univer-7th-semester/supercomputers
Code Actions Releases

Уточнил задание

Browse Source
This commit is contained in:
Артём Тищенко
2025-12-11 16:47:30 +03:00
parent 7f16a5c17a
commit d82fde7116
2 changed files with 247 additions and 200 deletions
Download Patch File Download Diff File Expand all files Collapse all files

445
data.ipynb
View File

@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 20,
"id": "2acce44b",
"metadata": {},
"outputs": [],
@@ -12,7 +12,7 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 21,
"id": "5ba70af7",
"metadata": {},
"outputs": [
@@ -111,7 +111,7 @@
"7317758 0.410369 "
]
},
"execution_count": 14,
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
@@ -124,8 +124,8 @@
},
{
"cell_type": "code",
"execution_count": 19,
"id": "d4b22f3b",
"execution_count": 23,
"id": "3b320537",
"metadata": {},
"outputs": [
{
@@ -150,67 +150,190 @@
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Timestamp</th>\n",
" <th>Low</th>\n",
" <th>High</th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Volume</th>\n",
" <th>Avg</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>5078</th>\n",
" <td>2025-11-26</td>\n",
" <td>86304.0</td>\n",
" <td>90646.0</td>\n",
" <td>87331.0</td>\n",
" <td>90477.0</td>\n",
" <th>7317754</th>\n",
" <td>2025-11-30 23:55:00+00:00</td>\n",
" <td>90405.0</td>\n",
" <td>90452.0</td>\n",
" <td>90403.0</td>\n",
" <td>90452.0</td>\n",
" <td>0.531700</td>\n",
" <td>90427.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5079</th>\n",
" <td>2025-11-27</td>\n",
" <td>90091.0</td>\n",
" <td>91926.0</td>\n",
" <td>90476.0</td>\n",
" <td>91325.0</td>\n",
" <th>7317755</th>\n",
" <td>2025-11-30 23:56:00+00:00</td>\n",
" <td>90452.0</td>\n",
" <td>90481.0</td>\n",
" <td>90420.0</td>\n",
" <td>90420.0</td>\n",
" <td>0.055547</td>\n",
" <td>90450.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5080</th>\n",
" <td>2025-11-28</td>\n",
" <td>90233.0</td>\n",
" <td>93091.0</td>\n",
" <td>91326.0</td>\n",
" <td>90913.0</td>\n",
" <th>7317756</th>\n",
" <td>2025-11-30 23:57:00+00:00</td>\n",
" <td>90412.0</td>\n",
" <td>90458.0</td>\n",
" <td>90396.0</td>\n",
" <td>90435.0</td>\n",
" <td>0.301931</td>\n",
" <td>90427.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5081</th>\n",
" <td>2025-11-29</td>\n",
" <td>90216.0</td>\n",
" <td>91179.0</td>\n",
" <td>90913.0</td>\n",
" <td>90832.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5082</th>\n",
" <td>2025-11-30</td>\n",
" <th>7317757</th>\n",
" <td>2025-11-30 23:58:00+00:00</td>\n",
" <td>90428.0</td>\n",
" <td>90428.0</td>\n",
" <td>90362.0</td>\n",
" <td>90362.0</td>\n",
" <td>4.591653</td>\n",
" <td>90395.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7317758</th>\n",
" <td>2025-11-30 23:59:00+00:00</td>\n",
" <td>90363.0</td>\n",
" <td>90386.0</td>\n",
" <td>90362.0</td>\n",
" <td>91969.0</td>\n",
" <td>90832.0</td>\n",
" <td>90382.0</td>\n",
" <td>0.410369</td>\n",
" <td>90374.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Timestamp Low High Open Close\n",
"5078 2025-11-26 86304.0 90646.0 87331.0 90477.0\n",
"5079 2025-11-27 90091.0 91926.0 90476.0 91325.0\n",
"5080 2025-11-28 90233.0 93091.0 91326.0 90913.0\n",
"5081 2025-11-29 90216.0 91179.0 90913.0 90832.0\n",
"5082 2025-11-30 90362.0 91969.0 90832.0 90382.0"
" Timestamp Open High Low Close \\\n",
"7317754 2025-11-30 23:55:00+00:00 90405.0 90452.0 90403.0 90452.0 \n",
"7317755 2025-11-30 23:56:00+00:00 90452.0 90481.0 90420.0 90420.0 \n",
"7317756 2025-11-30 23:57:00+00:00 90412.0 90458.0 90396.0 90435.0 \n",
"7317757 2025-11-30 23:58:00+00:00 90428.0 90428.0 90362.0 90362.0 \n",
"7317758 2025-11-30 23:59:00+00:00 90363.0 90386.0 90362.0 90382.0 \n",
"\n",
" Volume Avg \n",
"7317754 0.531700 90427.5 \n",
"7317755 0.055547 90450.5 \n",
"7317756 0.301931 90427.0 \n",
"7317757 4.591653 90395.0 \n",
"7317758 0.410369 90374.0 "
]
},
"execution_count": 19,
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['Avg'] = (df['Low'] + df['High']) / 2\n",
"df.tail()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "4b1cd63c",
"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>Timestamp</th>\n",
" <th>Avg</th>\n",
" <th>OpenMin</th>\n",
" <th>OpenMax</th>\n",
" <th>CloseMin</th>\n",
" <th>CloseMax</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>5078</th>\n",
" <td>2025-11-26</td>\n",
" <td>88057.301736</td>\n",
" <td>86312.0</td>\n",
" <td>90574.0</td>\n",
" <td>86323.0</td>\n",
" <td>90574.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5079</th>\n",
" <td>2025-11-27</td>\n",
" <td>91245.092708</td>\n",
" <td>90126.0</td>\n",
" <td>91888.0</td>\n",
" <td>90126.0</td>\n",
" <td>91925.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5080</th>\n",
" <td>2025-11-28</td>\n",
" <td>91324.308681</td>\n",
" <td>90255.0</td>\n",
" <td>92970.0</td>\n",
" <td>90283.0</td>\n",
" <td>92966.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5081</th>\n",
" <td>2025-11-29</td>\n",
" <td>90746.479514</td>\n",
" <td>90265.0</td>\n",
" <td>91158.0</td>\n",
" <td>90279.0</td>\n",
" <td>91179.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5082</th>\n",
" <td>2025-11-30</td>\n",
" <td>91187.356250</td>\n",
" <td>90363.0</td>\n",
" <td>91940.0</td>\n",
" <td>90362.0</td>\n",
" <td>91940.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Timestamp Avg OpenMin OpenMax CloseMin CloseMax\n",
"5078 2025-11-26 88057.301736 86312.0 90574.0 86323.0 90574.0\n",
"5079 2025-11-27 91245.092708 90126.0 91888.0 90126.0 91925.0\n",
"5080 2025-11-28 91324.308681 90255.0 92970.0 90283.0 92966.0\n",
"5081 2025-11-29 90746.479514 90265.0 91158.0 90279.0 91179.0\n",
"5082 2025-11-30 91187.356250 90363.0 91940.0 90362.0 91940.0"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
@@ -218,7 +341,13 @@
"source": [
"df_days = (\n",
" df.groupby(df[\"Timestamp\"].dt.date)\n",
" .agg({\"Low\": \"min\", \"High\": \"max\", \"Open\": \"first\", \"Close\": \"last\"})\n",
" .agg(\n",
" Avg=(\"Avg\", \"mean\"),\n",
" OpenMin=(\"Open\", \"min\"),\n",
" OpenMax=(\"Open\", \"max\"),\n",
" CloseMin=(\"Close\", \"min\"),\n",
" CloseMax=(\"Close\", \"max\"),\n",
" )\n",
" .reset_index()\n",
")\n",
"df_days.tail()"
@@ -226,111 +355,7 @@
},
{
"cell_type": "code",
"execution_count": 21,
"id": "91823496",
"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>Timestamp</th>\n",
" <th>Low</th>\n",
" <th>High</th>\n",
" <th>Open</th>\n",
" <th>Close</th>\n",
" <th>Avg</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>5078</th>\n",
" <td>2025-11-26</td>\n",
" <td>86304.0</td>\n",
" <td>90646.0</td>\n",
" <td>87331.0</td>\n",
" <td>90477.0</td>\n",
" <td>88475.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5079</th>\n",
" <td>2025-11-27</td>\n",
" <td>90091.0</td>\n",
" <td>91926.0</td>\n",
" <td>90476.0</td>\n",
" <td>91325.0</td>\n",
" <td>91008.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5080</th>\n",
" <td>2025-11-28</td>\n",
" <td>90233.0</td>\n",
" <td>93091.0</td>\n",
" <td>91326.0</td>\n",
" <td>90913.0</td>\n",
" <td>91662.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5081</th>\n",
" <td>2025-11-29</td>\n",
" <td>90216.0</td>\n",
" <td>91179.0</td>\n",
" <td>90913.0</td>\n",
" <td>90832.0</td>\n",
" <td>90697.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5082</th>\n",
" <td>2025-11-30</td>\n",
" <td>90362.0</td>\n",
" <td>91969.0</td>\n",
" <td>90832.0</td>\n",
" <td>90382.0</td>\n",
" <td>91165.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Timestamp Low High Open Close Avg\n",
"5078 2025-11-26 86304.0 90646.0 87331.0 90477.0 88475.0\n",
"5079 2025-11-27 90091.0 91926.0 90476.0 91325.0 91008.5\n",
"5080 2025-11-28 90233.0 93091.0 91326.0 90913.0 91662.0\n",
"5081 2025-11-29 90216.0 91179.0 90913.0 90832.0 90697.5\n",
"5082 2025-11-30 90362.0 91969.0 90832.0 90382.0 91165.5"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_days[\"Avg\"] = (df_days[\"Low\"] + df_days[\"High\"]) / 2\n",
"df_days.tail()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"execution_count": 26,
"id": "9a7b3310",
"metadata": {},
"outputs": [
@@ -358,6 +383,8 @@
" <th>start_date</th>\n",
" <th>end_date</th>\n",
" <th>min_open</th>\n",
" <th>max_open</th>\n",
" <th>min_close</th>\n",
" <th>max_close</th>\n",
" <th>start_avg</th>\n",
" <th>end_avg</th>\n",
@@ -366,76 +393,86 @@
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>335</th>\n",
" <th>316</th>\n",
" <td>2025-02-27</td>\n",
" <td>2025-04-23</td>\n",
" <td>76252.0</td>\n",
" <td>94273.0</td>\n",
" <td>84801.5</td>\n",
" <td>93335.0</td>\n",
" <td>0.100629</td>\n",
" <td>2025-04-25</td>\n",
" <td>74509.0</td>\n",
" <td>95801.0</td>\n",
" <td>74515.0</td>\n",
" <td>95800.0</td>\n",
" <td>85166.063889</td>\n",
" <td>94303.907292</td>\n",
" <td>0.107294</td>\n",
" </tr>\n",
" <tr>\n",
" <th>336</th>\n",
" <td>2025-04-24</td>\n",
" <td>2025-05-09</td>\n",
" <td>93730.0</td>\n",
" <td>103261.0</td>\n",
" <td>92867.5</td>\n",
" <td>103341.0</td>\n",
" <td>0.112779</td>\n",
" <th>317</th>\n",
" <td>2025-04-26</td>\n",
" <td>2025-05-11</td>\n",
" <td>92877.0</td>\n",
" <td>104971.0</td>\n",
" <td>92872.0</td>\n",
" <td>104965.0</td>\n",
" <td>94500.950347</td>\n",
" <td>104182.167708</td>\n",
" <td>0.102446</td>\n",
" </tr>\n",
" <tr>\n",
" <th>337</th>\n",
" <td>2025-05-10</td>\n",
" <th>318</th>\n",
" <td>2025-05-12</td>\n",
" <td>2025-07-11</td>\n",
" <td>100990.0</td>\n",
" <td>117579.0</td>\n",
" <td>103915.0</td>\n",
" <td>117032.5</td>\n",
" <td>0.126233</td>\n",
" <td>98384.0</td>\n",
" <td>118833.0</td>\n",
" <td>98382.0</td>\n",
" <td>118839.0</td>\n",
" <td>103569.791319</td>\n",
" <td>117463.666667</td>\n",
" <td>0.134150</td>\n",
" </tr>\n",
" <tr>\n",
" <th>338</th>\n",
" <th>319</th>\n",
" <td>2025-07-12</td>\n",
" <td>2025-11-04</td>\n",
" <td>106470.0</td>\n",
" <td>124728.0</td>\n",
" <td>117599.0</td>\n",
" <td>103079.0</td>\n",
" <td>0.123470</td>\n",
" <td>98944.0</td>\n",
" <td>126202.0</td>\n",
" <td>98943.0</td>\n",
" <td>126202.0</td>\n",
" <td>117640.026389</td>\n",
" <td>103712.985764</td>\n",
" <td>0.118387</td>\n",
" </tr>\n",
" <tr>\n",
" <th>339</th>\n",
" <th>320</th>\n",
" <td>2025-11-05</td>\n",
" <td>2025-11-18</td>\n",
" <td>92112.0</td>\n",
" <td>105972.0</td>\n",
" <td>101737.5</td>\n",
" <td>91471.0</td>\n",
" <td>0.100912</td>\n",
" <td>89291.0</td>\n",
" <td>107343.0</td>\n",
" <td>89286.0</td>\n",
" <td>107343.0</td>\n",
" <td>102514.621181</td>\n",
" <td>91705.833333</td>\n",
" <td>0.105437</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" start_date end_date min_open max_close start_avg end_avg \\\n",
"335 2025-02-27 2025-04-23 76252.0 94273.0 84801.5 93335.0 \n",
"336 2025-04-24 2025-05-09 93730.0 103261.0 92867.5 103341.0 \n",
"337 2025-05-10 2025-07-11 100990.0 117579.0 103915.0 117032.5 \n",
"338 2025-07-12 2025-11-04 106470.0 124728.0 117599.0 103079.0 \n",
"339 2025-11-05 2025-11-18 92112.0 105972.0 101737.5 91471.0 \n",
" start_date end_date min_open max_open min_close max_close \\\n",
"316 2025-02-27 2025-04-25 74509.0 95801.0 74515.0 95800.0 \n",
"317 2025-04-26 2025-05-11 92877.0 104971.0 92872.0 104965.0 \n",
"318 2025-05-12 2025-07-11 98384.0 118833.0 98382.0 118839.0 \n",
"319 2025-07-12 2025-11-04 98944.0 126202.0 98943.0 126202.0 \n",
"320 2025-11-05 2025-11-18 89291.0 107343.0 89286.0 107343.0 \n",
"\n",
" change \n",
"335 0.100629 \n",
"336 0.112779 \n",
"337 0.126233 \n",
"338 0.123470 \n",
"339 0.100912 "
" start_avg end_avg change \n",
"316 85166.063889 94303.907292 0.107294 \n",
"317 94500.950347 104182.167708 0.102446 \n",
"318 103569.791319 117463.666667 0.134150 \n",
"319 117640.026389 103712.985764 0.118387 \n",
"320 102514.621181 91705.833333 0.105437 "
]
},
"execution_count": 25,
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
@@ -455,8 +492,10 @@
" intervals.append({\n",
" \"start_date\": df_days.loc[start_idx, \"Timestamp\"],\n",
" \"end_date\": df_days.loc[i, \"Timestamp\"],\n",
" \"min_open\": interval[\"Open\"].min(),\n",
" \"max_close\": interval[\"Close\"].max(),\n",
" \"min_open\": interval[\"OpenMin\"].min(),\n",
" \"max_open\": interval[\"OpenMax\"].max(),\n",
" \"min_close\": interval[\"CloseMin\"].min(),\n",
" \"max_close\": interval[\"CloseMax\"].max(),\n",
" \"start_avg\": price_base,\n",
" \"end_avg\": price_now,\n",
" \"change\": change,\n",
@@ -470,6 +509,14 @@
"df_intervals = pd.DataFrame(intervals)\n",
"df_intervals.tail()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "07f1cd58",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {