I'm trying to read multiple CSV files from nightly observations. Each CSV file has a time and magnitude column and I want to be able to stack all my nightly files into a single Timeseries object.
It is very easy to do with a panda Dataframe (pd.concat()) but I cannot find a simple, elegant way with Astropy Timeseries.
I could write the merged file to disk or other solutions but I'm looking for a simple way. It must be doable within astropy Timeseries or Astropy Table I imagine.
Stacking multiple TimeSeries is a common use case.
I tried the following one:
from astropy.timeseries import TimeSeries
ts = TimeSeries.read('mydata.csv', format='ascii.csv',time_column='mjd',time_format='mjd')
ts2 = ts.add_row(vals=ts.values()) #imagine that I want to stack with another observation
Doing this throw my an Error :
ValueError: Unable to insert row because of exception in column 'time':
Any idea while staying in the astropy ecosystem ?
You can use the astropy.table.vstack function (see, e.g., here). For example, if I had two files data1.csv and data2.csv, containing:
mjd, mag
54668, 2.4
54669, 2.5
and
mjd, mag
54700, 2.6
54701, 2.7
respectively, I could do:
from astropy.table import vstack
from astropy.timeseries import TimeSeries
ts = TimeSeries.read("data1.csv", format="ascii.csv", time_column="mjd", time_format="mjd")
ts2 = TimeSeries.read("data2.csv", format="ascii.csv", time_column="mjd", time_format="mjd")
ts = vstack([ts, ts2])
print(ts)
time mag
------- ---
54668.0 2.4
54669.0 2.5
54700.0 2.6
54701.0 2.7