Hi, This seems again to be a topic wandering. Was the original question whether Python could be used for dealing with Seismic data of some unspecified sort as in PROCESSING it and now we are debating how to clean various aspects of data and make things like data.frames and extract subsets for analysis?
Plenty of the above can be done in any number of places ranging from languages like Python and R to databases and SQL. If the result you want to analyze can then be written in a format with rows and columns containing the usual suspects like numbers and text and dates and so on, then this part of the job can be done anywhere you want. And when you have assembled your data and now want to make a query to generate a subset such as data in a date range that is from a set of measuring stations and with other qualities, then you can simply save the data to a file in whatever format, often something like a .CSV. It is the following steps where you want to choose your language based on what is available. Are you using features like a time series, for example? Are you looking or periodicity. Is graphing a major aspect and do you need some obscure graph types not easily found but that are parts of packages/modules in some language like R or Python? Do you need the analysis to have interactive aspects such as from a GUI, or a web page? Does any aspect of your work include things like statistical analyses or machine learning? The list goes on. As mentioned, people who do lots of stuff along these lines can share some tools in python, or elsewhere, they find useful and that might help fit the needs of the OP but they work best when they have a better idea of what exactly you want to do. Part of what I gleaned, was a want to do a 3-D graph that rotates. Python has multiple graphics packages and so on as do languages like R. The likelihood of finding something useful goes up if you identify if there are communities of people doing similar work and can share some of their tools. Hence the idea of focused searches. Asking here will largely get you people mainly who use Python and if it turns out R or something entirely else meets your needs better, perhaps Mathematica even if you have to pay for it if that is expected by your peers. My guess is that python would be a decent choice as it can do almost anything, but for practical purposes, you do not want to stick with what is in the base and probably want to use extensions like numpy/pandas and perhaps others like scipy and if doing graphics, there are too many including matplotlib and seaborn but you may need something specialized for your needs. I cannot stress the importance of making sure the people evaluating and using your work can handle it. Python is fairly mainstream and free enough that it can foot your bill. But it has various versions and clearly nobody would advise you to use version 2. Some versions are packaged with many of the tools you may want to use, such as Anaconda. It depends on your level of expertise already and how much you want to learn to get this task done. You make it sound like your kind of work must be done alone, and that can simplify things but also mean more work for you. -----Original Message----- From: Python-list <python-list-bounces+avi.e.gross=gmail....@python.org> On Behalf Of Thomas Passin Sent: Monday, March 13, 2023 2:10 PM To: python-list@python.org Subject: Re: Can you process seismographic signals in Python or should I switch to Matlab ? On 3/13/2023 11:54 AM, Rich Shepard wrote:> On Mon, 13 Mar 2023, Thomas Passin wrote: > >> No doubt, depending on the data formats used. But it's still going >> to be a big task. > > Thomas, > > True, but once you have a dataframe with all the information about > all the earthquakes you can extract data for every analysis you want > to do. This message would better have gone to the list instead of just me. I'm not saying that Pandas is a bad choice! I'm saying that getting all that data into shape so that it can be ingested into a usable dataframe will be a lot of hard work. > If you've not read Wes McKinney's "Python for Data Analysis: Data > Wrangling with Pandas, NumPy, and IPython" I encourage you to do so. I've been interested in that title, but since I don't currently have any large, complex data wrangling problems I've put it off. -- https://mail.python.org/mailman/listinfo/python-list -- https://mail.python.org/mailman/listinfo/python-list
