This tutorial will demonstrate the basic steps required to recover the signal of Kepler-10b, the first rocky planet that was discovered by Kepler!

Let’s start by downloading the pixel data for this target for one of Kepler’s observing quarters:

```
[1]:
```

```
import lightkurve as lk
tpf = lk.search_targetpixelfile("Kepler-10", quarter=3).download()
```

Let’s use the `plot`

method to show the pixel data at one point in time (frame index 100). We’ll also pass along a few plotting arguments.

```
[2]:
```

```
tpf.plot(frame=100, scale='log', show_colorbar=True);
```

The target pixel file appears to show one bright star with a core brightness of approximately 50,000 electrons/seconds.

Now, we will use the `to_lightcurve`

method to create a simple aperture photometry lightcurve using the mask defined by the pipeline which is stored in `tpf.pipeline_mask`

.

```
[3]:
```

```
lc = tpf.to_lightcurve(aperture_mask=tpf.pipeline_mask)
```

Let’s take a look at the output lightcurve.

```
[4]:
```

```
lc.plot();
```

Now let’s use the `flatten`

method, which removes long-term variability that we are not interested in using a high-pass filter called *Savitzky-Golay*.

```
[5]:
```

```
flat, trend = lc.flatten(window_length=301, return_trend=True)
```

Let’s plot the trend estimated in red:

```
[6]:
```

```
ax = lc.errorbar(label="Kepler-10") # plot() returns a matplotlib axes ...
trend.plot(ax=ax, color='red', lw=2, label='Trend'); # which we can pass to the next plot() to use the same axes
```

and the flat lightcurve:

```
[7]:
```

```
flat.errorbar(label="Kepler-10");
```

Now, let’s run a period search function using the well-known Box-Least Squares algorithm (BLS), which was added to the AstroPy package in version 3.1.

We will use the BLS algorithm to search a pre-defined grid of transit periods:

```
[8]:
```

```
import numpy as np
periodogram = flat.to_periodogram(method="bls", period=np.arange(0.3, 1.5, 0.001))
periodogram.plot();
```

It looks like we found a strong signal with a periodicity of 0.8 days!

```
[9]:
```

```
best_fit_period = periodogram.period_at_max_power
print('Best fit period: {:.3f}'.format(best_fit_period))
```

```
Best fit period: 0.837 d
```

```
[10]:
```

```
flat.fold(period=best_fit_period, t0=periodogram.transit_time_at_max_power).errorbar();
```

We successfully recovered the planet!