A recent addition to the Concert Datasets page is Operabase, a database of over 500,000 opera performances worldwide since 2004. I plan to look at this data more closely in a future article, but for now, I thought it would be interesting to see if opera performances follow a power law.1
Continue reading →Category: Case Studies
Eighteenth Century London Concerts: 6 – Repertoire
This article looks at the types of repertoire included in eighteenth-century London concerts. As discussed in the first article of this series, information on the works performed is encoded, in a complicated way, in the “programme” field of the dataset.
The data is based on concert advertisements in newspapers, so there is considerable variation in the detail provided. Some advertisements spell out details of all of the works and who will perform them, but it is more typical for the focus to be on the performers, with the works often vaguely specified, such as “a concerto by Handel” (if you are lucky, it will say what instrument it is for).
Continue reading →Eighteenth Century London Concerts: 5 – The Concert Season
This article in the series exploring the Eighteenth Century London Concerts dataset looks at when the concerts were held. This covers questions such as in which decade or year they took place, at what point during the year, on which days of the week, and at what times of day? And how did this vary according to the type of concert?
Continue reading →Eighteenth Century London Concerts: 4 – Ticket Prices
In this article about the Eighteenth Century London Concerts dataset, I will look in more detail at the prices of concert tickets.
The published data has multiple prices and categories listed in single cells of the spreadsheet. This needs to be parsed before it can be used for statistical analysis.
Continue reading →Eighteenth Century London Concerts: 3 – Concert Venues
The first article in this series looked at how to get the data on Eighteenth Century London Concerts into a more usable form, and the second geocoded the locations and classified the venues by type. In this third article, we will start the analysis of the data by looking in more detail at the distribution of concert venues.
Continue reading →Eighteenth Century London Concerts: 2 – The Locations
In the previous article looking at Simon McVeigh’s “Calendar of London Concerts 1750-1800“, I considered how to organise the data to make it suitable for statistical analysis. In this second article, I will add to the dataset by identifying the exact locations of the concert venues.
Continue reading →Eighteenth Century London Concerts: 1 – The Data
This is the first in a series of articles looking at Simon McVeigh’s fascinating dataset “Calendar of London Concerts 1750-1800“. In this article I will describe the data and consider how it can be put into a form suitable for statistical analysis. A second article will look at finding the locations of the concert venues, and I will then move on to some analysis of the dataset.
Continue reading →British Music Plaques
Many British buildings are adorned with plaques, marking the birthplace or residence of a famous person, or the site of a significant event. Details of these plaques are available in an online database, and I thought it would be interesting to see how many of them have a musical connection.
Continue reading →Desert Island Discs
“Desert Island Discs” is the UK’s longest running radio show, still going strong on BBC Radio 4 over 78 years after the first episode on the BBC Forces Programme in January 1942. Each episode, an interviewed “castaway” chooses the eight pieces of music they would take with them to a desert island. They also select their favourite of these tracks, plus a book and a luxury item.
Continue reading →Time at the top: classical vs popular music
One of the things that seems to distinguish ‘classical’ from ‘popular’ music is the fact that the same classical composers and works can remain at the top for very long periods of time – decades, even centuries – whereas popular music songs and artists can reach the top of the charts, sell millions of records, and disappear within a matter of months. But is this difference real?
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