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If you have a working version of Python 2 or 3 on your system (we recommend Anaconda Python), you can simply install the latest stable release of the lightkurve package using pip:

$ pip install lightkurve

With lightkurve installed, it is easy to extract brightness time series data (astronomers call this a lightcurve) from the tiny images of stars collected by NASA’s Kepler and TESS planet-hunting telescopes.

For example, let’s download and display the pixels of a famous star named KIC 8462852, also known as Tabby’s Star or Boyajian’s Star, which is known to show unusual light fluctuations.

First, we start Python and use the search_targetpixelfile function to obtain the Kepler pixel data for the star from the data archive:

In [1]:
from lightkurve import search_targetpixelfile
pixelfile = search_targetpixelfile(8462852, quarter=16).download(quality_bitmask='hardest');

Next, let’s display the first image in this data set:

In [2]:

It looks like the star is an isolated object, so we can extract a lightcurve by simply summing up all the pixel values in each image:

In [3]:
lc = pixelfile.to_lightcurve(aperture_mask='all');

The above method returned a KeplerLightCurve object which gives us access to the flux over time, which are both available as array objects. The time is in units of days and the flux is in units electrons/second.

In [4]:
lc.time, lc.flux
(array([1472.11777934, 1472.13821223, 1472.15864492, ..., 1557.89718798,
        1557.9380561 , 1557.95849016]),
 array([258645.03, 258660.05, 258690.08, ..., 258929.86, 258884.66,
        258865.6 ], dtype=float32))

We can plot these data using the plot() method:

In [5]:

The plot reveals a short-lived 20% dip in the brightness of the star. It looks like we re-discovered one of the intriguing dips in Tabby’s star!

Created with ♥ by the Lightkurve developers. Join us on GitHub.