transform testing

This commit is contained in:
Gourav Kumar 2022-05-24 21:11:15 +05:30
parent 66ad448516
commit 9a71cdf355

View File

@ -478,7 +478,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 1,
"id": "aead3e77-2670-4541-846a-5537b01f3d2e",
"metadata": {},
"outputs": [],
@ -493,7 +493,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 2,
"id": "f287e05f",
"metadata": {},
"outputs": [],
@ -583,34 +583,34 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 12,
"id": "c85b5dd9-9a88-4608-ac58-1a141295f63f",
"metadata": {},
"outputs": [],
"source": [
"data = sample_data_generator(num=261, frequency=fc.AllFrequencies.W, mu=0.6, sigma=0.7)\n",
"data = sample_data_generator(num=261, frequency=fc.AllFrequencies.W)\n",
"ts = fc.TimeSeries(data, \"W\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 13,
"id": "0488a4d0-bca1-4341-9fae-1fd254adc0dc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"TimeSeries([(datetime.datetime(2017, 1, 1, 0, 0), 1040.39),\n",
"\t (datetime.datetime(2017, 1, 8, 0, 0), 1032.83),\n",
"\t (datetime.datetime(2017, 1, 15, 0, 0), 1120.5)\n",
"TimeSeries([(datetime.datetime(2017, 1, 1, 0, 0), 1003.03),\n",
"\t (datetime.datetime(2017, 1, 8, 0, 0), 1002.71),\n",
"\t (datetime.datetime(2017, 1, 15, 0, 0), 1008.77)\n",
"\t ...\n",
"\t (datetime.datetime(2021, 12, 12, 0, 0), 2007.18),\n",
"\t (datetime.datetime(2021, 12, 19, 0, 0), 1987.49),\n",
"\t (datetime.datetime(2021, 12, 26, 0, 0), 1924.2)], frequency='W')"
"\t (datetime.datetime(2021, 12, 12, 0, 0), 1107.21),\n",
"\t (datetime.datetime(2021, 12, 19, 0, 0), 1106.66),\n",
"\t (datetime.datetime(2021, 12, 26, 0, 0), 1104.32)], frequency='W')"
]
},
"execution_count": 5,
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@ -621,429 +621,71 @@
},
{
"cell_type": "code",
"execution_count": 6,
"id": "cd0eb38c",
"execution_count": 14,
"id": "04624145-4fce-484c-aa69-0d17d159b598",
"metadata": {},
"outputs": [],
"source": [
"dates = fc.create_date_series(ts.start_date, ts.end_date, 'M')"
"tst = ts.transform('Q', 'mean', False)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "69c48512",
"metadata": {},
"outputs": [],
"source": [
"prev_date = dates[0]\n",
"for i in dates[1:]:\n",
" cur_date = i\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "43fa2254",
"execution_count": 16,
"id": "75ed1666-5fc8-4707-bf42-62d44adcae18",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"TimeSeries([(datetime.datetime(2017, 1, 8, 0, 0), 1032.83),\n",
"\t(datetime.datetime(2017, 1, 15, 0, 0), 1120.5),\n",
"\t(datetime.datetime(2017, 1, 22, 0, 0), 1125.86),\n",
"\t(datetime.datetime(2017, 1, 29, 0, 0), 1178.74)], frequency='W')"
"20"
]
},
"execution_count": 8,
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ts[(ts.dates < '2017-01-31') & (ts.dates > '2017-01-01')]"
"len(tst)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "32a82399-e056-45d6-86a3-b9f0855aed27",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Series([datetime.datetime(2017, 1, 1, 0, 0), datetime.datetime(2017, 2, 1, 0, 0), datetime.datetime(2017, 3, 1, 0, 0), datetime.datetime(2017, 4, 1, 0, 0), datetime.datetime(2017, 5, 1, 0, 0), datetime.datetime(2017, 6, 1, 0, 0), datetime.datetime(2017, 7, 1, 0, 0), datetime.datetime(2017, 8, 1, 0, 0), datetime.datetime(2017, 9, 1, 0, 0), datetime.datetime(2017, 10, 1, 0, 0), datetime.datetime(2017, 11, 1, 0, 0), datetime.datetime(2017, 12, 1, 0, 0), datetime.datetime(2018, 1, 1, 0, 0), datetime.datetime(2018, 2, 1, 0, 0), datetime.datetime(2018, 3, 1, 0, 0), datetime.datetime(2018, 4, 1, 0, 0), datetime.datetime(2018, 5, 1, 0, 0), datetime.datetime(2018, 6, 1, 0, 0), datetime.datetime(2018, 7, 1, 0, 0), datetime.datetime(2018, 8, 1, 0, 0), datetime.datetime(2018, 9, 1, 0, 0), datetime.datetime(2018, 10, 1, 0, 0), datetime.datetime(2018, 11, 1, 0, 0), datetime.datetime(2018, 12, 1, 0, 0), datetime.datetime(2019, 1, 1, 0, 0), datetime.datetime(2019, 2, 1, 0, 0), datetime.datetime(2019, 3, 1, 0, 0), datetime.datetime(2019, 4, 1, 0, 0), datetime.datetime(2019, 5, 1, 0, 0), datetime.datetime(2019, 6, 1, 0, 0), datetime.datetime(2019, 7, 1, 0, 0), datetime.datetime(2019, 8, 1, 0, 0), datetime.datetime(2019, 9, 1, 0, 0), datetime.datetime(2019, 10, 1, 0, 0), datetime.datetime(2019, 11, 1, 0, 0), datetime.datetime(2019, 12, 1, 0, 0), datetime.datetime(2020, 1, 1, 0, 0), datetime.datetime(2020, 2, 1, 0, 0), datetime.datetime(2020, 3, 1, 0, 0), datetime.datetime(2020, 4, 1, 0, 0), datetime.datetime(2020, 5, 1, 0, 0), datetime.datetime(2020, 6, 1, 0, 0), datetime.datetime(2020, 7, 1, 0, 0), datetime.datetime(2020, 8, 1, 0, 0), datetime.datetime(2020, 9, 1, 0, 0), datetime.datetime(2020, 10, 1, 0, 0), datetime.datetime(2020, 11, 1, 0, 0), datetime.datetime(2020, 12, 1, 0, 0), datetime.datetime(2021, 1, 1, 0, 0), datetime.datetime(2021, 2, 1, 0, 0), datetime.datetime(2021, 3, 1, 0, 0), datetime.datetime(2021, 4, 1, 0, 0), datetime.datetime(2021, 5, 1, 0, 0), datetime.datetime(2021, 6, 1, 0, 0), datetime.datetime(2021, 7, 1, 0, 0), datetime.datetime(2021, 8, 1, 0, 0), datetime.datetime(2021, 9, 1, 0, 0), datetime.datetime(2021, 10, 1, 0, 0), datetime.datetime(2021, 11, 1, 0, 0), datetime.datetime(2021, 12, 1, 0, 0)], data_type='datetime')"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dates"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "352a71a3-5469-4464-8a93-17f4660822fd",
"execution_count": 15,
"id": "bccd7d1c-2d57-444c-af68-290f476f2b05",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2017-01-01 00:00:00 1040.39\n",
"2017-01-08 00:00:00 1032.83\n",
"2017-01-15 00:00:00 1120.5\n",
"2017-01-22 00:00:00 1125.86\n",
"2017-01-29 00:00:00 1178.74\n",
"2017-02-05 00:00:00 1158.8\n",
"2017-02-12 00:00:00 1151.54\n",
"2017-02-19 00:00:00 1137.19\n",
"2017-02-26 00:00:00 1141.47\n",
"2017-03-05 00:00:00 1112.37\n",
"2017-03-12 00:00:00 1186.34\n",
"2017-03-19 00:00:00 1202.35\n",
"2017-03-26 00:00:00 1169.04\n",
"2017-04-02 00:00:00 1220.55\n",
"2017-04-09 00:00:00 1202.93\n",
"2017-04-16 00:00:00 1187.57\n",
"2017-04-23 00:00:00 1197.52\n",
"2017-04-30 00:00:00 1218.61\n",
"2017-05-07 00:00:00 1272.3\n",
"2017-05-14 00:00:00 1278.49\n",
"2017-05-21 00:00:00 1296.56\n",
"2017-05-28 00:00:00 1294.03\n",
"2017-06-04 00:00:00 1244.9\n",
"2017-06-11 00:00:00 1233.13\n",
"2017-06-18 00:00:00 1218.74\n",
"2017-06-25 00:00:00 1208.5\n",
"2017-07-02 00:00:00 1179.17\n",
"2017-07-09 00:00:00 1164.11\n",
"2017-07-16 00:00:00 1109.05\n",
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"2017-08-06 00:00:00 1059.84\n",
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"2017-09-10 00:00:00 1175.81\n",
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"2017-09-24 00:00:00 1208.74\n",
"2017-10-01 00:00:00 1210.82\n",
"2017-10-08 00:00:00 1170.14\n",
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"2017-10-29 00:00:00 1256.52\n",
"2017-11-05 00:00:00 1288.37\n",
"2017-11-12 00:00:00 1342.41\n",
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"2017-12-03 00:00:00 1538.06\n",
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"2017-12-31 00:00:00 1515.75\n",
"2018-01-07 00:00:00 1528.28\n",
"2018-01-14 00:00:00 1541.99\n",
"2018-01-21 00:00:00 1510.71\n",
"2018-01-28 00:00:00 1592.01\n",
"2018-02-04 00:00:00 1718.11\n",
"2018-02-11 00:00:00 1788.51\n",
"2018-02-18 00:00:00 1895.84\n",
"2018-02-25 00:00:00 1965.28\n",
"2018-03-04 00:00:00 1985.45\n",
"2018-03-11 00:00:00 1948.76\n",
"2018-03-18 00:00:00 2004.36\n",
"2018-03-25 00:00:00 2040.49\n",
"2018-04-01 00:00:00 1966.17\n",
"2018-04-08 00:00:00 1984.85\n",
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"2019-12-29 00:00:00 1117.66\n",
"2020-01-05 00:00:00 1162.87\n",
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"2021-12-26 00:00:00 1924.2\n"
"(datetime.datetime(2017, 1, 1, 0, 0), 1010.4553846153846)\n",
"(datetime.datetime(2017, 4, 1, 0, 0), 1019.34)\n",
"(datetime.datetime(2017, 7, 1, 0, 0), 1015.3515384615384)\n",
"(datetime.datetime(2017, 10, 1, 0, 0), 1031.2892857142858)\n",
"(datetime.datetime(2018, 1, 1, 0, 0), 1054.7216666666666)\n",
"(datetime.datetime(2018, 4, 1, 0, 0), 1059.736153846154)\n",
"(datetime.datetime(2018, 7, 1, 0, 0), 1049.1100000000001)\n",
"(datetime.datetime(2018, 10, 1, 0, 0), 1051.663076923077)\n",
"(datetime.datetime(2019, 1, 1, 0, 0), 1062.2869230769231)\n",
"(datetime.datetime(2019, 4, 1, 0, 0), 1059.7423076923076)\n",
"(datetime.datetime(2019, 7, 1, 0, 0), 1050.7661538461539)\n",
"(datetime.datetime(2019, 10, 1, 0, 0), 1045.2061538461537)\n",
"(datetime.datetime(2020, 1, 1, 0, 0), 1046.11)\n",
"(datetime.datetime(2020, 4, 1, 0, 0), 1053.126923076923)\n",
"(datetime.datetime(2020, 7, 1, 0, 0), 1053.273846153846)\n",
"(datetime.datetime(2020, 10, 1, 0, 0), 1064.2384615384615)\n",
"(datetime.datetime(2021, 1, 1, 0, 0), 1073.1538461538462)\n",
"(datetime.datetime(2021, 4, 1, 0, 0), 1094.3215384615385)\n",
"(datetime.datetime(2021, 7, 1, 0, 0), 1104.3584615384616)\n",
"(datetime.datetime(2021, 10, 1, 0, 0), 1112.806923076923)\n"
]
}
],
"source": [
"for i, j in ts:\n",
" print(i, j)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "14c72558-0500-44e4-a893-628a4102ff53",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2017-01-01 00:00:00 1099.664\n",
"2017-02-01 00:00:00 1147.25\n",
"2017-03-01 00:00:00 1167.5249999999999\n",
"2017-04-01 00:00:00 1205.436\n",
"2017-05-01 00:00:00 1285.345\n",
"2017-06-01 00:00:00 1226.3175\n",
"2017-07-01 00:00:00 1119.366\n",
"2017-08-01 00:00:00 1096.86\n",
"2017-09-01 00:00:00 1173.1475\n",
"2017-10-01 00:00:00 1210.18\n",
"2017-11-01 00:00:00 1391.4975\n",
"2017-12-01 00:00:00 1473.172\n",
"2018-01-01 00:00:00 1543.2475\n",
"2018-02-01 00:00:00 1841.935\n",
"2018-03-01 00:00:00 1994.7649999999999\n",
"2018-04-01 00:00:00 1933.944\n",
"2018-05-01 00:00:00 1768.365\n",
"2018-06-01 00:00:00 1798.7775000000001\n",
"2018-07-01 00:00:00 1602.54\n",
"2018-08-01 00:00:00 1468.445\n",
"2018-09-01 00:00:00 1534.14\n",
"2018-10-01 00:00:00 1545.12\n",
"2018-11-01 00:00:00 1517.2875\n",
"2018-12-01 00:00:00 1534.112\n",
"2019-01-01 00:00:00 1689.6924999999999\n",
"2019-02-01 00:00:00 1829.31\n",
"2019-03-01 00:00:00 1612.344\n",
"2019-04-01 00:00:00 1561.4325\n",
"2019-05-01 00:00:00 1639.56\n",
"2019-06-01 00:00:00 1562.152\n",
"2019-07-01 00:00:00 1405.61\n",
"2019-08-01 00:00:00 1351.45\n",
"2019-09-01 00:00:00 1322.7\n",
"2019-10-01 00:00:00 1333.6025\n",
"2019-11-01 00:00:00 1166.5925\n",
"2019-12-01 00:00:00 1163.202\n",
"2020-01-01 00:00:00 1167.065\n",
"2020-02-01 00:00:00 1170.555\n",
"2020-03-01 00:00:00 1210.952\n",
"2020-04-01 00:00:00 1284.5774999999999\n",
"2020-05-01 00:00:00 1216.634\n",
"2020-06-01 00:00:00 1272.9099999999999\n",
"2020-07-01 00:00:00 1272.22\n",
"2020-08-01 00:00:00 1161.09\n",
"2020-09-01 00:00:00 1217.0974999999999\n",
"2020-10-01 00:00:00 1313.04\n",
"2020-11-01 00:00:00 1310.506\n",
"2020-12-01 00:00:00 1440.78\n",
"2021-01-01 00:00:00 1438.026\n",
"2021-02-01 00:00:00 1437.3474999999999\n",
"2021-03-01 00:00:00 1524.5225\n",
"2021-04-01 00:00:00 1764.155\n",
"2021-05-01 00:00:00 1830.142\n",
"2021-06-01 00:00:00 1981.4175\n",
"2021-07-01 00:00:00 1875.5275000000001\n",
"2021-08-01 00:00:00 2023.024\n",
"2021-09-01 00:00:00 2212.9825\n",
"2021-10-01 00:00:00 2280.428\n",
"2021-11-01 00:00:00 2235.4325\n"
]
}
],
"source": [
"prev_date = dates[0]\n",
"for date in dates[1:]:\n",
" cur_ts = ts[(ts.dates < date) & (ts.dates >= prev_date)]\n",
" print(prev_date, cur_ts.mean())\n",
" prev_date = date"
"for i in tst:\n",
" print(i)"
]
}
],
@ -1066,7 +708,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
"version": "3.10.2"
}
},
"nbformat": 4,