Investment Funds of European Countries

Posted on Jun 11, 2019

Project GitHub | LinkedIn




Financial data is a strong source of information that gives us an idea of how well the economy is functioning.  We like to see consistent flow of funds in the market because this is a good indicator that investors are confident.  Although the investment market is not the whole of the economy, it is a major component of total economic output, the GDP. This highly interactive application gives users insight on how investment funds are being distributed across Europe.



This app is designed to allow you, the user, to extract specific information about European financial markets over the past ten years. There are three different sets of interactive plots, each being adjusted according to the year selected.  


Countries Analyzed:

Austria, Belgium, Cyprus, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Portugal, Slovakia, Slovenia, Spain


Fund Types:

The stock value of a fund is the amount of that fund that a country owns.  The flows on the other hand is a measure of how much was put in or taken out of that fund. A negative investment flow implies that businesses have taken their money out of that fund.

Bond Funds, Equity Funds, Hedge Funds, Mixed Funds, Real Estate Funds, Other Funds


The App:

The first set of plots allows you to observe the investments of each country individually and compare how they invest in each kind of fund.



The second set of plots gives an in depth look at each fund, and how each country invests in them.  The line chart on the top shows how much each country owns of that fund, and the line chart on the bottom shows us how much each country invested in that fund throughout the year. It may be hard to compare initially due to the large amount of companies represented on these plots, but hovering over each line will show the country name and how much was invested.



The final set of plots gives us an in depth look at how each country ranks in the amount of assets owned. The top bar plot illustrates rank of each country with respect to the selected fund. The bottom bar plot shows us the rank of the top five countries aggregated over all fund types for that particular year. It is interesting to note that the leader in a particular fund may not lead in the sum of all funds.


About Author

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI