mirror of
https://github.com/AllenDowney/AstronomicalData.git
synced 2026-07-28 22:50:53 -07:00
Revising notebooks
This commit is contained in:
Allen Downey
+276
-422
File diff suppressed because it is too large
Load Diff
+2
-2
@@ -4,7 +4,7 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Chapter 2\n",
|
||||
"# Coordinates and units\n",
|
||||
"\n",
|
||||
"This is the second in a series of notebooks related to astronomy data.\n",
|
||||
"\n",
|
||||
@@ -75,7 +75,7 @@
|
||||
"IN_COLAB = 'google.colab' in sys.modules\n",
|
||||
"\n",
|
||||
"if IN_COLAB:\n",
|
||||
" !pip install astroquery astro-gala pyia"
|
||||
" !pip install astroquery astro-gala"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
+300
-78
@@ -79,7 +79,7 @@
|
||||
"IN_COLAB = 'google.colab' in sys.modules\n",
|
||||
"\n",
|
||||
"if IN_COLAB:\n",
|
||||
" !pip install astroquery astro-gala pyia python-wget"
|
||||
" !pip install astroquery astro-gala python-wget"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -331,7 +331,7 @@
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<i>Row index=0</i>\n",
|
||||
"<table id=\"table139758619539344\">\n",
|
||||
"<table id=\"table140419756472688\">\n",
|
||||
"<thead><tr><th>source_id</th><th>ra</th><th>dec</th><th>pmra</th><th>pmdec</th><th>parallax</th><th>parallax_error</th><th>radial_velocity</th></tr></thead>\n",
|
||||
"<thead><tr><th></th><th>deg</th><th>deg</th><th>mas / yr</th><th>mas / yr</th><th>mas</th><th>mas</th><th>km / s</th></tr></thead>\n",
|
||||
"<thead><tr><th>int64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
|
||||
@@ -555,64 +555,49 @@
|
||||
"\n",
|
||||
"To plot them, we will transform them back to the `GD1Koposov10` frame; that way, the axes of the figure are aligned with the GD-1, which will make it easy to select stars near the centerline of the stream.\n",
|
||||
"\n",
|
||||
"To do that, we'll put the results into a `GaiaData` object, provided by the [pyia library](https://pyia.readthedocs.io/en/latest/api/pyia.GaiaData.html).\n",
|
||||
"\n",
|
||||
"TODO: Do we need pyia, or could we do this with astropy and gala?"
|
||||
"To do that, we'll put the results into a `SkyCoord` object, \n",
|
||||
"which is an \"interface for celestial coordinate representation, manipulation, and transformation between systems\", provided by Astropy."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"pyia.data.GaiaData"
|
||||
]
|
||||
},
|
||||
"execution_count": 14,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from pyia import GaiaData\n",
|
||||
"\n",
|
||||
"gaia_data = GaiaData(results)\n",
|
||||
"type(gaia_data)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Now we can extract sky coordinates from the `GaiaData` object, like this:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"execution_count": 53,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import astropy.coordinates as coord\n",
|
||||
"import astropy.units as u\n",
|
||||
"\n",
|
||||
"skycoord = gaia_data.get_skycoord(\n",
|
||||
" distance=8*u.kpc, \n",
|
||||
" radial_velocity=0*u.km/u.s)"
|
||||
"skycoord = coord.SkyCoord(\n",
|
||||
" ra=results['ra'], \n",
|
||||
" dec=results['dec'],\n",
|
||||
" pm_ra_cosdec=results['pmra'],\n",
|
||||
" pm_dec=results['pmdec'], \n",
|
||||
" distance=8*u.kpc, \n",
|
||||
" radial_velocity=0*u.km/u.s)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We provide `distance` and `radial_velocity` to prepare the data for reflex correction, which we explain below."
|
||||
"Most of the arguments we send to `SkyCoord` come directly from `results`.\n",
|
||||
"\n",
|
||||
"We provide `distance` and `radial_velocity` to prepare the data for reflex correction, which we explain below.\n",
|
||||
"\n",
|
||||
"The result is a `SkyCoord` object ([documentation here](https://docs.astropy.org/en/stable/api/astropy.coordinates.SkyCoord.html#astropy.coordinates.SkyCoord))."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The result is an Astropy `SkyCoord` object."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"execution_count": 59,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -621,7 +606,7 @@
|
||||
"astropy.coordinates.sky_coordinate.SkyCoord"
|
||||
]
|
||||
},
|
||||
"execution_count": 16,
|
||||
"execution_count": 59,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@@ -634,12 +619,12 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"The result is an Astropy `SkyCoord` object ([documentation here](https://docs.astropy.org/en/stable/api/astropy.coordinates.SkyCoord.html#astropy.coordinates.SkyCoord)), which provides `transform_to`, so we can transform the coordinates to other frames."
|
||||
"`SkyCoord` provides `transform_to`, so we can transform the coordinates to other frames."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 17,
|
||||
"execution_count": 60,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -648,7 +633,7 @@
|
||||
"astropy.coordinates.sky_coordinate.SkyCoord"
|
||||
]
|
||||
},
|
||||
"execution_count": 17,
|
||||
"execution_count": 60,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@@ -695,7 +680,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 18,
|
||||
"execution_count": 61,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -704,7 +689,7 @@
|
||||
"astropy.coordinates.sky_coordinate.SkyCoord"
|
||||
]
|
||||
},
|
||||
"execution_count": 18,
|
||||
"execution_count": 61,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@@ -730,7 +715,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 19,
|
||||
"execution_count": 57,
|
||||
"metadata": {
|
||||
"scrolled": true
|
||||
},
|
||||
@@ -749,7 +734,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 20,
|
||||
"execution_count": 58,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -785,7 +770,7 @@
|
||||
"source": [
|
||||
"## Pandas DataFrame\n",
|
||||
"\n",
|
||||
"At this point we have three objects containing different subsets of the data."
|
||||
"At this point we have two objects containing different subsets of the data. `results` is the Astropy `Table` we downloaded from Gaia."
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -809,28 +794,15 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 22,
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"pyia.data.GaiaData"
|
||||
]
|
||||
},
|
||||
"execution_count": 22,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"type(gaia_data)"
|
||||
"And `gd1_coord` is a `SkyCoord` object that contains the transformed coordinates and proper motions."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 23,
|
||||
"execution_count": 63,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -839,7 +811,7 @@
|
||||
"astropy.coordinates.sky_coordinate.SkyCoord"
|
||||
]
|
||||
},
|
||||
"execution_count": 23,
|
||||
"execution_count": 63,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@@ -852,7 +824,7 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"On one hand, this makes sense, since each object provides different capabilities. But working with three different object types can be awkward.\n",
|
||||
"On one hand, this division of labor makes sense because each object provides different capabilities. But working with multiple object types can be awkward.\n",
|
||||
"\n",
|
||||
"It will be more convenient to choose one object and get all of the data into it. We'll use a Pandas DataFrame, for two reasons:\n",
|
||||
"\n",
|
||||
@@ -1027,7 +999,7 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Python detail: `shape` is an attribute, so we can display it's value without calling it as a function; `head` is a function, so we need the parentheses."
|
||||
"Python detail: `shape` is an attribute, so we display its value without calling it as a function; `head` is a function, so we need the parentheses."
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -1039,16 +1011,16 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 26,
|
||||
"execution_count": 64,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"(140340, 10)"
|
||||
"(140340, 12)"
|
||||
]
|
||||
},
|
||||
"execution_count": 26,
|
||||
"execution_count": 64,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@@ -1068,7 +1040,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 27,
|
||||
"execution_count": 65,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@@ -1077,7 +1049,7 @@
|
||||
"(140340, 12)"
|
||||
]
|
||||
},
|
||||
"execution_count": 27,
|
||||
"execution_count": 65,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@@ -1097,6 +1069,256 @@
|
||||
"We could have: `proper_motion` contains the same data as `pm_phi1_cosphi2` and `pm_phi2`, but in a different format."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Exploring data\n",
|
||||
"\n",
|
||||
"One benefit of using Pandas is that it provides function for exploring the data and checking for problems.\n",
|
||||
"\n",
|
||||
"One of the most useful of these functions is `describe`, which computes summary statistics for each column."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 66,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>source_id</th>\n",
|
||||
" <th>ra</th>\n",
|
||||
" <th>dec</th>\n",
|
||||
" <th>pmra</th>\n",
|
||||
" <th>pmdec</th>\n",
|
||||
" <th>parallax</th>\n",
|
||||
" <th>parallax_error</th>\n",
|
||||
" <th>radial_velocity</th>\n",
|
||||
" <th>phi1</th>\n",
|
||||
" <th>phi2</th>\n",
|
||||
" <th>pm_phi1</th>\n",
|
||||
" <th>pm_phi2</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>count</th>\n",
|
||||
" <td>1.403400e+05</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>1.403400e+05</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" <td>140340.000000</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>mean</th>\n",
|
||||
" <td>6.792378e+17</td>\n",
|
||||
" <td>143.822971</td>\n",
|
||||
" <td>26.780161</td>\n",
|
||||
" <td>-2.484410</td>\n",
|
||||
" <td>-6.100784</td>\n",
|
||||
" <td>0.179474</td>\n",
|
||||
" <td>0.518068</td>\n",
|
||||
" <td>9.931167e+19</td>\n",
|
||||
" <td>-50.091337</td>\n",
|
||||
" <td>-1.803264</td>\n",
|
||||
" <td>-0.868980</td>\n",
|
||||
" <td>1.409215</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>std</th>\n",
|
||||
" <td>3.792015e+16</td>\n",
|
||||
" <td>3.697824</td>\n",
|
||||
" <td>3.052639</td>\n",
|
||||
" <td>5.913923</td>\n",
|
||||
" <td>7.202013</td>\n",
|
||||
" <td>0.759622</td>\n",
|
||||
" <td>0.505558</td>\n",
|
||||
" <td>8.267982e+18</td>\n",
|
||||
" <td>2.892321</td>\n",
|
||||
" <td>3.444439</td>\n",
|
||||
" <td>6.657700</td>\n",
|
||||
" <td>6.518573</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>min</th>\n",
|
||||
" <td>6.214900e+17</td>\n",
|
||||
" <td>135.425699</td>\n",
|
||||
" <td>19.286617</td>\n",
|
||||
" <td>-106.755260</td>\n",
|
||||
" <td>-138.065163</td>\n",
|
||||
" <td>-15.287602</td>\n",
|
||||
" <td>0.020824</td>\n",
|
||||
" <td>-1.792684e+02</td>\n",
|
||||
" <td>-54.999989</td>\n",
|
||||
" <td>-8.029159</td>\n",
|
||||
" <td>-115.275637</td>\n",
|
||||
" <td>-161.150142</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>25%</th>\n",
|
||||
" <td>6.443515e+17</td>\n",
|
||||
" <td>140.967807</td>\n",
|
||||
" <td>24.592348</td>\n",
|
||||
" <td>-5.038746</td>\n",
|
||||
" <td>-8.341641</td>\n",
|
||||
" <td>-0.035983</td>\n",
|
||||
" <td>0.141108</td>\n",
|
||||
" <td>1.000000e+20</td>\n",
|
||||
" <td>-52.603097</td>\n",
|
||||
" <td>-4.750410</td>\n",
|
||||
" <td>-2.948851</td>\n",
|
||||
" <td>-1.107074</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>50%</th>\n",
|
||||
" <td>6.888056e+17</td>\n",
|
||||
" <td>143.734183</td>\n",
|
||||
" <td>26.746169</td>\n",
|
||||
" <td>-1.834971</td>\n",
|
||||
" <td>-4.689570</td>\n",
|
||||
" <td>0.362705</td>\n",
|
||||
" <td>0.336103</td>\n",
|
||||
" <td>1.000000e+20</td>\n",
|
||||
" <td>-50.147567</td>\n",
|
||||
" <td>-1.671497</td>\n",
|
||||
" <td>0.585038</td>\n",
|
||||
" <td>1.987196</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>75%</th>\n",
|
||||
" <td>6.976578e+17</td>\n",
|
||||
" <td>146.607180</td>\n",
|
||||
" <td>28.990490</td>\n",
|
||||
" <td>0.452995</td>\n",
|
||||
" <td>-1.937833</td>\n",
|
||||
" <td>0.657636</td>\n",
|
||||
" <td>0.751171</td>\n",
|
||||
" <td>1.000000e+20</td>\n",
|
||||
" <td>-47.593466</td>\n",
|
||||
" <td>1.160632</td>\n",
|
||||
" <td>3.001761</td>\n",
|
||||
" <td>4.628859</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>max</th>\n",
|
||||
" <td>7.974418e+17</td>\n",
|
||||
" <td>152.777393</td>\n",
|
||||
" <td>34.285481</td>\n",
|
||||
" <td>104.319923</td>\n",
|
||||
" <td>20.981070</td>\n",
|
||||
" <td>0.999957</td>\n",
|
||||
" <td>4.171221</td>\n",
|
||||
" <td>1.000000e+20</td>\n",
|
||||
" <td>-45.000086</td>\n",
|
||||
" <td>4.014794</td>\n",
|
||||
" <td>39.802471</td>\n",
|
||||
" <td>79.275199</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" source_id ra dec pmra \\\n",
|
||||
"count 1.403400e+05 140340.000000 140340.000000 140340.000000 \n",
|
||||
"mean 6.792378e+17 143.822971 26.780161 -2.484410 \n",
|
||||
"std 3.792015e+16 3.697824 3.052639 5.913923 \n",
|
||||
"min 6.214900e+17 135.425699 19.286617 -106.755260 \n",
|
||||
"25% 6.443515e+17 140.967807 24.592348 -5.038746 \n",
|
||||
"50% 6.888056e+17 143.734183 26.746169 -1.834971 \n",
|
||||
"75% 6.976578e+17 146.607180 28.990490 0.452995 \n",
|
||||
"max 7.974418e+17 152.777393 34.285481 104.319923 \n",
|
||||
"\n",
|
||||
" pmdec parallax parallax_error radial_velocity \\\n",
|
||||
"count 140340.000000 140340.000000 140340.000000 1.403400e+05 \n",
|
||||
"mean -6.100784 0.179474 0.518068 9.931167e+19 \n",
|
||||
"std 7.202013 0.759622 0.505558 8.267982e+18 \n",
|
||||
"min -138.065163 -15.287602 0.020824 -1.792684e+02 \n",
|
||||
"25% -8.341641 -0.035983 0.141108 1.000000e+20 \n",
|
||||
"50% -4.689570 0.362705 0.336103 1.000000e+20 \n",
|
||||
"75% -1.937833 0.657636 0.751171 1.000000e+20 \n",
|
||||
"max 20.981070 0.999957 4.171221 1.000000e+20 \n",
|
||||
"\n",
|
||||
" phi1 phi2 pm_phi1 pm_phi2 \n",
|
||||
"count 140340.000000 140340.000000 140340.000000 140340.000000 \n",
|
||||
"mean -50.091337 -1.803264 -0.868980 1.409215 \n",
|
||||
"std 2.892321 3.444439 6.657700 6.518573 \n",
|
||||
"min -54.999989 -8.029159 -115.275637 -161.150142 \n",
|
||||
"25% -52.603097 -4.750410 -2.948851 -1.107074 \n",
|
||||
"50% -50.147567 -1.671497 0.585038 1.987196 \n",
|
||||
"75% -47.593466 1.160632 3.001761 4.628859 \n",
|
||||
"max -45.000086 4.014794 39.802471 79.275199 "
|
||||
]
|
||||
},
|
||||
"execution_count": 66,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df.describe()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Exercise\n",
|
||||
"\n",
|
||||
"Review the summary statistics in this table.\n",
|
||||
"\n",
|
||||
"* Do the values makes senses based on what you know about the context?\n",
|
||||
"\n",
|
||||
"* Do you see any values that seem problematic, or evidence of other data issues?"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 68,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Solution\n",
|
||||
"\n",
|
||||
"# A few issues that are likely to come up:\n",
|
||||
"\n",
|
||||
"# 1. Why are some of the parallax values negative?\n",
|
||||
"# Some parallax measurements are inaccurate, especially\n",
|
||||
"# stars that are far away.\n",
|
||||
"\n",
|
||||
"# 2. Why are some of the radial velocities 1e20?\n",
|
||||
"# It seems like this value is used to indicate invalid data.\n",
|
||||
"# Notice that the 25th percentile is 1e20, which indicates\n",
|
||||
"# that at least 75% of these values are invalid."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
@@ -1441,12 +1663,12 @@
|
||||
"\n",
|
||||
"We'll use a simple rectangle for now, but in a later lesson we'll see how to select a polygonal region as well.\n",
|
||||
"\n",
|
||||
"Here are bounds on proper motion we chose by eye,"
|
||||
"Here are bounds on proper motion we chose by eye:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 38,
|
||||
"execution_count": 44,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
@@ -1465,7 +1687,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 39,
|
||||
"execution_count": 45,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
@@ -1482,7 +1704,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 40,
|
||||
"execution_count": 46,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
||||
+50
-329
File diff suppressed because one or more lines are too long
+10
-10
@@ -71,7 +71,7 @@
|
||||
"IN_COLAB = 'google.colab' in sys.modules\n",
|
||||
"\n",
|
||||
"if IN_COLAB:\n",
|
||||
" !pip install astroquery astro-gala pyia python-wget"
|
||||
" !pip install astroquery astro-gala python-wget"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -184,16 +184,16 @@
|
||||
"\n",
|
||||
"Fortunately, smart people have worked on this problem, and the Gaia database includes cross-matching tables that suggest a best neighbor in the Pan-STARRS catalog for many stars in the Gaia catalog.\n",
|
||||
"\n",
|
||||
"[This document describes the cross matching process](https://gea.esac.esa.int/archive/documentation/GDR2/Catalogue_consolidation/chap_cu9val_cu9val/ssec_cu9xma/sssec_cu9xma_extcat.html). Briefly, it uses a cone search to find possible matches in approximately the right position, then uses attributes like color and magnitude to choose pairs of stars most likely to be identical."
|
||||
"[This document describes the cross matching process](https://gea.esac.esa.int/archive/documentation/GDR2/Catalogue_consolidation/chap_cu9val_cu9val/ssec_cu9xma/sssec_cu9xma_extcat.html). Briefly, it uses a cone search to find possible matches in approximately the right position, then uses attributes like color and magnitude to choose pairs of observations most likely to be the same star."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"So the hard part of cross-matching has been done for us. However, using the results is a little tricky.\n",
|
||||
"## Joining tables\n",
|
||||
"\n",
|
||||
"But, it is also an opportunity to learn about one of the most important tools for working with databases: \"joining\" tables.\n",
|
||||
"So the hard part of cross-matching has been done for us. Using the results is a little tricky, but it gives us a chance to learn about one of the most important tools for working with databases: \"joining\" tables.\n",
|
||||
"\n",
|
||||
"In general, a \"join\" is an operation where you match up records from one table with records from another table using as a \"key\" a piece of information that is common to both tables, usually some kind of ID code.\n",
|
||||
"\n",
|
||||
@@ -285,8 +285,8 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"table = candidate_table[['source_id']]\n",
|
||||
"table.write('candidate_df.xml', format='votable', overwrite=True)"
|
||||
"table_id = candidate_table[['source_id']]\n",
|
||||
"table_id.write('candidate_df.xml', format='votable', overwrite=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -395,8 +395,8 @@
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"table = candidate_table[['source_id']]\n",
|
||||
"type(table)"
|
||||
"table_id = candidate_table[['source_id']]\n",
|
||||
"type(table_id)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -952,8 +952,8 @@
|
||||
"source": [
|
||||
"# Solution\n",
|
||||
"\n",
|
||||
"table = results1[['source_id', 'original_ext_source_id']]\n",
|
||||
"table.write('external.xml', format='votable', overwrite=True)"
|
||||
"table_ext = results1[['source_id', 'original_ext_source_id']]\n",
|
||||
"table_ext.write('external.xml', format='votable', overwrite=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
+509
-6
File diff suppressed because one or more lines are too long
+1
-1
@@ -69,7 +69,7 @@
|
||||
"IN_COLAB = 'google.colab' in sys.modules\n",
|
||||
"\n",
|
||||
"if IN_COLAB:\n",
|
||||
" !pip install astroquery astro-gala pyia python-wget"
|
||||
" !pip install astroquery astro-gala python-wget"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
Reference in New Issue
Block a user