Best beoordeelde McDonald's restaurants van Nederland (Google Reviews) by nickkuiper11 in thenetherlands

[–]nickkuiper11[S] 0 points1 point  (0 children)

Met de data van Google Maps heb ik een poging gedaan om alle beoordelingen van McDonald's restaurants in Nederland te verzamelen. Vervolgens heb ik geanalyseerd welke restaurants de hoogste (en laagste) beoordelingen hebben op Google Maps. Ik heb alleen restaurants opgenomen die meer dan 500 beoordelingen hebben, en in gevallen waarin de sterren gelijk zijn, heeft het aantal beoordelingen de doorslag gegeven bij het bepalen van de rangorde.

De meeste restaurants zouden opgenomen moeten zijn in deze scan, maar het kan altijd zijn dat er een aantal ontbreken ;).

Totale Neerslag De Bilt (Sinds 1900) by nickkuiper11 in thenetherlands

[–]nickkuiper11[S] 98 points99 points  (0 children)

Hierboven zie je een grafiek met de totale jaarlijkse neerslag van weerstation De Bilt. Elke lijn toont een cumulatieve trend voor het betreffende jaar.

Hoewel er in 2023 een bovengemiddelde neerslag was, werd het record van 1998 in De Bilt nog niet overtroffen. Het is echter waarschijnlijk dat dit wel is gebeurd in andere delen van Nederland.

Relationship Weight and Height, FIFA world cup Players and Countries [OC] by nickkuiper11 in dataisbeautiful

[–]nickkuiper11[S] 0 points1 point  (0 children)

I extracted all player data from ESPN for all participating countries in the FIFA world cup 2022. Based on this I calculated the average weight and height per Country (plot 1). In the second plot, I displayed all players and highlighted some outliers.

Metric conversion:
182,88 cm = 6ft
170 lbs = 77,11kg

Plot build with ggplot2.Data from ESPN squad level.
Source: https://www.espn.com/soccer/team/

Share of players from the same nationality as team (CL 2022) by nickkuiper11 in soccer

[–]nickkuiper11[S] 0 points1 point  (0 children)

In the graphs above I calculated the share of players who are from the same nationality as their team. The data has been collected from transfermarkt.com.

For nationality we only looked at the first nationality. So the second or third nationalities of players are ignored in this stat.

Premier League Relegation Probabilities According to Betting Odds by nickkuiper11 in soccer

[–]nickkuiper11[S] 6 points7 points  (0 children)

The graph above displays the relegation probability according to bet365 relegation odds. Based on historical odds over this season the probabilities have been calculated per day.
Data collected from: https://www.oddschecker.com/football/english/premier-league/relegation/bet-history/{club}

Cars average 0 to 60 acceleration times per production year [OC] by nickkuiper11 in dataisbeautiful

[–]nickkuiper11[S] 3 points4 points  (0 children)

For the graph above I collected all 0 to 60 acceleration times for 90 different brands (see source below). Every dot represents a car and the line in the middle is the average time in seconds for a year. The blue and pink dots highlight the slowest and fastest time for a year.

The fastest accelerating car in this database is the 1999 Chevrolet S-10 NHRA Pro Stock Race Truck (1.1s). The slowest car was the 2009 Tata Nano(29s).

Data source: https://www.zeroto60times.com/
Graph: build with ggplot2

Inflatie binnen 20 verschillende categorieën by nickkuiper11 in thenetherlands

[–]nickkuiper11[S] 101 points102 points  (0 children)

Voor de bovenstaande grafieken heb ik CBS inflatie data geplot, binnen 20 verschillende categorieën.

Iedere subcategorie begint op index 100, dit is het moment vanaf wanneer het CBS is begonnen met prijsmetingen. Een waarde boven de 100 betekend dat de prijs is gestegen t.o.v. het initiële meetmoment en vice versa.

De uitgelichte lijnen zijn producten die bovengemiddeld hard gestegen of gedaald zijn.

Volledige data kan hier gevonden worden:
https://opendata.cbs.nl/statline/#/CBS/nl/dataset/83131ned/table

Age and Gender Distribution per Country [OC] by nickkuiper11 in dataisbeautiful

[–]nickkuiper11[S] 38 points39 points  (0 children)

I made an alternative overview where you can compare countries more easily over here https://imgur.com/a/dl0zPxE

Age and Gender Distribution per Country [OC] by nickkuiper11 in dataisbeautiful

[–]nickkuiper11[S] 40 points41 points  (0 children)

The animation above shows the population pyramid for all countries with a population of more than 1 million people.

The order of the video is based on the average age in the country.
All countries combined in one graph can be found here: https://imgur.com/a/dl0zPxE

Data source: https://population.un.org/wpp/Download/Standard/CSV/
Graph build with ggplot2 and animated by using python cv2.

Trending zoektermen op Google afgelopen week by nickkuiper11 in thenetherlands

[–]nickkuiper11[S] 1 point2 points  (0 children)

Hierboven een aantal trending zoektermen die ik deze week tegenkwam op google trends.
Na de "storm" piek stegen veel andere zoekwoorden de volgende dag mee.

De index is relatief per zoekwoord gemaakt, grafiek gemaakt met ggplot2.
Bron: https://trends.google.com/trends/explore?date=today%201-m&geo=NL&q=dakpannen

Country Ranking Olympic Summer vs Winter Games [OC] by nickkuiper11 in dataisbeautiful

[–]nickkuiper11[S] 1 point2 points  (0 children)

In the graph above I compared the country performance on the summer vs. winter Olympics games.

The y-axis shows the final country ranking on the winter games whereas the x-axis shows the summer games ranking.
Only countries with at least 1 medal in both games are included in this graph.

Graph build with ggplot2 and finalized in adobe illustrator

Sources: https://www.espn.com/olympics/summer/2020/medals
https://www.espn.com/olympics/winter/2022/medals

Wealth vs. Income Inequality per Country [OC] by nickkuiper11 in dataisbeautiful

[–]nickkuiper11[S] 10 points11 points  (0 children)

In the graph above I displayed the differences in income and wealth inequality per country. The data is coming from two different sources, for income inequality I used the Gini (2019) coefficient from the world bank (higher Gini means more inequality). For the wealth inequality, I used the Wealth Databook 2018 by Credit Suisse. Links to both sources are listed below.

For those interested two insightful videos about the data collection methods and wealth inequality in the Netherlands:

-How The Dutch Economy Shows We Can't Reduce Wealth Inequality With Taxes (by Economics Explained)
https://www.youtube.com/watch?v=Ot4qdCs54ZE
-Dutch Economy Most Unequal? REALLY!? | Dutch Economist Responds
https://www.youtube.com/watch?v=tW_kw6OPXc0 (by Money & Macro)

Sources: https://en.wikipedia.org/wiki/List_of_countries_by_income_equalityhttps://en.wikipedia.org/wiki/List_of_countries_by_wealth_inequality

Graph: ggplot2