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Rock Music is Alive and Powerful! Statistics from 1950 and 2020

This article was done to get some statistics about rock music and what big data analysis can do to gather or discover hidden useful information.

The following analysis gets the data from Kaggle, free license

What is Kaggle? According to online definitions, Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. inside the website can be found courses, datasets, contest/challenges including money.

Dataset can be uploaded by single usernames or by companies during a competition.

 Scope of the Study

A lot of considerations can be made from the history of rock music, but the scope of this study is to support the changes that music rock did during the years.

Rock music, as an alternative of pop music (intended as common or soft) in the beginning was an underground music that gained fame during the years, with a constant increase. Some people or critics claim that rock is dead, but we will seek if there is a truth on this sentence.


Dataset is from 2020 retrieved from spotify covering rock songs from 1950 to 2020 with 5484 songs and 17 tags/label to identify and classify a song. From the tag list, only popularity is an index from the audience feedback while the remaining tags describe the song characteristics.

  1. Index
  2. Name: Song’s name
  3. Artist
  4. Release date
  5. Length: in minutes
  6. Popularity: A value from 0 to 100
  7. Danceability: Describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity.
  8. Acousticness: A confidence measure from 0.0 to 1.0 of whether the track is acoustic.
  9. Energy: Represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale.
  10. Instrumentalness: Predicts whether a track contains no vocals. “Ooh” and “aah” sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly “vocal”.
  11. Key: The estimated overall key of the track. Integers map to pitches using standard Pitch Class notation . E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on.
  12. Liveness: Detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live.
  13. Loudness: The overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks.
  14. Speechiness: This detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value.
  15. Tempo: The overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration.
  16. Time Signature: An estimated overall time signature of a track. The time signature (meter) is a notational convention to specify how many beats are in each bar (or measure).
  17. Valence: Describes the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).

Popularity requires some clarification from analytical point of view and need some assumptions. We don’t know when the popularity was measured, monthly or yearly, and also in which year. Considering this lack of information, we will assume likelihood that popularity was calculed in 2020 when considering songs from 1950 to 2019.

Data Pre-processing & Feature Engineering

After loading the data, we need to manipulate it according to our scope of the study, more specifically we will count the letters both in the artist’s name and song’s name.

The name of the song contains some noise created by the versions mastered or remastered. this creates a distortion in the real name of the song. Most of time, remastering a song has the only effect to clean using new technologies and also to refresh the mind of people.

Since there are 5848 rows in the data, this creates a lot of noise, so the best way for filtering data, is to preprocesssing in aggregated way following statistical parameters, mean, max & min of the values for each year from 1956 to 2020. This leads to a new data set of 65 rows where every row is one year.

Below you can find complete pdf.


Wind energy or Photovoltaic, which is the best?

Nowadays there are several sources that are not affected by quantity limitations because are renewed by the nature in different way, they are the renewable energies. The two most common and developed are wind energy (on-shore and off-shore) and solar (as photovoltaic), with some advantages according to the location where they will be placed, both are governed by environmental conditions.

Wind energy has the greatest advantage high energy density which relates to energy production in kWh and land occupied in sqm because they are developed vertically, on the other hand wind turbines can handle wind speeds from 3 m/s (cut-in) to 25 m/s (cut-out parameter).

Solar, photovoltaic energy has the greatest advantage to be cheaper than wind turbine, no cut-out parameter but they require more land area to achieve same energy production.

Over the years, cost of kW installed of both systems falls down until now when photovoltaic is cheaper the onshore wind energy, passing from barely 5000 usd/kW to less then 1000 usd in 10 years, while wind energy decreasing is less pronounced.

One the parameter that can help the reader to get a clear information of performance difference of both sources is the capacity factor.

Can be defined as the

unitless ratio of actual electrical energy output over a given period of time divided by the theoretical continuous maximum electrical energy output over that period.

The graph shows the capacity factor of all renewable energy sources and can be noticed that photovoltaic has a lower capacity than wind but at a cost that is 3 times lower than offshore wind and 0.5 times lower than onshore wind.

What is Data Driven Decision Making? A quick intro

Data driven decision making (DDD) refers to the practice of basing decisions on the analysis of data, rather than purely on intuition. For example, a marketer could select advertisements based purely on her long experience in the field and her eye for what will work. Or, she could base her selection on the analysis of data regarding how consumers react to different ads. She could also use a combination of these approaches. DDD is not an all-or-nothing practice, and different firms engage in DDD to greater or lesser degrees.

The benefits of data-driven decision-making have been demonstrated conclusively.
Economist Erik Brynjolfsson and his colleagues from MIT and Penn’s Wharton School conducted a study of how DDD affects firm performance (Brynjolfsson, Hitt, & Kim,2011). They developed a measure of DDD that rates firms as to how strongly they use Data Science, Engineering, and Data-Driven Decision Making data to make decisions across the company. They show that statistically, the more datadriven a firm is, the more productive it is—even controlling for a wide range of possible confounding factors. And the differences are not small. One standard deviation higher on the DDD scale is associated with a 4%–6% increase in productivity. DDD also is correlated with higher return on assets, return on equity, asset utilization, and market value, and the relationship seems to be causal.

In 2012, Walmart’s competitor Target was in the news for a data-driven decision-making
case of its own. Like most retailers, Target cares about consumers’ shopping habits, what drives them, and what can influence them. Consumers tend to have inertia in their habits and getting them to change is very difficult. Decision makers at Target knew, however, that the arrival of a new baby in a family
is one point where people do change their shopping habits significantly. In the Target analyst’s words, “As soon as we get them buying diapers from us, they’re going to start buying everything else too.” Most retailers know this and so they compete with each other trying to sell baby-related products to new parents. Since most birth records are public, retailers obtain information on births and send out special offers to the new parents.

However, Target wanted to get a jump on their competition. They were interested in whether they could predict that people are expecting a baby. If they could, they would gain an advantage by making offers before their competitors. Using techniques of data science, Target analyzed historical data on customers who later were revealed to have been pregnant, and were able to extract information that could predict which consumers were pregnant. For example, pregnant mothers often change their diets, their wardrobes, their vitamin regimens, and so on. These indicators could be extracted from historical data, assembled into predictive models, and then deployed in marketing campaigns.

Another case was in 2004 when Hurricane Frances was on its way, barreling across the Caribbean, threatening a direct hit on Florida’s Atlantic coast. Residents made for higher ground, but far away, in Bentonville, Ark., executives at Wal-Mart Stores decided that the situation offered a great opportunity for one of their newest data-driven weapons … predictive technology. A week ahead of the storm’s landfall, Linda M. Dillman, Wal-Mart’s chief information officer, pressed her staff to come up with forecasts based on what had happened when Hurricane Charley struck several weeks earlier. Backed by the trillions of bytes’ worth of shopper history that is stored in Wal-Mart’s data warehouse, she felt that the company
could ‘start predicting what’s going to happen, instead of waiting for it to happen,’ as she put it. (Hays, 2004)

Data Science for Business
by Foster Provost and Tom Fawcett

Natural Gas in Italy

After several months of research, we are happy to announce our first report about LNG & Natural Gas energy in Italy.

With more than 60 pages full of graphs and useful information, our report is a tool for journalists, data-driven companies and marked insider.

Below you can find some excerpts of the content of the book.

If you are interesed in a copy of this selected report, write to us info@htc-sagl.ch

Do you like vibrations? Have fun!

Fourier wave generator

Wave generation concept & theory is the key to understand vibrations in industry with a consequence on maintenance.

Discrete: Allows you to create a wave choosing the armonics value. turn on the speaker to hear it!

Wave Game: Try to match the wave below by chosing armonics values. there are 5 levels, level 1 with one armonic, level 5 with 5+ harmonics

Wave Packet: A full in depth view of fourier wave generation

Waves on a string

With this game you can study the effects of resonance, wave fundamentals and damping. Try to play around with frequency, amplitude, damping and tension.

Have fun!

Wind Power Generation

A technical review

Wind power generation is the most preferred among all renewable sources of energy, since the ratio between the dimension of the basement with energy produced is very high if compared with solar or hydro.

Wind power generation is not a new technology. The first turbine used for power generation was built in 1883 in Glasgow Scotland by professor James Blyth

The world’s first windfarm was in 1980 consisting of 20 turbines is built in New Hampshire, but due to a failure, the project was abandoned

But after 10 year of experimenting and testing, the first offshore wind farm was installed in the 90’s in Vindeby (Denmark), with a total power of 450kW.

From that day, improvement in technology, R&D and materials led to increase in power generation by wind with a decreasing cost.

Power generation against wind turbine diameter

In the graph it is possible to see increasing rotor diameter and the worldwide power generation. The swing between 2013-2015 neutralize themself. From the information above it is possible to obtain the specific power generation per meter (as diameter) of the rotor.

Energy produced per meter of the rotor

It is worth to highlight that from 2008 the GW/m remains mostly unchanged until 2016; as said before the swing 2013-2015 is neutral to the analysis.

Compressor Inspection in Switzerland

Compressor and pumps are two rotating equipments that carry fluids inside a plant or circuit.

Two of the most common compressor used in industry are centrifugal and reciprocating, depending on the duty they are involved. Also axial compressor and screw are used in some applications.

For testing, exists two reference standards API 617 for centrifugal compressors and API 618 for reciprocating compressors. In both documents there is a dedicated section for inspection requirements, but the client can decide the extention of the inspecting activities.

We as a company have a vast experience with inspecting compressors, both centrifugal and reciprocating whose have some activities in common and some specific for their category. Starting from the very beginning of the construction phase, we assisted hydrostatic pressure test of the casing, that can house the cylinder in case of reciprocating compressor or the impellers in case of centrifugal compressor.

Centrifugal Compressor

Successively overspeed and balancing of the impeller is key step in ensuring compressor performance. Assisting to this step is very important because allows to verify the fundamental frequency of the impeller which is important for maintenance and performance analysis.

After balancing, performance and running test are performed. Performance test scope is to simulate process condition at supplier shop and determine the behaviour in terms of polytropic head and thermodynamic efficiency. To achieve this, there is a sequence of steps to follow in order to get the nearest result of the behaviour compressor can have under process condition.

On the other side, running test scope is to determine reliability/endurance behaviour of the compressor. After completion of both performance and running test, inspection of the bearings is done to verify wearing, scratches that are caused by tests.

Final stage is assembly and final inspection.

Being based in Switzerland, we have the assignment to witness tests from the first step to the final stage, packing

Reciprocating compressor

Reciprocating compressor inspection, starts with hydrostatic test of the casing that will house the cylinders. After hydrostatic, air & helium test are done to fully determine possible leaks.

Performance test is a key step for evaluate compressor behaviour and also cylinder head inspection is needed. In contrast with centrifugal compressor, after running test, piston allignment need to be measured and verify if in tolerance.

Packing is the last activity to do by checking tools and spare parts provision.

Hinkley Point C – Blade construction Inspection

Hinkley Point C nuclear power station (HPC) is a project to construct a 3,200 MWe nuclear power station with two EPR reactors in Somerset, England.

The site was one of eight announced by the British government in 2010 and in November 2012 a nuclear site licence was granted.

Power generation is made by two GE Arabelle nuclear steam turbine. One of the most important components in power generation by turbine is the shape of the blade.

As based a company based in switzerland, we were chosen to follow construction of blade of the 1st stage of the turbine by witnessing forming, welding, NDE and dimensional check.

Finished blades

Blades (airfoils) were made in Switzerland by a Swiss manufacturer specialized in airfoil construction for different applications, ranging from energy production to aviation.

Airfoil is made by shaping two plates, one for high pressure side and another for lower pressure side. After forming, the two halves are welded at the leading edge and trailing edge.

Finally after machining airfoil get his final shape and can be inspected for weld defects, geometrical deviations and surface condition.

Sellafield project – Weld Supervising

After 2 interviews with Sellafield representative our company was involved as Tier 5 on full time basis in supervising weld activities, NDE & FAT testing 5 gate valves intended for HVAC system lifetime operational. The valves were fabricated in Switzerland, Basel area.

Sellafield, located 500 km north London, is the biggest nuclear site in Europe. Covering 265 hectares, comprises 200 nuclear facilities, 1000 buildings and 10.000 employees.

Starting from 2003, nuclear production of power generation was shut down leaving operative facilities for reprocessing or storage of spent nuclear fuel and/or nuclear waste coming from Europe.

The site is due to be fully decommissioned in 2120.

The Project

The Box Encapsulation Plant Delivery Team is an unincorporated joint venture of Amec Foster Wheeler, Balfour Beatty and Jacobs.

The framework contract for the project was awarded in October 2014 and is being delivered as an integral part of the Magnox Swarf Storage Silo (MSSS) programme for Sellafield Ltd, which is tackling the clean-up of one of the most hazardous legacy facilities on the Sellafield site.

When complete BEP will deliver the capability to treat nuclear waste recovered from MSSS, immobilise it and prepare it for storage. In addition, the BEP may also process waste recovered during the decommissioning of other Sellafield facilities including the First Generation Magnox Storage Pond (FGMSP) and the Pile Fuel Storage Pond (PFSP).


After 2 interviews with Sellafield representative our company was involved on full time basis in supervising welding activities, NDE & FAT testing 5 gate valves intended for HVAC system lifetime operational. The valves were fabricated in Switzerland, Basel area.

According to Nuclear QA grading, the valves (or dampers) were classified with a quality grade 2:

Failure is likely to lead to a MAJOR but less serious radiological risk


cause serious injury to persons


lead to a breach of the Site Licence or Environmental or Statutory requirements


lead to SIGNIFICANT cost penalty


The construction of the valve isin 304L, 5 mm plate with metal-to-metal sealing and removable internal mechanic blade.

Welding process was divided in 3 stages to avoid deformation due to high precision required to ensure -0.5 mbar vacuum.

The first stage isthe fit-up; the second stage consist in more than 300 welds seams with different lengths, third stage only minor welds.

The welding process was manual TIG or GTAW with only one approved weld position, having an impact on the handling of the damper with final weight of 350 kg. One of the key parts of welding was the colour of the weld and the grade of inerting/shielding.

First weld layer was monitored in terms of forming gas flow rate, weld seam length (max. 100 mm) and welding parameters. Since back gouging was not practical due to low space, the entire body was sealed and inerted with forming gas. An oximeter was used for monitoring the quantity of oxygen generated during welding.

Surface wet pickling was not practicable due to impossibility to ensure water full dryness so the final surface condition was glassblasted (100 microns glass microsphere). A test was done the verify the removal power of the glass against weld seam colour. It was found that the colour of the welds where the O2 was above 30 ppm, cannot be removed.

After 200 working days all 5 valves were completely welded.

Before testing, cleaning was achieved with solvent; the chemical composition of the pure inlet solvent stream was monitored and compared with the outlet wasted stream. When the difference between clean inlet & outlet contaminants was zero, the damper was considered fully clean.

Testing was aimed to check vacuum tightness with obtained values of zero flow rate passing to the seats.