.noaa.gov/cdo-web/ atmospheric, ocean Bureau of Labor Statistics - https://www.bls.gov/data/ employment, inflation US Census Data - https://www.census.gov/data.html demographics, income, geo, time series Bureau of Economic Analysis - http://www.bea.gov/data/gdp/gross-dom... GDP, corporate profits, savings rates Federal Reserve - https://fred.stlouisfed.org/ curency, interest rates, payroll Quandl - https://www.quandl.com/ financial and economic Data.gov.uk UK Dataservice - https://www.ukdataservice.ac.uk Census data and much more WorldBank - https://datacatalog.worldbank.org census, demographics, geographic, health, income, GDP IMF - https://www.imf.org/en/Data economic, currency, finance, commodities, time series OpenData.go.ke Kenya govt data on agriculture, education, water, health, finance, … https://data.world/ Open Data for Africa - http://dataportal.opendataforafrica.org/ agriculture, energy, environment, industry, … Kaggle - https://www.kaggle.com/datasets A huge variety of different datasets Amazon Reviews - https://snap.stanford.edu/data/web-Am... 35M product reviews from 6.6M users GroupLens - https://grouplens.org/datasets/moviel... 20M movie ratings Yelp Reviews - https://www.yelp.com/dataset 6.7M reviews, pictures, businesses IMDB Reviews - http://ai.stanford.edu/~amaas/data/se... 25k Movie reviews Twitter Sentiment 140 - http://help.sentiment140.com/for-stud... 160k Tweets Airbnb - http://insideairbnb.com/get-the-data.... A TON of data by geo UCI ML Datasets - http://mlr.cs.umass.edu/ml/ iris, wine, abalone, heart disease, poker hands, …. Enron Email dataset - http://www.cs.cmu.edu/~enron/ 500k emails from 150 people From 2001 energy scandal. See the movie: The Smartest Guys in the Room. Spambase - https://archive.ics.uci.edu/ml/datase... Emails Jeopardy Questions - https://www.reddit.com/r/datasets/com... 200k Questions and answers in json Gutenberg Ebooks - http://www.gutenberg.org/wiki/Gutenbe... Large collection of books

The project focused on the use of public data to assess the economic situation in the country based on the state of the stock market and national means of payment, in particular - of the national currency. As sources are used: Open data Ministry of Finance of the Russian Federation These Moscow Exchange Google Finance Data Technologies used: Backend: Databases (relational) - Microsoft SQL Server 2014 Databases (multivariate) models DataMining, OLAP-cube - Microsoft Analysis Services 12.0 Веб-сервер - Windows Server 2012 / Internet Information Services Самописный ASP.NET HTTP Restful интерфейс для взаимодействия с Frontend ETL (загрузка и пре-процессинг данных, управление обновлением данных) SQL Server Integration Services 2014 (разработка в Visual Studio 2013, SSDT) Frontend: AngularJS ChartJS Twitter Bootstrap These were chosen so that the detail (granularity) in the set is not less than 1 day. The result has been created and filled with data analytic repository (Kimball model, topology - star), which was used to build a multi-dimensional databases and OLAP-based cubes on it, as well as models of analysis of data on two main algorithms: Microsoft Time Series, Microsoft Neural Network . To ensure interoperability frontend and backend server for backend-server was set up HTTP-Restful interface JSON-issuing documents in the form of finished sets. The project includes two main areas: Intelligent visualization of open data Analysis of open data and the construction of forecasts based on them Intelligent visualization involves the use of MDX-queries to the OLAP-cube, followed by depression (drilldown) in the data, the system allows the user to quickly find the "weak points" of the economy, as part of the data collected. To predict the time a standard mix of algorithms ARTXP / ARIMA, without the use of queries involving cross-prediction (but it is possible to enroll in the system correct data). These algorithms have been tested primarily on foreign exchange rates (US dollar) and the assets of banks included in the special list of Ministry of Finance. In addition, for assets shows the different customization options algorithms - a long-term, short-term and medium-term (balanced) plan. Assessing the impact of oil prices and foreign currency exchange rate for the total market capitalization was conducted on a sample of the data collected: companies with a total market capitalization of 100 to 500 million rubles, present in the market during 2013-2015 Analytical server builds the neural network receiving the input exchange rates, companies, the weighted average share price, total capitalization of the company and the price of oil to requests received models give the opportunity to evaluate the growth rate of \ fall (if at all) the company's capitalization at historical exchange rates and / or the cost of oil. Built a system can expand to include new indicators, which will significantly increase the accuracy of forecasting.

A Python API client used to pull and retrieve data from the US Bureau of Economic Analysis

The basis of this project involves analyzing Amgen future profitability based on its current business environment and financial performance. Technical Analysis, on the other hand, includes reading the charts and using statistical figures to identify the trends in the stock market. The dataset used for this analysis was downloaded from Yahoo finance for year 2009 to 2019. There are multiple variables in the dataset – date, open, high, low, volume. Adjusted close. The columns Open and Close represent the starting and final price at which the stock is traded on a day. High and Low represent the maximum, minimum price of the share for the day. The profit or loss calculation is usually determined by the closing price of a stock for the day, I used the adjusted closing price as the target variable. I downloaded data on the inflation rate, unemployment rate, Industrial Production Index, Consumer Price Index for All Urban Consumers: All Items and Real Gross Domestic Product as independent variables, Quarterly Financial Report: U.S. Corporations: Cash Dividends Charged to Retained Earnings All Manufacturing: All Nondurable Manufacturing: Chemicals: Pharmaceuticals and Medicines Industry, Producer Price Index by Industry: Pharmaceutical Preparation Manufacturing, 30-Year Treasury Constant Maturity Rate, and Producer Price Index by Industry: Pharmaceutical and Medicine Manufacturing Index. The independent variables are economic parameters which was obtained from Federal Reserve Economic Data (FRED) website. Methodology 1. Linear Regression: The linear regression model returns an equation that determines the relationship between the independent variables and the dependent variable. I used linear regression tool in Alteryx with ARIMA tool to forecast the stock prices for the year. The algorithm was trained with the historical data to see how the variables impact on the dependent variable. The test data was used to predict the adjusted closing price for the year and predicted a stock price of $193.38. 2. Support Vector Machines (SVM): Support Vector Networks (SVN), are a popular set of supervised learning algorithms originally developed for classification (categorical target) problems and can be used for regression (numerical target) problems. SVMs are memory efficient and can address many predictor variables. This model finds the best equation of one predictor, a plane (two predictors) or a hyperplane (three or more predictors) that maximally separates the groups of records, based on a measure of distance into different groups based on the target variable. A kernel function provides the measure of distance that causes to records to be placed in the same or different groups and involves taking a function of the predictor variables to define the distance metric. I used the SVM tool in Alteryx with ARIMA tool to forecast the stock prices for the year and predicted a stock price of $189.44. 3. Spline Model: The Spline Model tool was used because it provides the multivariate adaptive regression splines (or MARS) algorithm of Friedman. This statistical learning model self-determines which subset of fields best predict a target field of interest and can capture highly nonlinear relationships and interactions between fields. I used the Spline tool in Alteryx with ARIMA tool to forecast the stock prices for the year and predicted a stock price of $201.84. The results from the models was weighted by comparing the RMSE of each model. A lower RMSE indicates that the model’s predictions were closer to the actual values. However, a simpler model with the same RMSE as a more complex model is generally better, as simpler models are less likely to be overfit. Though the Spline model had a lower RMSE, the Linear Regression model had fewer variables. Thus, we combined the 3 models with the ARIMA forecast in a model ensemble, which allows us to use the results of multiple models. The forecasted stock price is $197.99 with 1.5% increase for 31st December 2019. Apart from economic parameters, stock price is affected by the news about the company and other factors like demonetization or merger/demerger of the companies. There are certain intangible factors which can often be impossible to predict beforehand hence the model predicts that the stock price of Amgen will continue to rise except there is a drastic downturn of the company.

DESCRIPTION One of the leading retail stores in the US, Walmart, would like to predict the sales and demand accurately. There are certain events and holidays which impact sales on each day. There are sales data available for 45 stores of Walmart. The business is facing a challenge due to unforeseen demands and runs out of stock some times, due to the inappropriate machine learning algorithm. An ideal ML algorithm will predict demand accurately and ingest factors like economic conditions including CPI, Unemployment Index, etc. Walmart runs several promotional markdown events throughout the year. These markdowns precede prominent holidays, the four largest of all, which are the Super Bowl, Labour Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in the evaluation than non-holiday weeks. Part of the challenge presented by this competition is modeling the effects of markdowns on these holiday weeks in the absence of complete/ideal historical data. Historical sales data for 45 Walmart stores located in different regions are available. Dataset Description This is the historical data which covers sales from 2010-02-05 to 2012-11-01, in the file Walmart_Store_sales. Within this file you will find the following fields: Store - the store number Date - the week of sales Weekly_Sales - sales for the given store Holiday_Flag - whether the week is a special holiday week 1 – Holiday week 0 – Non-holiday week Temperature - Temperature on the day of sale Fuel_Price - Cost of fuel in the region CPI – Prevailing consumer price index Unemployment - Prevailing unemployment rate Holiday Events Super Bowl: 12-Feb-10, 11-Feb-11, 10-Feb-12, 8-Feb-13 Labour Day: 10-Sep-10, 9-Sep-11, 7-Sep-12, 6-Sep-13 Thanksgiving: 26-Nov-10, 25-Nov-11, 23-Nov-12, 29-Nov-13 Christmas: 31-Dec-10, 30-Dec-11, 28-Dec-12, 27-Dec-13 Analysis Tasks Basic Statistics tasks Which store has maximum sales Which store has maximum standard deviation i.e., the sales vary a lot. Also, find out the coefficient of mean to standard deviation Which store/s has good quarterly growth rate in Q3’2012 Some holidays have a negative impact on sales. Find out holidays which have higher sales than the mean sales in non-holiday season for all stores together Provide a monthly and semester view of sales in units and give insights Statistical Model For Store 1 – Build prediction models to forecast demand

Saxo Bank Review Info Update 2022 otoxs July 03, 2022 Saxo bank is considered one of the most relied on names inside the world of foreign exchange buying and selling. The dealer provides a huge collection of belongings for margin-based totally trading, low spreads, and lightning speedy execution of trades. The broker holds a couple of policies global. In this article, I review some functions that Saxo Bank has and why buyers and nontraders could make money with the broker’s provision.Overview Saxo Bank A/S is privately owned; Geely Financials Denmark A/S, a subsidiary of Zhejiang Geely Holding Group Co., Ltd, owns fifty two percentage of the stocks of its shares. The founder and CEO of Saxo Bank, Kim Fournals, owns 25.71% of the Bank shares. Shampoo Plc, a main Nordic economic offerings enterprise, additionally owns 19.9% of the financial institution shares. Minority shareholders, such as numerous modern and former personnel of the Bank, preserve the ultimate stocks. The Bank turned into the primary broking in Denmark to gain approval from the European Investment Directive in 1992. Saxo Group presently operates international, taking part carefully with supervisory government in each jurisdiction it exists in. The broking is regulated through the Australian Securities and Investments in Australia, the Securities and Futures Commission in Hong Kong, the Japanese Financial Services Agency in Japan, Financial Conduct Authority inside the UK, Bank of Netherlands within the Netherland. It is also regulated in Italy, Czech, Singapore, Switzerland, U.A.E., Denmark, and many others. Aside from having a extensive agency jurisdiction, it additionally has a completely extensive variety of markets reachable to traders. The markets furnished encompass foreign exchange, stocks, ETFs, Bonds, Mutual Funds, Futures, Listed Options, and more. It also gives controlled portfolios wherein professionals navigate and manipulate your investments without your input. The controlled portfolio additionally gives you the liberty to withdraw at any time. The Bank has provisions for retail traders and institutional buyers.ProsConsStrongly regulated Wide variety of markets Useful studies toolsHigh minimum deposit Only to be had for six days a week High bond, alternatives and destiny costs Who is Saxo Bank for? The broking offers a extensive variety of offerings, and it has one of a kind aspects, which makes it beneficial for one of a kind forms of humans. The SaxoSelect program affords a controlled portfolio that's beneficial for individuals who do not have any form of history in trading. Through the program, specialists carry out buying and selling and manipulate portfolio for your behalf. The SaxoSelect is not just beneficial for amateur investors; other buyers who do no longer have time to exchange or desire to construct a separate portfolio other than their regular trades also can make earnings through the program. Beginners and advanced buyers also can make money through trading the lots of gadgets which are to be had at an cheap rate. The broker additionally provides a wholesome ground for institutional buyers and people who're inquisitive about partnering with the corporation. Rating: four.five/5Is Saxo Bank Safe? Saxo Bank A/S is integrated in Denmark as a certified bank and is regulated along side Saxo Bank A/S Italy, Saxo Bank AS the Czech Republic, Saxo Bank Netherlands via the Danish Financial Supervisory Authority (F.S.A.). As a member of the European Union, the E.U. Banking and Investment Directives were incorporated through Denmark into the Danish Law. Saxo financial institution A/C and its branches are also regulated in one of a kind jurisdictions. It is regulated and licensed in the U.K. by using the Financial Conduct Authority; BG SAXO Societal did. Intermediazione Mobiliaire S.p.A. is certified by way of the Italian Market Authority. It is licensed in the Czech Republic with the aid of Czech National Bank. Saxo Bank A/S Netherlands is registered by means of the Bank of Netherlands. Saxo Bank Pte. Ltd. Singapore is supervised through the Monetary Authority of Singapore. It is a capital markets offerings license holder and an exempt financial marketing consultant. Other rules and licenses include the Central Bank of U.A.E. as a consultant workplace, Japanese Financial Services Agency, Securities and Futures Commission in Hong Kong, Australia Securities and Investments Commission in Australia.[2] So a long way, what I will say is that the bank is duly certified and controlled by way of the top and trusted agencies and businesses. For more statistics approximately the licenses and guidelines, please click right here. Rating: 4.5/5Year founded:1992Publicly traded: NoLicenses: ASIC, FCA, FMS (Swiss), SFC, JFSA (Japanese), MAS (Singapore), and moreBacklist: NoOffering of InvestmentsStock Saxo financial institution provides get admission to to more than 19,000 stocks across several core and rising markets on extra than forty exchanges worldwide. I find this thoughts-blowing because it is not commonplace to look the range of shares furnished with the aid of the broker on many other brokerage systems. These exchanges encompass NASDAQ, NYS, Singapore Exchange, Hong Kong Exchange, Australian Securities Exchange, Tokyo Stock Exchange.ETFs It also has more than 3000 ETFs from extra than 30 exchanges across the worldBonds Mutual Funds there are extra than 250 top-rated mutual finances to be had on the platform. The mutual price range are from the sector’s largest investors.Futures They are also to be had of their thousand Listed Products Traders and traders have get admission to to extra than 1,two hundred listed options from 23 exchanges global. These listed alternatives are throughout equities, hobby rates, energy, metals, indices, and extra. Others Asides from all that have been listed above, you could additionally alternate cryptocurrency CFD and ETPs. The ETPs help to take a long-time period function without leverage. Forex trading and lots of extra. The dealer provides eighty two FX spot pairs and 140 forwards throughout fundamental, minor and distinguished pairs. Metals are also available. Rating: 4.5/5Forex: Spot TradingYesCurrency Pairs (Total the Forex market pairs)182Social Trading / Copy-TradingYesCFDs instrumentsforex, stocks, crypto, ETFs, Bonds, Mutual fund, futures, indexed products, and so on.Commissions & Fees The dealer gives enterprise-leading costs. Traders and traders get competitive spreads and commissions throughout all asset training. The rates additionally grow to be better as change volume will increase. The dealer offers commissions from $1 on US stocks and the USA-indexed ETFs. It also costs commissions as low as $1.25 futures and indexed options; there aren't any expenses for making an investment in mutual funds. Many of the options, bonds, and futures expenses are a little high as compared to some other agents. For more facts on the expenses Rating: 4/5Minimum Initial DepositUSD 10,00, 500(GBP) for UK, USD3000 for Australia and SGD three hundred for Singapore Average Spread EUR/USD – Standard0.8All-in Cost EUR/USD – Active0.6Minimum withdrawal Platforms & Tools SaxoTraderGO It has improved trade tickets, fundamental and technical evaluation equipment, an in depth charting package, performance analysis, and some other essential capabilities. It helps a one-screen setup even though the chart can be dragged to a 2nd display screen. I located that the platform is obtainable through mobile and exclusive variations of windows.SaxoTraderPRO it's miles completely customizable and is a expert-grade platform. It provides functions like algorithmic orders, one-click buying and selling, and different charting applications. I found that it's miles customizable throughout six screens, with superior workspace and more functions thru my check. This platform isn't reachable on mobile gadgets. It is restrained to PC and MAC. The two platforms are well constructed and are consumer-friendly. Connectivity and APIs: this device allows you hook up with Saxo’s capital markets infrastructure through your selected interface. Third-celebration equipment These tools assist to execute trades from one in all Saxo’s companion’s structures. This enables you join your Saxo account to a 3rd-birthday celebration platform to access custom tools that healthy your unique buying and selling requirement. These equipment, although useful, is probably too technical for beginners to understand how to use them. Such novices could need to undergo a getting to know procedure to master them. The broking also gives a demo account in which traders can alternate a selected marketplace earlier than trading it on a stay account. Rating: 4/5Virtual Trading (Demo)YesProprietary PlatformYesDesktop Platform (Windows)YesWeb PlatformYesMetaTrader four (MT4)YesMetaTrader 5 (MT5)NoCharting – Indicators / Studies (Total)58Charting – Drawing Tools (Total)19Charting – Trade From ChartYesOrder Type – Trailing StopYesResearch The studies tools cover all of the assets furnished. Saxo Bank affords day by day commentary and in-intensity analysis across its markets. There are also articles written through monetary experts from special fields that can be beneficial for buyers to get statistics from. The studies data helps you understand how investors view the markets and notice what the experts are seeing.

Principles of Data Science Part I. Fivethirtyeight data graphics An R package that provides access to the code and data sets published by FiveThirtyEight https://github.com/fivethirtyeight/data, was just made available to public. The developers, Albert Kim and his colleagues, maintains a webpage for the package fivethirtyeight: https://rudeboybert.github.io/fivethirtyeight/ The data sets included are massive. You can find a list of these, including the URLs to the original fivethirtyeight.com articles, at https://rudeboybert.github.io/fivethirtyeight/articles/fivethirtyeight.html. The task (Part I) is to choose one of the articles with data graphics, and recreate one or more of the data graphics found in the article. Examples of such report can be found at https://rudeboybert.github.io/fivethirtyeight/articles/ The report will consist of 1. A technical discussion of your data wrangling-visualization statements; 2. A brief paragraph explaining the context of the data graphic you created, and be prepared by R markdown. Part II. Retreive, explore, and analyze This part of the task is to retreive, explore, and analyze data in one of the topic areas. You will need to choose one from American Time Use Survey Data and Economic Mobility data (see below). Scope of the work The final product will consist of 1. visualization or tabulation of the data (from either exploring or modeling), 2. results of statistic tests for your hypothesis, 3. and modeling and predictions from statistical learning methods. report The report consists of 1. Proposed goals in your progress report, 2. Analysis (both code chunks and results), 3. Interpretation, 1. Economic Mobility data We will look at economic mobility across generations in the contemporary USA. The data come from a large study1, based on tax records, which allowed researchers to link the income of adults to the income of their parents several decades previously. For privacy reasons, we don’t have that individual-level data, but we do have aggregate statistics about economic mobility for several hundred communities, containing most of the American population, and covariate information about those communities. We are interested in predicting economic mobility from the characteristics of communities. Data can be read using the following R code. There are 741 communities (observations) and 43 variables. dat <- read.csv("mobility.csv") The variable we want to predict is economic mobility; the rest are predictor variables or covariates. 1. Mobility: The probability that a child born in 1980–1982 into the lowest quintile (20%) of household income will be in the top quintile at age 30. Individuals are assigned to the community they grew up in, not the one they were in as adults. (가계 소득의 최저 5 분위수 (20 %)에 속해 있는 1980-1982 년 출생한 아이가 30세에 되었을 때 상위 1 분위에 속할 확률)
 2. Population in 2000. (2000년 기준 인구)
 3. Is the community primarily urban or rural? (커뮤니티가 도시인가 시골인가?)
 4. Black: percentage of individuals who marked black (and nothing else) on census forms. (흑인의 비율)
 5. Racial segregation: a measure of residential segregation by race. (인종별 주거지 분리의 정도)
 6. Income segregation: Similarly but for income. (소득별 주거지 분리의 정도)
 7. Segregation of poverty: Specifically a measure of residential segregation for those in the bottom quarter of the national income distribution. (저소득층과 중상류층의 주거지 분리의 정도)
 8. Segregation of affluence: Residential segregation for those in the top qarter. (상류층과 중하층의 주거지 분리의 정도)
 9. Commute: Fraction of workers with a commute of less than 15 minutes. (15 분 미만 통근하는 주민의 비율)
 10. Mean income: Average income per capita in 2000. (평균 소득 )
 11. Gini: A measure of income inequality, which would be 0 if all incomes were perfectly equal, and tends towards 100 as all the income is concentrated among the richest individuals. ( 지니 계수)
 12. Share 1%: Share of the total income of a community going to its richest 1%. (상위 1% 가 차지하는 수입의 비율)
 13. Gini bottom 99%: Gini coefficient among the lower 99% of that community. (상위 1 %를 제외한 나머지의 지니 계수)
 14. Fraction middle class: Fraction of parents whose income is between the national 25th and 75th percentiles. ( 중산층 비율 )
 15. Local tax rate: Fraction of all income going to local taxes. ( 지방세율 )
 16. Local government spending: per capita. ( 1 인당 지방정부 지출 )
 17. Progressivity: Measure of how much state income tax rates increase with income. ( 세금 가중의 정도 )
 18. EITC: Measure of how much the state contributed to the Earned Income Tax Credit (a sort of negative income tax for very low-paid wage earners). ( 저소득층을 위한 세금 공제의 정도 )
 19. School expenditures: Average spending per pupil in public schools. ( 공립학교의 학생 1 인당 평균 지출. )
 20. Student/teacher ratio: Number of students in public schools divided by number of teachers.( 학생 / 교사 비율 )
 21. Test scores: Residuals from a linear regression of mean math and English test scores on household income per capita. ( 시험 점수: 언어+수학 점수를 평균 가정 소득에 회귀한 잔차 )
 22. High school dropout rate: Also, residuals from a linear regression of the dropout rate on per-capita income. ( 고등학교 중퇴율 : 실제 중퇴율를 평균 가정 소득에 회귀한 잔차 )
 23. Colleges per capita ( 1 인당 대학의 갯수 )
 24. College tuition: in-state, for full-time students ( 대학 등록금 )
 25. College graduation rate: Again, residuals from a linear regression of the actual graduation rate on household income per capita. ( 대학 졸업율: 실제 졸업율를 평균 가정 소득에 회귀한 잔차 )
 26. Labor force participation: Fraction of adults in the workforce. ( 노동인구 중 성인의 비율 )
 27. Manufacturing: Fraction of workers in manufacturing. ( 제조업 근로자의 비율 )
 28. Chinese imports: Growth rate in imports from China per worker between 1990 and 2000. ( 중국산 수입 증가율 )
 29. Teenage labor: fraction of those age 14–16 who were in the labor force. ( 노동인구 중 10 대의 비율 )
 30. Migration in: Migration into the community from elsewhere, as a fraction of 2000 population. ( 이사오는 비율 )
 31. Migration out: Ditto for migration into other communities. ( 이사 나가는 비율 )
 32. Foreign: fraction of residents born outside the US. ( 외국 태생 인구 비율 )
 33. Social capital: Index combining voter turnout, participation in the census, and participation in community organizations. ( 사회 참여의 정도 )
 34. Religious: Share of the population claiming to belong to an organized religious body. ( 종교 생활 참여의 정도 )
 35. Violent crime: Arrests per person per year for violent crimes. ( 폭력 범죄율 )
 36. Single motherhood: Number of single female households with children divided by the total number of households with children. ( 전체 아이가 있는 가정 중 엄마 혼자 아이 키우는 집의 비율 )
 37. Divorced: Fraction of adults who are divorced. (이혼한 비율 )
 38. Married: Ditto. ( 결혼한 비율 )
 39. Longitude: Geographic coordinate for the center of the community (경도: 동서 )
 40. Latitude: Ditto ( 위도: 남북 )
 41. ID: A numerical code, identifying the community. ( 커뮤니티 식별 코드 )
 42. Name: the name of principal city or town. ( 동네 이름 )
 43. State: the state of the principal city or town of the community. ( 동네가 속한 미국의 주)
 1. Chetty, Raj, Nathaniel Hendren, Patrick Kline and Emmanuel Saez (2014). “Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States.” Quarterly Journal of Economics, 129: 1553– 1623. Finding and reading this paper does not actually help you↩


In this project, I have used the US Economic Data to explore how variation in GDP makes an impact on the unemployment rate. Then I make a dashboard to display the line chart that compares both GDP variation & unemployment rate variations.

Analysis of county-scale US economic data from 1970 - 2013

This repository contains a data science project focused on analyzing economic indicators using the Gapminder dataset.

📈 USA Financial Performance Dashboard This project is a data analytics solution built in Power BI to monitor and analyze the financial health and operational performance of a large US-based organization (or an analysis of US economic indicators).

📈 USA Financial Performance Dashboard This project is a data analytics solution built in Power BI to monitor and analyze the financial health and operational performance of a large US-based organization (or an analysis of US economic indicators).

For this project we have used 2015 American Community Survey (ACS) as our primary dataset. The ACS dataset is annually compiled by the US Census, and designed to provide broad demographic and socio-economic characteristics of the US population. This project aims to visualize 13 variables of population and census data using a combination of choropleths, bar charts, pie charts, scatterplots and multiple maps. We have provided users with the ability to view the variable distribution of all states or the ability to select a state and obtain detailed information of different variables for each state. Our analysis has provided the following insights. The native population is highest in southern states such as New Mexico, Texas, Oklahoma & Arizona. A quick google search revealed that the region of Oklahoma had settled occupation that dates back to a previous time in history. This can be attributed to high number of natives in this region. Hopefully by using this visualization you can help us gather further insights into the data.

Do you know, as per WHO every year seven million people die from breathing polluted air and also, during world environmental day the WHO has warned that nine out of ten people on earth breathe polluted air(10 facts about air pollution on World Environment Day | World Economic Forum n.d.)? There is also a huge problem as we are all aware of happening around the world in terms of global warming. Gases like carbon potentially damage the earth's ozone layer. This is something that can destroy humankind by the hit of even a small asteroid. As responsible data engineers, what we can contribute to society in this regard? There could be so many topics I could talk about, but I strongly believe it’s time for us, data engineers to make use of technology to deep dive into the data to explore it further and make predictions from it. We can make use of these predictions to focus on those counties or towns so that govt. can put more regulations in place to protest against the unrestrained use of plastic or fossil fuel vehicles (Hertwich et al. 2001). Such measures are inevitable in this era to mitigate the air pollution in the country and around the world. Even though several studies like (Roberts 2004) have been done in the past, In my view, this analysis is expected to make accurate and more efficient models which can impact the society to act differently by using more eco-friendly vehicles and materials in day to day life leveraging the air pollution in all the cities of US.

Summery: These developments are hampering operations resulting in supply chain breaches, stock market inefficiencies, and vendor chaos. These are constantly interfering with the normal functioning of industries. The latest report by Global Market Vision with COVID19 Impact on Open Source Intelligence Market Size, Share, Growth, Industry Trends and Forecast to 2028 offers detailed coverage of the industry and main market trends with historical and forecast market data, demand, application details, price trends, and company shares of the leading Open Source Intelligence by geography. This report also studies the Open Source Intelligence market status, competition landscape, market share, growth rate, future trends, market drivers, opportunities and challenges, sales channels, and distributors. The report splits the market size, by volume and value, based on application, type, and geography. Free Sample Report + All Related Graphs & Charts @ https://www.adroitmarketresearch.com/contacts/request-sample/2606 The complete value chain and downstream and upstream essentials are scrutinized in this report. Essential trends like globalization, growth progress boost fragmentation regulation & ecological concerns. This Market report covers technical data, manufacturing plants analysis, and raw material sources analysis of Open Source Intelligence Industry as well as explains which product has the highest penetration, their profit margins, and R & D status. The report makes future projections based on the analysis of the subdivision of the market which includes the global market size by product category, end-user application, and various regions. Various factors are responsible for the market’s growth trajectory, which are studied at length in the report. In addition, the report lists down the restraints that are posing threat to the global Open Source Intelligence market. This report is a consolidation of primary and secondary research, which provides market size, share, dynamics, and forecast for various segments and sub-segments considering the macro and micro environmental factors. It also gauges the bargaining power of suppliers and buyers, threat from new entrants and product substitute, and the degree of competition prevailing in the market. Access full Report Description, TOC, Table of Figure, Chart, etc. @ https://www.adroitmarketresearch.com/industry-reports/open-source-intelligence-market Global Open Source Intelligence Market research report offers: • Market definition of the global Open Source Intelligence market along with the analysis of different influencing factors like drivers, restraints, and opportunities. • Extensive research on the competitive landscape of global Open Source Intelligence. • Identification and analysis of micro and macro factors that are and will effect on the growth of the market. • A comprehensive list of key market players operating in the global Open Source Intelligence market. • Analysis of the different market segments such as type, size, applications, and end-users. • It offers a descriptive analysis of demand-supply chaining in the global Open Source Intelligence market. • Statistical analysis of some significant economics facts • Figures, charts, graphs, pictures to describe the market clearly. Marketing Communication and Sales Channel Understanding marketing effectiveness on a continual basis help determine the potential of advertising and marketing communications and allow to use best practices to utilize untapped audience. In order to make marketers make effective strategies and identify why target market is not giving attention we ensure Study is Segmented with appropriate marketing & sales channels to identify potential market size by value & Volume* (if Applicable). SWOT Analysis on COVID-19 Outbreak- Open Source Intelligence Players In additional Market Share analysis of players, in-depth profiling, product/service and business overview, the study also concentrates on BCG matrix, heat map analysis, FPNV positioning along with SWOT analysis to better correlate market competitiveness. Demand from top notch companies and government agencies is expected to rise as they seek more information on latest scenario. Check Demand Determinants section for more information. Reasons for buying this report: * It offers an analysis of changing competitive scenarios. * For making informed decisions in the businesses, it offers analytical data with strategic planning methodologies. * It offers a six-year assessment of Open Source Intelligence Market. * It helps in understanding the major key product segments. * Researchers throw light on the dynamics of the market such as drivers, restraints, trends, and opportunities. * It offers a regional analysis of Open Source Intelligence Market along with the business profiles of several stakeholders. * It offers massive data about trending factors that will influence the progress of the Open Source Intelligence Market. Table of Content: 1 Scope of the Report 1.1 Market Introduction 1.2 Research Objectives 1.3 Years Considered 1.4 Market Research Methodology 1.5 Economic Indicators 1.6 Currency Considered 2 Executive Summary 3 Global Open Source Intelligence by Players 4 Open Source Intelligence by Regions 4.1 Open Source Intelligence Market Size by Regions 4.2 Americas Open Source Intelligence Market Size Growth 4.3 APAC Open Source Intelligence Market Size Growth 4.4 Europe Open Source Intelligence Market Size Growth 4.5 Middle East & Africa Open Source Intelligence Market Size Growth 5 Americas 6 APAC 7 Europe 8 Middle East & Africa 9 Market Drivers, Challenges and Trends 9.1 Market Drivers and Impact 9.1.1 Growing Demand from Key Regions 9.1.2 Growing Demand from Key Applications and Potential Industries 9.2 Market Challenges and Impact 9.3 Market Trends 10 Global Open Source Intelligence Market Forecast 11 Key Players Analysis 12 Research Findings and Conclusion Do You Have Any Query Or Specific Requirement? Ask to Our Industry Expert @ https://www.adroitmarketresearch.com/contacts/enquiry-before-buying/2606 ABOUT US: Adroit Market Research is an India-based business analytics and consulting company. Our target audience is a wide range of corporations, manufacturing companies, product/technology development institutions and industry associations that require understanding of a market’s size, key trends, participants and future outlook of an industry. We intend to become our clients’ knowledge partner and provide them with valuable market insights to help create opportunities that increase their revenues. We follow a code– Explore, Learn and Transform. At our core, we are curious people who love to identify and understand industry patterns, create an insightful study around our findings and churn out money-making roadmaps. CONTACT US: Ryan Johnson Account Manager Global 3131 McKinney Ave Ste 600, Dallas, TX 75204, U.S.A Phone No.: USA: +1.210.667.2421/ +91 9665341414

"This report gives a significant enumerating and intensive systematic investigation of the global Clinical Laboratory Services Market taking into account the growth factors, recent trends, developments, opportunities, and competitive landscape. The market analysts and researchers have done extensive analysis of the global Clinical Laboratory Services market with the help of research methodologies such as Pestle and Porter’s Five Forces analysis. They have provided accurate and reliable market data and useful recommendations with an aim to help the players gain an insight into the overall present and future market scenario. The Clinical Laboratory Services report comprises in-depth study of the potential segments including product type, application, and end user and their contribution to the overall market size. The Clinical Laboratory Services market research report added by Adroit Market Research, is an in-depth analysis of the latest developments, market size, status, upcoming technologies, industry drivers, challenges, regulatory policies, with key company profiles and strategies of players. The research study provides market overview; Clinical Laboratory Services derived key statistics, based on the market status of the manufacturers and is a valuable source of guidance and direction for companies and individuals interested in Clinical Laboratory Services market size forecast, Get report to understand the structure of the complete fine points (Including Full TOC, List of Tables & Figures, Chart). Get Exclusive Sample of Report on Clinical Laboratory Services market is available @ https://www.adroitmarketresearch.com/contacts/request-sample/713 Leading Companies Reviewed in the Report are: ACM Medical Laboratory, Abbott Laboratories, Arup Laboratories, Adicon Clinical Laboratory, Bio-Reference Laboratories, Charles River Laboratories, Inc., Bioscientia Healthcare, and Clarient Inc. Other prominent players too have considerable contribution in this market which includes Genzyme Corporation, Genoptix Medical Laboratory, Healthscope Ltd., Labcorp, Intertek, Labco S.A., Lifelabs Medical Laboratory, Siemens Sonic Healthcare Limited, Qiagen, Quest Diagnostics, Inc., In-Depth Qualitative Analyses Include Identification And Investigation Of The Following Aspects: Market Structure, Growth Drivers, Restraints and Challenges, Emerging Product Trends & Market Opportunities, Porter’s Fiver Forces. The report also inspects the financial standing of the leading companies, which includes gross profit, revenue generation, sales volume, sales revenue, manufacturing cost, individual growth rate, and other financial ratios. The report basically gives information about the Market trends, growth factors, limitations, opportunities, challenges, future forecasts, and details about all the key market players. Global Clinical Laboratory Services Market is segmented based by type, application and region. Based on type, the market has been segmented into, Clinical Chemistry Medical Microbiology & Cytology Human & Tumor Genetics Other Esoteric Tests Based on service provider, the market has been segmented into, Hospital-based Laboratories Clinic-based Laboratories Stand-alone Laboratories Based on therapeutic application, the market has been segmented into, Applications1 Applications2 Other Applications Geographical Breakdown: Regional level analysis of the market, currently covering North America, Europe, China & Japan Study on Table of Contents: Clinical Laboratory Services Market Overview, Scope, Status and Prospect (2015-2020) covering COVID-19 Pandemic. Global Clinical Laboratory Services Market Competition by Manufacturers Global Clinical Laboratory Services Capacity, Production, Revenue (Value) by Region (2015-2020) Global Clinical Laboratory Services Supply (Production), Consumption, Export, Import by Region (2015-2020) Global Clinical Laboratory Services Production, Revenue (Value), Price Trend by Type Global Clinical Laboratory Services Manufacturers Profiles/Analysis Clinical Laboratory Services Manufacturing Cost Analysis Industrial Chain, Sourcing Strategy and Downstream Buyers Marketing Strategy Analysis, Distributors/Traders Global Clinical Laboratory Services Market Effect Factors Analysis and Forecast (2020-2025) Research Findings and Conclusion Appendix – Methodology/Research Approach, Market Size Estimation, Data Source, Secondary Sources, Primary Sources, and Disclaimer. Browse the complete report Along with TOC @ https://www.adroitmarketresearch.com/industry-reports/clinical-laboratory-services-market Key Points Covered in Clinical Laboratory Services Market Report: COVID 19 Impact Analysis Market Characteristics – The market characteristics section of the report defines and explains the Clinical Laboratory Services market. This chapter includes different goods and services covered in the report, basic definitions and market supply chain analysis. Global Market Size And Growth – This section contains the global historic and forecast market value, and drivers and restraints that support and control the growth of the market in the historic and forecast period 2020 Updated & COVID 19 Outbreak Impact Analysis Trends And Strategies – This chapter includes some of the major trends shaping the global Clinical Laboratory Services market by segment. This section highlights likely future developments in the market and suggests approaches companies can take to exploit these opportunities 2020 Updated & Covid 19 Impact and Recovery PESTEL Analysis – This chapter covers the political, economic, social, technological, environmental and legal factors affecting a market. Customer Information – This section includes customer surveys in the Clinical Laboratory Services industry & Trends to Watch During the COVID-19 Outbreak Global Market Segmentation – This section contains global segmentation of the Clinical Laboratory Services market. Segmentation types include by region and by country segmentation of the Clinical Laboratory Services market. Drives Future Change Do You Have Any Query Or Specific Requirement? Ask to Our Industry Expert @ https://www.adroitmarketresearch.com/contacts/enquiry-before-buying/713" About Us : Adroit Market Research is an India-based business analytics and consulting company incorporated in 2018. Our target audience is a wide range of corporations, manufacturing companies, product/technology development institutions and industry associations that require understanding of a market’s size, key trends, participants and future outlook of an industry. We intend to become our clients’ knowledge partner and provide them with valuable market insights to help create opportunities that increase their revenues. We follow a code – Explore, Learn and Transform. At our core, we are curious people who love to identify and understand industry patterns, create an insightful study around our findings and churn out money-making roadmaps. Contact Us : Ryan Johnson Account Manager Global 3131 McKinney Ave Ste 600, Dallas, TX75204, U.S.A. Phone No.: USA: +1 972-362 -8199/ +91 9665341414

Summary The given report aims to explain the features and characteristics of the global “Perfume” market. It talks about the benefits offered by the market and contains discrete data to give a concise idea about the traits of the market. Besides it also talks about the existing matters of the market and its current circumstances. It accesses the global situation of the market and suggests specialist-devised conclusions. This report analyzes every face of the market giving a comprehensive approach to the report so that, no important information is left aback. Thereby, the report could be of great use to prospective investors, producers, and specialists in the market. Furthermore, the report contains a contrast of information explaining both the advantages and the disadvantages. The report further talks about the market drivers of the “Perfume” market. Market drivers are factors that boost the growth of the market. Such factors are evaluated and collated in the report. Furthermore, in every sector, there is a risk for future validity. Such restraints of the forecasted period are predicted in the report and solutions are also devised. Such an assessment of the vulnerability of the market gives the producers an upper hand to see the forthcoming problems in the “Perfume” market. The value of the market and the CAGR rate of the market in the forecasted period are also estimated in the given report. After a comprehensive and detailed description of the working of the market and its aspects, the report evaluates each segment of the “Perfume” market. The market is typically segmented by type, application, end-user and region. Such aspects are a necessary force and determine the progress of the market. The most lucrative types and the most generic applications of the market are examined and described in the report. Also, the key players in the market and their growth strategies are further discussed in the report. The end-user habits along with the solutions of the market players are also discretely mentioned in the report. Free Sample Report + All Related Graphs & Charts @ https://www.adroitmarketresearch.com/contacts/request-sample/547 The geographical location and the availability of resources also acts as an important factor in determining the future of the market. Each market has varying potential in different regions and it must be assessed before the commencement of the business. The report interprets the potential of each region in the world concerning the “Perfume” market. The social, political and economic facets of the region also play a crucial role in the progress and advancement of the market and thereby, the impact of such components is also included in the report. Purchase the report at https://www.adroitmarketresearch.com/researchreport/purchase/547 Key Points Covered in the Report: A thorough analysis of value and volume at the worldwide, sector, and regional levels is included in the global ' Perfume' market report. The study offers a full business size ' Perfume' from a global point of view through a review of past facts and possible scenarios. Geographically, the Perfume of market analysis includes the number of regions and their contrast of revenue. The The market analysis focuses on ex-factory costs, output volume, market share & sales for every manufacturer on a company level basis. Key Reasons to Purchase this Report: A comprehensive study of market size, share and dynamics is a global ' Perfume' market research report and a thorough survey of developments in the field. It offers an in-depth overview of revenue growth and an analysis of the total business benefits. In addition to the strategic landscape for commodity pricing and marketing, the ' Perfume' industry research also provides key players. This is a new post covering the latest impact on the target market. The research report addresses the rapidly evolving market climate as well as the initial and future impact assessment. ABOUT US: Adroit Market Research is an India-based business analytics and consulting company. Our target audience is a wide range of corporations, manufacturing companies, product/technology development institutions and industry associations that require understanding of a market’s size, key trends, participants and future outlook of an industry. We intend to become our clients’ knowledge partner and provide them with valuable market insights to help create opportunities that increase their revenues. We follow a code– Explore, Learn and Transform. At our core, we are curious people who love to identify and understand industry patterns, create an insightful study around our findings and churn out money-making roadmaps. CONTACT US: Ryan Johnson Account Manager Global 3131 McKinney Ave Ste 600, Dallas, TX 75204, U.S.A Phone No.: USA: +1 9726644514/ +91 9665341414

US_Economic_Data_Analysis

A look into several datsets concerning the US's economy

No description available

This project analyzes economic data for the 50 U.S. states from 1980 to 2018. The dataset includes key variables such as population, unemployment rates, personal income, and state minimum wage, allowing for a comprehensive examination of economic trends over nearly four decades.

Analysis of US economic data and building a dashboard

Used FRED API to search for and pull data to conduct analysis on. Analysis of unemployment rates for different states in the USA and also labour participation rates.

Exploratory data analysis on US political, socio-economic, wealth and public health outcomes

No description available

In-depth analysis of US market trends, encompassing economic indicators, industry performance, and financial data

Exploratory Data analysis of the US House election data and district level socio-economic variables from 2000 to 2020

Creating a simple dashboard in Python using Ibm Watson to show your analysis on Us Economic Data.

An open-source toolset for automated US stock & ETF data analysis, designed to help retail investors access macro-economic insights and structured financial data.