{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "b97688d5-dbd8-451e-924b-902649ef3712",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import math"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "838b4878-cb24-4330-ac58-48de11ee1372",
"metadata": {},
"outputs": [
{
"data": {
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"
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" | \n",
" spkid | \n",
" pha | \n",
" H | \n",
" epoch_mjd | \n",
" e | \n",
" a | \n",
" i | \n",
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" w | \n",
" ma | \n",
" moid | \n",
"
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" 0 | \n",
" 20000433 | \n",
" N | \n",
" 10.41 | \n",
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" 0.2227 | \n",
" 1.458 | \n",
" 10.83 | \n",
" 304.28 | \n",
" 178.90 | \n",
" 334.73 | \n",
" 0.1500 | \n",
"
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" 1 | \n",
" 20000719 | \n",
" N | \n",
" 15.59 | \n",
" 60400 | \n",
" 0.5469 | \n",
" 2.636 | \n",
" 11.58 | \n",
" 183.85 | \n",
" 156.22 | \n",
" 102.37 | \n",
" 0.2010 | \n",
"
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" \n",
" 2 | \n",
" 20000887 | \n",
" N | \n",
" 13.88 | \n",
" 60400 | \n",
" 0.5710 | \n",
" 2.472 | \n",
" 9.40 | \n",
" 110.42 | \n",
" 350.48 | \n",
" 289.48 | \n",
" 0.0803 | \n",
"
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" \n",
" 3 | \n",
" 20001036 | \n",
" N | \n",
" 9.26 | \n",
" 60400 | \n",
" 0.5328 | \n",
" 2.665 | \n",
" 26.69 | \n",
" 215.50 | \n",
" 132.48 | \n",
" 321.69 | \n",
" 0.3450 | \n",
"
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" \n",
" 4 | \n",
" 20001221 | \n",
" N | \n",
" 17.38 | \n",
" 60400 | \n",
" 0.4352 | \n",
" 1.920 | \n",
" 11.88 | \n",
" 171.31 | \n",
" 26.68 | \n",
" 197.64 | \n",
" 0.1080 | \n",
"
\n",
" \n",
"
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"
"
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"text/plain": [
" spkid pha H epoch_mjd e a i om w \\\n",
"0 20000433 N 10.41 60400 0.2227 1.458 10.83 304.28 178.90 \n",
"1 20000719 N 15.59 60400 0.5469 2.636 11.58 183.85 156.22 \n",
"2 20000887 N 13.88 60400 0.5710 2.472 9.40 110.42 350.48 \n",
"3 20001036 N 9.26 60400 0.5328 2.665 26.69 215.50 132.48 \n",
"4 20001221 N 17.38 60400 0.4352 1.920 11.88 171.31 26.68 \n",
"\n",
" ma moid \n",
"0 334.73 0.1500 \n",
"1 102.37 0.2010 \n",
"2 289.48 0.0803 \n",
"3 321.69 0.3450 \n",
"4 197.64 0.1080 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"folder='/home/unipi/v.vichi3/Desktop/'\n",
"df=pd.read_csv(folder+'sbdb_query_results.csv')\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "7f165f80-3253-49b0-b43c-a8722f60e57b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(34901, 11)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.shape"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c41deece-a459-4ef3-8c83-0f87756dac92",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['spkid', 'pha', 'H', 'epoch_mjd', 'e', 'a', 'i', 'om', 'w', 'ma',\n",
" 'moid'],\n",
" dtype='object')"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.columns"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "f91e7f7c-4d5a-44c8-b0ba-9c2b71a01839",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"RangeIndex: 34901 entries, 0 to 34900\n",
"Data columns (total 11 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 spkid 34901 non-null int64 \n",
" 1 pha 34875 non-null object \n",
" 2 H 34897 non-null float64\n",
" 3 epoch_mjd 34901 non-null int64 \n",
" 4 e 34901 non-null float64\n",
" 5 a 34901 non-null float64\n",
" 6 i 34901 non-null float64\n",
" 7 om 34901 non-null float64\n",
" 8 w 34901 non-null float64\n",
" 9 ma 34901 non-null float64\n",
" 10 moid 34876 non-null float64\n",
"dtypes: float64(8), int64(2), object(1)\n",
"memory usage: 2.9+ MB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "eb543294-e46b-431e-862a-a0244cadd9fc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(34876, 11)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Eliminate the null values\n",
"df.drop(df[df['moid'].isna()].index,inplace=True)\n",
"df.reset_index(drop=True,inplace=True)\n",
"df.shape"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "e4ad2c21-bd10-4714-9d9a-aeb4ed639b36",
"metadata": {},
"outputs": [
{
"data": {
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"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" spkid | \n",
" H | \n",
" epoch_mjd | \n",
" e | \n",
" a | \n",
" i | \n",
" om | \n",
" w | \n",
" ma | \n",
" moid | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 3.487600e+04 | \n",
" 34872.000000 | \n",
" 34876.000000 | \n",
" 34876.000000 | \n",
" 34876.000000 | \n",
" 34876.000000 | \n",
" 34876.000000 | \n",
" 34876.000000 | \n",
" 34876.000000 | \n",
" 3.487600e+04 | \n",
"
\n",
" \n",
" mean | \n",
" 2.359880e+07 | \n",
" 23.486083 | \n",
" 59701.479986 | \n",
" 0.437249 | \n",
" 1.764192 | \n",
" 12.005071 | \n",
" 171.924096 | \n",
" 182.571561 | \n",
" 171.755088 | \n",
" 8.552434e-02 | \n",
"
\n",
" \n",
" std | \n",
" 2.362820e+07 | \n",
" 2.894608 | \n",
" 1572.136162 | \n",
" 0.176989 | \n",
" 2.117845 | \n",
" 10.694688 | \n",
" 103.659852 | \n",
" 104.303965 | \n",
" 122.272791 | \n",
" 9.834009e-02 | \n",
"
\n",
" \n",
" min | \n",
" 3.001703e+06 | \n",
" 9.260000 | \n",
" 44221.000000 | \n",
" 0.002800 | \n",
" 0.461700 | \n",
" 0.010000 | \n",
" 0.010000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 4.540000e-07 | \n",
"
\n",
" \n",
" 25% | \n",
" 3.701855e+06 | \n",
" 21.320000 | \n",
" 59976.000000 | \n",
" 0.304500 | \n",
" 1.294000 | \n",
" 4.420000 | \n",
" 80.380000 | \n",
" 93.357500 | \n",
" 49.480000 | \n",
" 1.280000e-02 | \n",
"
\n",
" \n",
" 50% | \n",
" 3.843806e+06 | \n",
" 23.800000 | \n",
" 60400.000000 | \n",
" 0.451700 | \n",
" 1.693000 | \n",
" 8.490000 | \n",
" 171.660000 | \n",
" 184.530000 | \n",
" 164.700000 | \n",
" 4.520000e-02 | \n",
"
\n",
" \n",
" 75% | \n",
" 5.416717e+07 | \n",
" 25.600000 | \n",
" 60400.000000 | \n",
" 0.565000 | \n",
" 2.172000 | \n",
" 16.810000 | \n",
" 252.402500 | \n",
" 272.662500 | \n",
" 291.902500 | \n",
" 1.280000e-01 | \n",
"
\n",
" \n",
" max | \n",
" 5.443990e+07 | \n",
" 33.580000 | \n",
" 60435.000000 | \n",
" 0.996200 | \n",
" 332.600000 | \n",
" 165.580000 | \n",
" 359.980000 | \n",
" 359.960000 | \n",
" 360.000000 | \n",
" 7.080000e-01 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" spkid H epoch_mjd e a \\\n",
"count 3.487600e+04 34872.000000 34876.000000 34876.000000 34876.000000 \n",
"mean 2.359880e+07 23.486083 59701.479986 0.437249 1.764192 \n",
"std 2.362820e+07 2.894608 1572.136162 0.176989 2.117845 \n",
"min 3.001703e+06 9.260000 44221.000000 0.002800 0.461700 \n",
"25% 3.701855e+06 21.320000 59976.000000 0.304500 1.294000 \n",
"50% 3.843806e+06 23.800000 60400.000000 0.451700 1.693000 \n",
"75% 5.416717e+07 25.600000 60400.000000 0.565000 2.172000 \n",
"max 5.443990e+07 33.580000 60435.000000 0.996200 332.600000 \n",
"\n",
" i om w ma moid \n",
"count 34876.000000 34876.000000 34876.000000 34876.000000 3.487600e+04 \n",
"mean 12.005071 171.924096 182.571561 171.755088 8.552434e-02 \n",
"std 10.694688 103.659852 104.303965 122.272791 9.834009e-02 \n",
"min 0.010000 0.010000 0.000000 0.000000 4.540000e-07 \n",
"25% 4.420000 80.380000 93.357500 49.480000 1.280000e-02 \n",
"50% 8.490000 171.660000 184.530000 164.700000 4.520000e-02 \n",
"75% 16.810000 252.402500 272.662500 291.902500 1.280000e-01 \n",
"max 165.580000 359.980000 359.960000 360.000000 7.080000e-01 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "292a8389-dcdb-4381-a547-0426c56b8fb0",
"metadata": {},
"outputs": [
{
"data": {
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" 6483 | \n",
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" N | \n",
" 24.11 | \n",
" 54767 | \n",
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" 32.39 | \n",
" 213.81 | \n",
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" 357.31 | \n",
" 0.1090 | \n",
"
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" 3683246 | \n",
" N | \n",
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" 93.63 | \n",
" 338.57 | \n",
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" 35.25 | \n",
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" 3766081 | \n",
" N | \n",
" 16.27 | \n",
" 57742 | \n",
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" 145.50 | \n",
" 165.97 | \n",
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" N | \n",
" 21.20 | \n",
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" 0.9962 | \n",
" 332.600 | \n",
" 108.34 | \n",
" 219.67 | \n",
" 151.26 | \n",
" 0.39 | \n",
" 0.3330 | \n",
"
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" 19835 | \n",
" 3840692 | \n",
" N | \n",
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" 340.62 | \n",
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"
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" 20634 | \n",
" 3843547 | \n",
" N | \n",
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" 60400 | \n",
" 0.7984 | \n",
" 5.774 | \n",
" 10.98 | \n",
" 348.98 | \n",
" 57.12 | \n",
" 114.87 | \n",
" 0.2340 | \n",
"
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" \n",
" 20682 | \n",
" 3843840 | \n",
" N | \n",
" 18.17 | \n",
" 58729 | \n",
" 0.9789 | \n",
" 59.680 | \n",
" 159.03 | \n",
" 187.95 | \n",
" 176.27 | \n",
" 0.09 | \n",
" 0.2580 | \n",
"
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" \n",
" 20698 | \n",
" 3843628 | \n",
" N | \n",
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" 5.693 | \n",
" 13.57 | \n",
" 252.31 | \n",
" 75.55 | \n",
" 122.88 | \n",
" 0.3770 | \n",
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" \n",
" 20742 | \n",
" 3843716 | \n",
" N | \n",
" 20.05 | \n",
" 60400 | \n",
" 0.7984 | \n",
" 5.775 | \n",
" 10.96 | \n",
" 348.94 | \n",
" 57.16 | \n",
" 114.83 | \n",
" 0.2330 | \n",
"
\n",
" \n",
" 22110 | \n",
" 3989287 | \n",
" N | \n",
" 18.12 | \n",
" 60400 | \n",
" 0.9213 | \n",
" 7.701 | \n",
" 165.58 | \n",
" 105.87 | \n",
" 57.80 | \n",
" 66.15 | \n",
" 0.0817 | \n",
"
\n",
" \n",
" 28090 | \n",
" 54240416 | \n",
" N | \n",
" 18.61 | \n",
" 60400 | \n",
" 0.8883 | \n",
" 9.983 | \n",
" 4.72 | \n",
" 77.69 | \n",
" 298.05 | \n",
" 26.08 | \n",
" 0.1390 | \n",
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\n",
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"text/plain": [
" spkid pha H epoch_mjd e a i om \\\n",
"3510 3024715 Y 17.69 60400 0.9480 17.800 19.67 48.69 \n",
"6483 3434371 N 24.11 54767 0.9060 7.315 32.39 213.81 \n",
"11522 3683246 N 20.00 60400 0.9407 21.440 93.63 338.57 \n",
"15455 3766081 N 16.27 57742 0.9919 153.200 145.50 165.97 \n",
"17114 3799259 N 21.20 60400 0.9962 332.600 108.34 219.67 \n",
"19835 3840692 N 22.61 60400 0.9889 96.930 139.83 340.62 \n",
"20634 3843547 N 18.68 60400 0.7984 5.774 10.98 348.98 \n",
"20682 3843840 N 18.17 58729 0.9789 59.680 159.03 187.95 \n",
"20698 3843628 N 21.20 60400 0.7734 5.693 13.57 252.31 \n",
"20742 3843716 N 20.05 60400 0.7984 5.775 10.96 348.94 \n",
"22110 3989287 N 18.12 60400 0.9213 7.701 165.58 105.87 \n",
"28090 54240416 N 18.61 60400 0.8883 9.983 4.72 77.69 \n",
"\n",
" w ma moid \n",
"3510 333.32 117.04 0.0111 \n",
"6483 263.82 357.31 0.1090 \n",
"11522 311.75 35.25 0.4590 \n",
"15455 77.94 360.00 0.5970 \n",
"17114 151.26 0.39 0.3330 \n",
"19835 193.09 1.90 0.1010 \n",
"20634 57.12 114.87 0.2340 \n",
"20682 176.27 0.09 0.2580 \n",
"20698 75.55 122.88 0.3770 \n",
"20742 57.16 114.83 0.2330 \n",
"22110 57.80 66.15 0.0817 \n",
"28090 298.05 26.08 0.1390 "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[df['a']>5]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "11f926f6-ee7c-47f1-82ae-1c5299e219f3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(34864, 11)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#We eliminate the values with a>5\n",
"df.drop(df[df['a']>5].index,inplace=True)\n",
"df.reset_index(drop=True,inplace=True)\n",
"df.shape"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "d1203169-ac0c-4d03-9dac-ebd136cd7680",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" spkid | \n",
" H | \n",
" epoch_mjd | \n",
" e | \n",
" a | \n",
" i | \n",
" om | \n",
" w | \n",
" ma | \n",
" moid | \n",
"
\n",
" \n",
" \n",
" \n",
" count | \n",
" 3.486400e+04 | \n",
" 34860.000000 | \n",
" 34864.000000 | \n",
" 34864.000000 | \n",
" 34864.000000 | \n",
" 34864.000000 | \n",
" 34864.000000 | \n",
" 34864.000000 | \n",
" 34864.000000 | \n",
" 3.486400e+04 | \n",
"
\n",
" \n",
" mean | \n",
" 2.360419e+07 | \n",
" 23.487377 | \n",
" 59701.525298 | \n",
" 0.437086 | \n",
" 1.744036 | \n",
" 11.983268 | \n",
" 171.907288 | \n",
" 182.575511 | \n",
" 171.776436 | \n",
" 8.546965e-02 | \n",
"
\n",
" \n",
" std | \n",
" 2.362906e+07 | \n",
" 2.893991 | \n",
" 1572.100889 | \n",
" 0.176795 | \n",
" 0.556275 | \n",
" 10.567228 | \n",
" 103.655813 | \n",
" 104.304053 | \n",
" 122.267979 | \n",
" 9.826509e-02 | \n",
"
\n",
" \n",
" min | \n",
" 3.001703e+06 | \n",
" 9.260000 | \n",
" 44221.000000 | \n",
" 0.002800 | \n",
" 0.461700 | \n",
" 0.010000 | \n",
" 0.010000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 4.540000e-07 | \n",
"
\n",
" \n",
" 25% | \n",
" 3.701855e+06 | \n",
" 21.330000 | \n",
" 59976.000000 | \n",
" 0.304400 | \n",
" 1.294000 | \n",
" 4.420000 | \n",
" 80.377500 | \n",
" 93.367500 | \n",
" 49.525000 | \n",
" 1.280000e-02 | \n",
"
\n",
" \n",
" 50% | \n",
" 3.843818e+06 | \n",
" 23.800000 | \n",
" 60400.000000 | \n",
" 0.451600 | \n",
" 1.692000 | \n",
" 8.490000 | \n",
" 171.650000 | \n",
" 184.545000 | \n",
" 164.730000 | \n",
" 4.520000e-02 | \n",
"
\n",
" \n",
" 75% | \n",
" 5.416727e+07 | \n",
" 25.600000 | \n",
" 60400.000000 | \n",
" 0.564900 | \n",
" 2.171000 | \n",
" 16.802500 | \n",
" 252.400000 | \n",
" 272.662500 | \n",
" 291.915000 | \n",
" 1.280000e-01 | \n",
"
\n",
" \n",
" max | \n",
" 5.443990e+07 | \n",
" 33.580000 | \n",
" 60435.000000 | \n",
" 0.970300 | \n",
" 4.816000 | \n",
" 154.350000 | \n",
" 359.980000 | \n",
" 359.960000 | \n",
" 360.000000 | \n",
" 7.080000e-01 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" spkid H epoch_mjd e a \\\n",
"count 3.486400e+04 34860.000000 34864.000000 34864.000000 34864.000000 \n",
"mean 2.360419e+07 23.487377 59701.525298 0.437086 1.744036 \n",
"std 2.362906e+07 2.893991 1572.100889 0.176795 0.556275 \n",
"min 3.001703e+06 9.260000 44221.000000 0.002800 0.461700 \n",
"25% 3.701855e+06 21.330000 59976.000000 0.304400 1.294000 \n",
"50% 3.843818e+06 23.800000 60400.000000 0.451600 1.692000 \n",
"75% 5.416727e+07 25.600000 60400.000000 0.564900 2.171000 \n",
"max 5.443990e+07 33.580000 60435.000000 0.970300 4.816000 \n",
"\n",
" i om w ma moid \n",
"count 34864.000000 34864.000000 34864.000000 34864.000000 3.486400e+04 \n",
"mean 11.983268 171.907288 182.575511 171.776436 8.546965e-02 \n",
"std 10.567228 103.655813 104.304053 122.267979 9.826509e-02 \n",
"min 0.010000 0.010000 0.000000 0.000000 4.540000e-07 \n",
"25% 4.420000 80.377500 93.367500 49.525000 1.280000e-02 \n",
"50% 8.490000 171.650000 184.545000 164.730000 4.520000e-02 \n",
"75% 16.802500 252.400000 272.662500 291.915000 1.280000e-01 \n",
"max 154.350000 359.980000 359.960000 360.000000 7.080000e-01 "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.describe()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "17be8338-6c23-4cc9-ae08-d1ab7f705a79",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of PHAs: 2421\n",
"Percentage of PHAs: 6.944125745754933\n"
]
}
],
"source": [
"#Count the number of PHAs in the dataset\n",
"print(\"Number of PHAs:\", np.count_nonzero(df['pha']=='Y'))\n",
"print(\"Percentage of PHAs:\", 100*np.count_nonzero(df['pha']=='Y')/df.shape[0])"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "cafcc865-5058-4a84-932b-8dcf95a5dcd4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of asteroids with MOID=0: 0\n",
"Number of asteroids with MOID < 0.05: 18275\n"
]
}
],
"source": [
"#Number of asteroids with MOID=0 and MOID <0.05\n",
"print(\"Number of asteroids with MOID=0:\", len(df[df['moid']==0.0]))\n",
"print(\"Number of asteroids with MOID < 0.05:\", len(df[df['moid']<0.05]))"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "cb2545a2-9961-4118-a2e3-94647adc4d85",
"metadata": {},
"outputs": [
{
"data": {
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",
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