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1 and 2 lab
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Работа с NumPy"
]
},
{
"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"matrix = \n",
" [[4 5 0]\n",
" [9 9 9]] \n",
"\n",
"tmatrix = \n",
" [[4 9]\n",
" [5 9]\n",
" [0 9]] \n",
"\n",
"vector = \n",
" [4 5 0 9 9 9] \n",
"\n",
"tvector = \n",
" [[4]\n",
" [5]\n",
" [0]\n",
" [9]\n",
" [9]\n",
" [9]] \n",
"\n",
"list_matrix = \n",
" [array([4, 5, 0]), array([9, 9, 9])] \n",
"\n",
"matrix as str = \n",
" [[4 5 0]\n",
" [9 9 9]] \n",
"\n",
"matrix type is <class 'numpy.ndarray'> \n",
"\n",
"vector type is <class 'numpy.ndarray'> \n",
"\n",
"list_matrix type is <class 'list'> \n",
"\n",
"str_matrix type is <class 'str'> \n",
"\n",
"formatted_vector = \n",
" 4; 5; 0; 9; 9; 9 \n",
"\n"
]
}
],
"source": [
"import numpy as np\n",
"\n",
"matrix = np.array([[4, 5, 0], [9, 9, 9]])\n",
"print(\"matrix = \\n\", matrix, \"\\n\")\n",
"\n",
"tmatrix = matrix.T\n",
"print(\"tmatrix = \\n\", tmatrix, \"\\n\")\n",
"\n",
"vector = np.ravel(matrix)\n",
"print(\"vector = \\n\", vector, \"\\n\")\n",
"\n",
"tvector = np.reshape(vector, (6, 1))\n",
"print(\"tvector = \\n\", tvector, \"\\n\")\n",
"\n",
"list_matrix = list(matrix)\n",
"print(\"list_matrix = \\n\", list_matrix, \"\\n\")\n",
"\n",
"str_matrix = str(matrix)\n",
"print(\"matrix as str = \\n\", str_matrix, \"\\n\")\n",
"\n",
"print(\"matrix type is\", type(matrix), \"\\n\")\n",
"\n",
"print(\"vector type is\", type(vector), \"\\n\")\n",
"\n",
"print(\"list_matrix type is\", type(list_matrix), \"\\n\")\n",
"\n",
"print(\"str_matrix type is\", type(str_matrix), \"\\n\")\n",
"\n",
"formatted_vector = \"; \".join(map(str, vector))\n",
"print(\"formatted_vector = \\n\", formatted_vector, \"\\n\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Работа с Pandas DataFrame\n",
"\n",
"https://pandas.pydata.org/docs/user_guide/10min.html"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Работа с данными - чтение и запись CSV"
]
},
{
"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
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"df = pd.read_csv(\"data/starbucks.csv\", index_col=\"Date\")\n",
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"\n",
"df.to_csv(\"test.csv\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Работа с данными - основные команды"
]
},
{
"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
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"Index: 8036 entries, 1992-06-26 to 2024-05-23\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Open 8036 non-null float64\n",
" 1 High 8036 non-null float64\n",
" 2 Low 8036 non-null float64\n",
" 3 Close 8036 non-null float64\n",
" 4 Adj Close 8036 non-null float64\n",
" 5 Volume 8036 non-null int64 \n",
"dtypes: float64(5), int64(1)\n",
"memory usage: 439.5+ KB\n",
" count mean std min 25% \\\n",
"Open 8036.0 3.005428e+01 3.361558e+01 3.281250e-01 4.392031e+00 \n",
"High 8036.0 3.035149e+01 3.390661e+01 3.476560e-01 4.531250e+00 \n",
"Low 8036.0 2.975132e+01 3.331457e+01 3.203130e-01 4.304922e+00 \n",
"Close 8036.0 3.005886e+01 3.361591e+01 3.359380e-01 4.399610e+00 \n",
"Adj Close 8036.0 2.667402e+01 3.172809e+01 2.607030e-01 3.414300e+00 \n",
"Volume 8036.0 1.470459e+07 1.340021e+07 1.504000e+06 7.817750e+06 \n",
"\n",
" 50% 75% max \n",
"Open 1.332500e+01 5.525000e+01 1.260800e+02 \n",
"High 1.349375e+01 5.572250e+01 1.263200e+02 \n",
"Low 1.315000e+01 5.485250e+01 1.248100e+02 \n",
"Close 1.333000e+01 5.526750e+01 1.260600e+02 \n",
"Adj Close 1.035245e+01 4.746483e+01 1.180104e+02 \n",
"Volume 1.169815e+07 1.778795e+07 5.855088e+08 \n",
" High Low Adj Close Volume\n",
"Date \n",
"1992-06-26 0.347656 0.320313 0.260703 224358400\n",
"1992-06-29 0.367188 0.332031 0.278891 58732800\n",
"1992-06-30 0.371094 0.343750 0.269797 34777600\n",
"1992-07-01 0.359375 0.339844 0.275860 18316800\n",
"1992-07-02 0.359375 0.347656 0.275860 13996800\n",
" High Low Adj Close Volume\n",
"Date \n",
"2024-05-17 78.000000 74.919998 77.849998 14436500\n",
"2024-05-20 78.320000 76.709999 77.540001 11183800\n",
"2024-05-21 78.220001 77.500000 77.720001 8916600\n",
"2024-05-22 81.019997 77.440002 80.720001 22063400\n",
"2024-05-23 80.699997 79.169998 79.260002 4651418\n",
" High Low Adj Close Volume\n",
"Date \n",
"1995-08-10 1.195313 1.183594 0.918523 1504000\n",
"2019-12-24 88.599998 88.000000 80.528366 1847800\n",
"1993-12-15 0.710938 0.695313 0.545657 1875200\n",
"1993-12-07 0.773438 0.750000 0.582034 1910400\n",
"2020-12-24 102.360001 101.680000 94.714470 1949200\n",
" High Low Adj Close Volume\n",
"Date \n",
"1998-07-24 3.375000 2.882813 2.322075 155107200\n",
"1992-06-26 0.347656 0.320313 0.260703 224358400\n",
"1995-09-29 1.371094 1.125000 0.918523 230883200\n",
"2000-06-07 4.671875 4.000000 3.352761 295411200\n",
"1999-07-01 3.375000 2.929688 2.613092 585508800\n"
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]
}
],
"source": [
"df.info()\n",
"\n",
"print(df.describe().transpose())\n",
"\n",
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"cleared_df = df.drop([\"Open\", \"Close\"], axis=1)\n",
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"print(cleared_df.head())\n",
"print(cleared_df.tail())\n",
"\n",
1 lab fix
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"sorted_df = cleared_df.sort_values(by=\"Volume\")\n",
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"print(sorted_df.head())\n",
"print(sorted_df.tail())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Работа с данными - работа с элементами"
]
},
{
"cell_type": "code",
1 lab fix
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"execution_count": 5,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"Date\n",
"1992-06-26 224358400\n",
"1992-06-29 58732800\n",
"1992-06-30 34777600\n",
"1992-07-01 18316800\n",
"1992-07-02 13996800\n",
" ... \n",
"2024-05-17 14436500\n",
"2024-05-20 11183800\n",
"2024-05-21 8916600\n",
"2024-05-22 22063400\n",
"2024-05-23 4651418\n",
"Name: Volume, Length: 8036, dtype: int64\n",
"Open 5.078130e-01\n",
"High 5.078130e-01\n",
"Low 5.000000e-01\n",
"Close 5.078130e-01\n",
"Adj Close 3.940860e-01\n",
"Volume 8.256000e+06\n",
"Name: 1992-11-17, dtype: float64\n",
"0.339844\n",
" Volume Open\n",
"Date \n",
"1992-07-08 15500800 0.355469\n",
"1992-07-09 3923200 0.351563\n",
"1992-07-10 11040000 0.359375\n",
"1992-07-13 5996800 0.363281\n",
"1992-07-14 17062400 0.371094\n",
"1992-07-15 4992000 0.375000\n",
"1992-07-16 17062400 0.382813\n",
"1992-07-17 15667200 0.410156\n",
"1992-07-20 19744000 0.427734\n",
"1992-07-21 7782400 0.437500\n",
"1992-07-22 10892800 0.433594\n",
" Open High Low Close Adj Close Volume\n",
"Date \n",
"1992-06-29 0.339844 0.367188 0.332031 0.359375 0.278891 58732800\n",
"1992-06-30 0.367188 0.371094 0.343750 0.347656 0.269797 34777600\n",
"Open 3.281250e-01\n",
"High 3.476560e-01\n",
"Low 3.203130e-01\n",
"Close 3.359380e-01\n",
"Adj Close 2.607030e-01\n",
"Volume 2.243584e+08\n",
"Name: 1992-06-26, dtype: float64\n",
" Open High\n",
"Date \n",
"1992-07-01 0.351563 0.359375\n",
"1992-07-02 0.359375 0.359375\n",
" Open High\n",
"Date \n",
"1992-07-01 0.351563 0.359375\n",
"1992-07-02 0.359375 0.359375\n"
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]
}
],
"source": [
1 lab fix
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"print(df[\"Volume\"])\n",
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"\n",
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"print(df.iloc[100])\n",
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"\n",
1 lab fix
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"print(df.loc[\"1992-06-29\", \"Open\"]) #мда индекс\n",
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"\n",
1 lab fix
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"print(df.loc[\"1992-07-08\":\"1992-07-22\", [\"Volume\", \"Open\"]])\n",
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"\n",
1 lab fix
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"print(df[1:3])\n",
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"\n",
"print(df.iloc[0])\n",
"\n",
"print(df.iloc[3:5, 0:2])\n",
"\n",
"print(df.iloc[[3, 4], [0, 1]])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Работа с данными - отбор и группировка"
]
},
{
"cell_type": "code",
1 lab fix
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"execution_count": 6,
1 and 2 lab
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
1 lab fix
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"[224358400 58732800 34777600 ... 8916600 22063400 4651418]\n",
"224358400 count = 1\n",
"58732800 count = 1\n",
"34777600 count = 1\n",
"18316800 count = 1\n",
"13996800 count = 1\n",
"5753600 count = 2\n",
"10662400 count = 1\n",
"15500800 count = 1\n",
"3923200 count = 1\n",
"11040000 count = 1\n",
"5996800 count = 2\n",
"17062400 count = 2\n",
"4992000 count = 1\n",
"15667200 count = 1\n",
"19744000 count = 2\n",
"7782400 count = 1\n",
"10892800 count = 2\n",
"10387200 count = 2\n",
"7052800 count = 1\n",
"11430400 count = 1\n",
"18009600 count = 1\n",
"30848000 count = 1\n",
"11737600 count = 1\n",
"6886400 count = 1\n",
"4832000 count = 1\n",
"6822400 count = 1\n",
"9516800 count = 2\n",
"3673600 count = 1\n",
"8825600 count = 1\n",
"5888000 count = 1\n",
"4147200 count = 1\n",
"12736000 count = 1\n",
"48320000 count = 1\n",
"17849600 count = 1\n",
"2681600 count = 1\n",
"2860800 count = 1\n",
"2380800 count = 1\n",
"2489600 count = 1\n",
"2048000 count = 1\n",
"6905600 count = 1\n",
"4128000 count = 1\n",
"19385600 count = 1\n",
"6169600 count = 1\n",
"3417600 count = 1\n",
"4441600 count = 2\n",
"2387200 count = 1\n",
"11692800 count = 1\n",
"16480000 count = 1\n",
"4249600 count = 1\n",
"17139200 count = 1\n",
"25299200 count = 1\n",
"8889600 count = 1\n",
"13036800 count = 3\n",
"13068800 count = 1\n",
"18099200 count = 1\n",
"14963200 count = 1\n",
"13459200 count = 1\n",
"17260800 count = 1\n",
"24012800 count = 2\n",
"19206400 count = 2\n",
"26912000 count = 1\n",
"5459200 count = 1\n",
"12102400 count = 1\n",
"7532800 count = 1\n",
"9593600 count = 1\n",
"11123200 count = 1\n",
"4556800 count = 1\n",
"5926400 count = 1\n",
"12755200 count = 1\n",
"6022400 count = 1\n",
"3692800 count = 1\n",
"2470400 count = 1\n",
"2432000 count = 1\n",
"4134400 count = 2\n",
"4390400 count = 1\n",
"4742400 count = 1\n",
"2950400 count = 1\n",
"8774400 count = 1\n",
"14745600 count = 1\n",
"8032000 count = 1\n",
"3366400 count = 1\n",
"5772800 count = 1\n",
"5785600 count = 1\n",
"7436800 count = 1\n",
"19462400 count = 1\n",
"22240000 count = 1\n",
"21280000 count = 1\n",
"5120000 count = 1\n",
"18604800 count = 1\n",
"5952000 count = 1\n",
"3699200 count = 2\n",
"17504000 count = 1\n",
"25056000 count = 1\n",
"13024000 count = 1\n",
"4870400 count = 1\n",
"4230400 count = 1\n",
"12524800 count = 1\n",
"11520000 count = 3\n",
"12582400 count = 1\n",
"8256000 count = 1\n",
"25280000 count = 1\n",
"19276800 count = 1\n",
"46131200 count = 1\n",
"16620800 count = 1\n",
"6067200 count = 1\n",
"8051200 count = 3\n",
"2464000 count = 1\n",
"9465600 count = 1\n",
"9171200 count = 1\n",
"44780800 count = 1\n",
"28006400 count = 1\n",
"24364800 count = 1\n",
"34515200 count = 1\n",
"16448000 count = 1\n",
"7718400 count = 2\n",
"14259200 count = 1\n",
"5734400 count = 1\n",
"7123200 count = 2\n",
"6867200 count = 1\n",
"17529600 count = 1\n",
"14988800 count = 1\n",
"4473600 count = 1\n",
"3046400 count = 1\n",
"7808000 count = 1\n",
"5420800 count = 1\n",
"13766400 count = 1\n",
"8992000 count = 1\n",
"5836800 count = 1\n",
"13376000 count = 1\n",
"14240000 count = 1\n",
"18329600 count = 1\n",
"33414400 count = 1\n",
"24044800 count = 1\n",
"15705600 count = 1\n",
"6220800 count = 1\n",
"14291200 count = 1\n",
"19065600 count = 1\n",
"32748800 count = 1\n",
"10521600 count = 1\n",
"11148800 count = 1\n",
"7315200 count = 1\n",
"15052800 count = 2\n",
"9196800 count = 2\n",
"13228800 count = 2\n",
"10803200 count = 2\n",
"10060800 count = 1\n",
"3468800 count = 1\n",
"2848000 count = 1\n",
"7974400 count = 1\n",
"17094400 count = 1\n",
"6099200 count = 1\n",
"10611200 count = 1\n",
"8742400 count = 1\n",
"6201600 count = 2\n",
"16409600 count = 2\n",
"11840000 count = 1\n",
"4608000 count = 1\n",
"3769600 count = 1\n",
"21036800 count = 1\n",
"25715200 count = 1\n",
"11219200 count = 1\n",
"9798400 count = 1\n",
"5184000 count = 2\n",
"20089600 count = 1\n",
"16672000 count = 1\n",
"10336000 count = 2\n",
"4563200 count = 1\n",
"2956800 count = 1\n",
"6374400 count = 3\n",
"6956800 count = 1\n",
"17971200 count = 1\n",
"4896000 count = 1\n",
"5075200 count = 1\n",
"5280000 count = 2\n",
"3104000 count = 1\n",
"29836800 count = 1\n",
"15372800 count = 1\n",
"8569600 count = 1\n",
"7276800 count = 1\n",
"5907200 count = 1\n",
"2547200 count = 1\n",
"2745600 count = 1\n",
"3737600 count = 2\n",
"7929600 count = 1\n",
"6816000 count = 1\n",
"4601600 count = 1\n",
"13171200 count = 1\n",
"4569600 count = 1\n",
"5478400 count = 1\n",
"4524800 count = 1\n",
"2784000 count = 1\n",
"5049600 count = 1\n",
"3001600 count = 2\n",
"23270400 count = 1\n",
"14681600 count = 1\n",
"17817600 count = 2\n",
"9100800 count = 2\n",
"6752000 count = 1\n",
"2873600 count = 1\n",
"2886400 count = 1\n",
"7936000 count = 2\n",
"8748800 count = 1\n",
"19801600 count = 1\n",
"10035200 count = 2\n",
"7628800 count = 1\n",
"6246400 count = 1\n",
"5990400 count = 2\n",
"4595200 count = 1\n",
"6297600 count = 1\n",
"5964800 count = 2\n",
"17926400 count = 1\n",
"28633600 count = 1\n",
"42073600 count = 1\n",
"12256000 count = 1\n",
"3564800 count = 1\n",
"11334400 count = 1\n",
"15891200 count = 1\n",
"19750400 count = 1\n",
"10489600 count = 1\n",
"13088000 count = 1\n",
"9683200 count = 1\n",
"7244800 count = 1\n",
"10726400 count = 1\n",
"30355200 count = 1\n",
"24134400 count = 2\n",
"15596800 count = 1\n",
"8627200 count = 2\n",
"10630400 count = 1\n",
"10636800 count = 1\n",
"10681600 count = 2\n",
"15065600 count = 1\n",
"9049600 count = 1\n",
"11008000 count = 1\n",
"4691200 count = 1\n",
"17606400 count = 1\n",
"12614400 count = 1\n",
"7712000 count = 1\n",
"14060800 count = 2\n",
"6457600 count = 1\n",
"6195200 count = 1\n",
"4025600 count = 1\n",
"14003200 count = 1\n",
"13030400 count = 1\n",
"13811200 count = 3\n",
"4998400 count = 1\n",
"6278400 count = 1\n",
"3500800 count = 1\n",
"6150400 count = 1\n",
"8140800 count = 1\n",
"12441600 count = 1\n",
"20870400 count = 1\n",
"19302400 count = 2\n",
"15660800 count = 1\n",
"10982400 count = 1\n",
"13344000 count = 1\n",
"21868800 count = 1\n",
"22316800 count = 1\n",
"20172800 count = 1\n",
"12601600 count = 1\n",
"18796800 count = 1\n",
"14739200 count = 1\n",
"11539200 count = 1\n",
"11270400 count = 1\n",
"9811200 count = 1\n",
"13286400 count = 1\n",
"14284800 count = 3\n",
"4000000 count = 1\n",
"4153600 count = 1\n",
"17254400 count = 1\n",
"35795200 count = 1\n",
"9862400 count = 1\n",
"20044800 count = 1\n",
"11974400 count = 1\n",
"12998400 count = 1\n",
"2624000 count = 1\n",
"10720000 count = 1\n",
"18336000 count = 1\n",
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"9785600 count = 1\n",
"7392000 count = 1\n",
"24614400 count = 1\n",
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"7801600 count = 1\n",
"24608000 count = 1\n",
"14361600 count = 1\n",
"15161600 count = 1\n",
"15987200 count = 1\n",
"21209600 count = 1\n",
"24723200 count = 2\n",
"13216000 count = 1\n",
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"12627200 count = 1\n",
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"10265600 count = 1\n",
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"3142400 count = 1\n",
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"9113600 count = 1\n",
"10025600 count = 1\n",
"26134400 count = 1\n",
"13430400 count = 1\n",
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"3968000 count = 1\n",
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"5200000 count = 1\n",
"6451200 count = 2\n",
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"9440000 count = 1\n",
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"4048000 count = 1\n",
"2019200 count = 1\n",
"2880000 count = 1\n",
"8435200 count = 2\n",
"3913600 count = 1\n",
"5088000 count = 2\n",
"5145600 count = 1\n",
"6704000 count = 2\n",
"5414400 count = 1\n",
"8393600 count = 1\n",
"2832000 count = 1\n",
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"5068800 count = 1\n",
"3136000 count = 1\n",
"2851200 count = 1\n",
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"20124800 count = 1\n",
"16822400 count = 1\n",
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"35849600 count = 1\n",
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"7225600 count = 1\n",
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"5744000 count = 1\n",
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"2243200 count = 1\n",
"4284800 count = 1\n",
"4300800 count = 1\n",
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"21984000 count = 1\n",
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"3024000 count = 1\n",
"12044800 count = 2\n",
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"65980800 count = 1\n",
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"27456000 count = 1\n",
"27443200 count = 1\n",
"19040000 count = 1\n",
"3849600 count = 1\n",
"4326400 count = 1\n",
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"10966400 count = 1\n",
"4102400 count = 1\n",
"10716800 count = 1\n",
"7088000 count = 1\n",
"5641600 count = 1\n",
"5462400 count = 1\n",
"7968000 count = 2\n",
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"5312000 count = 1\n",
"10534400 count = 1\n",
"11078400 count = 1\n",
"13795200 count = 1\n",
"20320000 count = 1\n",
"4982400 count = 1\n",
"6928000 count = 1\n",
"10640000 count = 3\n",
"2150400 count = 1\n",
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"4838400 count = 1\n",
"6224000 count = 1\n",
"9264000 count = 1\n",
"8169600 count = 3\n",
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"6720000 count = 1\n",
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"7190400 count = 1\n",
"7580800 count = 1\n",
"7910400 count = 1\n",
"6710400 count = 1\n",
"6153600 count = 1\n",
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"7513600 count = 1\n",
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"13628800 count = 1\n",
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"10998400 count = 1\n",
"8544000 count = 2\n",
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"7657600 count = 1\n",
"27360000 count = 1\n",
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"34179200 count = 1\n",
"35827200 count = 1\n",
"11635200 count = 1\n",
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"24617600 count = 1\n",
"12640000 count = 1\n",
"5606400 count = 1\n",
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"3107200 count = 1\n",
"2966400 count = 1\n",
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"6873600 count = 1\n",
"45456000 count = 1\n",
"31564800 count = 1\n",
"17628800 count = 2\n",
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"7385600 count = 1\n",
"13411200 count = 1\n",
"6598400 count = 1\n",
"10675200 count = 1\n",
"16867200 count = 1\n",
"5776000 count = 1\n",
"3248000 count = 1\n",
"6240000 count = 1\n",
"8316800 count = 1\n",
"9184000 count = 1\n",
"3801600 count = 1\n",
"16384000 count = 1\n",
"11763200 count = 1\n",
"26864000 count = 1\n",
"20364800 count = 1\n",
"16771200 count = 2\n",
"6080000 count = 2\n",
"10912000 count = 2\n",
"11923200 count = 1\n",
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"13577600 count = 1\n",
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"46592000 count = 1\n",
"30432000 count = 1\n",
"17248000 count = 1\n",
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"18966400 count = 1\n",
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"22262400 count = 1\n",
"6137600 count = 1\n",
"33443200 count = 1\n",
"7696000 count = 2\n",
"7952000 count = 2\n",
"11449600 count = 1\n",
"3228800 count = 2\n",
"5795200 count = 1\n",
"4905600 count = 1\n",
"9513600 count = 4\n",
"4614400 count = 1\n",
"4729600 count = 1\n",
"7795200 count = 2\n",
"18800000 count = 1\n",
"8451200 count = 2\n",
"12531200 count = 1\n",
"13212800 count = 1\n",
"14067200 count = 1\n",
"19504000 count = 1\n",
"6272000 count = 1\n",
"11900800 count = 1\n",
"10915200 count = 1\n",
"14630400 count = 2\n",
"7299200 count = 1\n",
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"6185600 count = 2\n",
"12489600 count = 1\n",
"12931200 count = 1\n",
"5571200 count = 1\n",
"3532800 count = 1\n",
"13433600 count = 1\n",
"54953600 count = 1\n",
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"23536000 count = 1\n",
"13833600 count = 1\n",
"15542400 count = 1\n",
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"10646400 count = 1\n",
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"20492800 count = 1\n",
"14025600 count = 1\n",
"10089600 count = 1\n",
"11235200 count = 1\n",
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"4736000 count = 1\n",
"3363200 count = 1\n",
"6256000 count = 1\n",
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"2704000 count = 1\n",
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"8320000 count = 1\n",
"29497600 count = 1\n",
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"3414400 count = 1\n",
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"8739200 count = 1\n",
"3920000 count = 1\n",
"5424000 count = 1\n",
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"21219200 count = 1\n",
"15299200 count = 1\n",
"8592000 count = 1\n",
"11392000 count = 1\n",
"8208000 count = 2\n",
"22291200 count = 1\n",
"6825600 count = 2\n",
"8768000 count = 1\n",
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"8560000 count = 1\n",
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"13033600 count = 1\n",
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"8144000 count = 1\n",
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"11440000 count = 1\n",
"10464000 count = 1\n",
"8665600 count = 2\n",
"4873600 count = 1\n",
"16172800 count = 1\n",
"11772800 count = 1\n",
"18742400 count = 1\n",
"12643200 count = 1\n",
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"31046400 count = 1\n",
"6899200 count = 1\n",
"11456000 count = 1\n",
"6275200 count = 1\n",
"8646400 count = 1\n",
"11728000 count = 1\n",
"3865600 count = 1\n",
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"44304000 count = 1\n",
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"16009600 count = 2\n",
"21270400 count = 1\n",
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"6854400 count = 1\n",
"5417600 count = 1\n",
"4617600 count = 1\n",
"8982400 count = 1\n",
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"23894400 count = 1\n",
"13219200 count = 1\n",
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"12310400 count = 1\n",
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"9008000 count = 1\n",
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"16400000 count = 1\n",
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"5945600 count = 1\n",
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"7424000 count = 1\n",
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"43856000 count = 1\n",
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"35321600 count = 1\n",
"10633600 count = 1\n",
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"16883200 count = 1\n",
"10294400 count = 1\n",
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"9203200 count = 1\n",
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"37862400 count = 1\n",
"13715200 count = 1\n",
"22233600 count = 2\n",
"32624000 count = 1\n",
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"18636800 count = 1\n",
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"9283200 count = 1\n",
"10220800 count = 1\n",
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"12368000 count = 1\n",
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"18694400 count = 1\n",
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"11795200 count = 1\n",
"10857600 count = 1\n",
"19334400 count = 1\n",
"23891200 count = 1\n",
"12585600 count = 1\n",
"10009600 count = 1\n",
"27504000 count = 1\n",
"12560000 count = 1\n",
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"37715200 count = 1\n",
"15158400 count = 1\n",
"35056000 count = 1\n",
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"22844800 count = 1\n",
"35011200 count = 1\n",
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"55404800 count = 1\n",
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"22876800 count = 1\n",
"21052800 count = 1\n",
"22060800 count = 1\n",
"15366400 count = 1\n",
"6678400 count = 1\n",
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"31881600 count = 1\n",
"55968000 count = 1\n",
"38784000 count = 2\n",
"30348800 count = 1\n",
"17452800 count = 1\n",
"18057600 count = 1\n",
"23872000 count = 1\n",
"16592000 count = 1\n",
"7520000 count = 2\n",
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"12230400 count = 1\n",
"22416000 count = 1\n",
"45699200 count = 1\n",
"24499200 count = 1\n",
"95052800 count = 1\n",
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"22521600 count = 1\n",
"19878400 count = 1\n",
"33888000 count = 1\n",
"42982400 count = 1\n",
"27363200 count = 1\n",
"13270400 count = 1\n",
"4166400 count = 1\n",
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"10848000 count = 1\n",
"2249600 count = 1\n",
"1504000 count = 1\n",
"6425600 count = 1\n",
"9884800 count = 1\n",
"23193600 count = 2\n",
"26899200 count = 1\n",
"17171200 count = 1\n",
"9936000 count = 1\n",
"6918400 count = 1\n",
"2467200 count = 1\n",
"6969600 count = 2\n",
"3296000 count = 1\n",
"8179200 count = 1\n",
"14553600 count = 1\n",
"17657600 count = 1\n",
"22099200 count = 1\n",
"3609600 count = 1\n",
"13203200 count = 1\n",
"25052800 count = 1\n",
"35548800 count = 1\n",
"15801600 count = 1\n",
"20208000 count = 1\n",
"11321600 count = 1\n",
"30368000 count = 1\n",
"15936000 count = 2\n",
"16768000 count = 1\n",
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"21276800 count = 1\n",
"18355200 count = 1\n",
"18614400 count = 1\n",
"11417600 count = 2\n",
"25654400 count = 1\n",
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"14918400 count = 1\n",
"230883200 count = 1\n",
"55622400 count = 1\n",
"30534400 count = 1\n",
"34297600 count = 1\n",
"39491200 count = 1\n",
"34908800 count = 1\n",
"9980800 count = 1\n",
"24441600 count = 1\n",
"11897600 count = 1\n",
"12515200 count = 1\n",
"13542400 count = 1\n",
"18224000 count = 1\n",
"51459200 count = 1\n",
"25683200 count = 1\n",
"30758400 count = 1\n",
"12336000 count = 1\n",
"11001600 count = 1\n",
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"13168000 count = 3\n",
"22684800 count = 1\n",
"13398400 count = 1\n",
"29830400 count = 1\n",
"16979200 count = 1\n",
"10448000 count = 1\n",
"11622400 count = 2\n",
"18272000 count = 1\n",
"9174400 count = 1\n",
"25945600 count = 1\n",
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"7036800 count = 1\n",
"49808000 count = 1\n",
"50288000 count = 1\n",
"30998400 count = 1\n",
"28678400 count = 1\n",
"39897600 count = 1\n",
"2505600 count = 1\n",
"19548800 count = 1\n",
"25312000 count = 1\n",
"29248000 count = 1\n",
"17305600 count = 1\n",
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"18534400 count = 1\n",
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"18675200 count = 1\n",
"6660800 count = 1\n",
"7484800 count = 1\n",
"26172800 count = 1\n",
"20684800 count = 1\n",
"15627200 count = 1\n",
"8899200 count = 1\n",
"13782400 count = 1\n",
"15396800 count = 1\n",
"19584000 count = 1\n",
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"98100800 count = 1\n",
"42499200 count = 1\n",
"11964800 count = 1\n",
"30825600 count = 2\n",
"13075200 count = 1\n",
"14678400 count = 1\n",
"15980800 count = 1\n",
"10627200 count = 2\n",
"2838400 count = 1\n",
"6268800 count = 1\n",
"15427200 count = 1\n",
"14483200 count = 1\n",
"21254400 count = 1\n",
"19601600 count = 2\n",
"50212800 count = 1\n",
"100820800 count = 1\n",
"43163200 count = 1\n",
"32996800 count = 1\n",
"29091200 count = 1\n",
"25948800 count = 1\n",
"12182400 count = 1\n",
"11731200 count = 2\n",
"14184000 count = 1\n",
"17828800 count = 3\n",
"47204800 count = 1\n",
"17454400 count = 1\n",
"14654400 count = 1\n",
"10544000 count = 1\n",
"14603200 count = 1\n",
"6355200 count = 1\n",
"7809600 count = 1\n",
"7152000 count = 1\n",
"21353600 count = 1\n",
"16435200 count = 1\n",
"7992000 count = 1\n",
"24648000 count = 1\n",
"24635200 count = 1\n",
"51344000 count = 1\n",
"29636800 count = 1\n",
"35769600 count = 1\n",
"16590400 count = 1\n",
"45592000 count = 1\n",
"29049600 count = 1\n",
"24755200 count = 1\n",
"16800000 count = 1\n",
"23316800 count = 1\n",
"24601600 count = 1\n",
"53769600 count = 1\n",
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"20856000 count = 1\n",
"25307200 count = 1\n",
"10019200 count = 1\n",
"10828800 count = 1\n",
"7552000 count = 2\n",
"5190400 count = 1\n",
"12132800 count = 1\n",
"19550400 count = 1\n",
"16353600 count = 1\n",
"21577600 count = 1\n",
"62248000 count = 1\n",
"24104000 count = 1\n",
"15649600 count = 1\n",
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"27884800 count = 1\n",
"24955200 count = 1\n",
"22227200 count = 1\n",
"30414400 count = 1\n",
"8355200 count = 1\n",
"11915200 count = 1\n",
"25448000 count = 1\n",
"27187200 count = 1\n",
"7856000 count = 1\n",
"14595200 count = 1\n",
"12803200 count = 1\n",
"12648000 count = 1\n",
"7182400 count = 1\n",
"75067200 count = 1\n",
"46024000 count = 1\n",
"13446400 count = 1\n",
"17846400 count = 2\n",
"27382400 count = 1\n",
"20121600 count = 1\n",
"31856000 count = 1\n",
"8209600 count = 1\n",
"13496000 count = 1\n",
"25880000 count = 1\n",
"9456000 count = 1\n",
"15163200 count = 1\n",
"16769600 count = 1\n",
"8283200 count = 2\n",
"7072000 count = 1\n",
"10588800 count = 2\n",
"8380800 count = 1\n",
"5521600 count = 1\n",
"10008000 count = 1\n",
"7928000 count = 1\n",
"5326400 count = 1\n",
"9825600 count = 1\n",
"14057600 count = 2\n",
"19377600 count = 1\n",
"4980800 count = 1\n",
"2979200 count = 1\n",
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"5224000 count = 1\n",
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"44184000 count = 1\n",
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"17512000 count = 1\n",
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"8254400 count = 1\n",
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"9028800 count = 1\n",
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"17932800 count = 1\n",
"21544000 count = 1\n",
"19393600 count = 1\n",
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"5436800 count = 1\n",
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"17177600 count = 1\n",
"15817600 count = 1\n",
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"14352000 count = 1\n",
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"37390400 count = 1\n",
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"20020800 count = 1\n",
"37433600 count = 1\n",
"23048000 count = 1\n",
"28564800 count = 1\n",
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"16916800 count = 1\n",
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"11052800 count = 1\n",
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"28488000 count = 1\n",
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"21622400 count = 1\n",
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"23670400 count = 1\n",
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"18462400 count = 1\n",
"51876800 count = 1\n",
"29910400 count = 1\n",
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"15497600 count = 2\n",
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"28110400 count = 1\n",
"30804800 count = 1\n",
"22121600 count = 1\n",
"24486400 count = 1\n",
"36033600 count = 1\n",
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"9852800 count = 2\n",
"13091200 count = 1\n",
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"27177600 count = 1\n",
"15168000 count = 1\n",
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"15528000 count = 1\n",
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"28883200 count = 1\n",
"31819200 count = 1\n",
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"19078400 count = 1\n",
"5404800 count = 1\n",
"12852800 count = 1\n",
"10185600 count = 1\n",
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"9481600 count = 1\n",
"7142400 count = 1\n",
"7312000 count = 1\n",
"15561600 count = 1\n",
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"34544000 count = 1\n",
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"9598400 count = 1\n",
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"8177600 count = 1\n",
"10121600 count = 1\n",
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"39409600 count = 1\n",
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"29425600 count = 1\n",
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"15912000 count = 1\n",
"15521600 count = 1\n",
"14241600 count = 1\n",
"17056000 count = 1\n",
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"21488000 count = 1\n",
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"26108800 count = 1\n",
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"10761600 count = 1\n",
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"7348800 count = 1\n",
"6633600 count = 1\n",
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"2792000 count = 1\n",
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"10102400 count = 1\n",
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"11059200 count = 1\n",
"10155200 count = 1\n",
"11448000 count = 1\n",
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"12312000 count = 2\n",
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"5830400 count = 1\n",
"4414400 count = 1\n",
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"11529600 count = 1\n",
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"5846400 count = 1\n",
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"37404800 count = 1\n",
"10126400 count = 1\n",
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"15409600 count = 1\n",
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"13712000 count = 1\n",
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"9052800 count = 1\n",
"19238400 count = 1\n",
"6182400 count = 1\n",
"3256000 count = 1\n",
"8643200 count = 1\n",
"4316800 count = 1\n",
"6728000 count = 1\n",
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"3448000 count = 1\n",
"12320000 count = 1\n",
"19796800 count = 1\n",
"16790400 count = 1\n",
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"33296000 count = 1\n",
"24040000 count = 1\n",
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"15577600 count = 1\n",
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"13648000 count = 1\n",
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"9521600 count = 1\n",
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"4675200 count = 1\n",
"9004800 count = 1\n",
"5305600 count = 1\n",
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"10694400 count = 1\n",
"18528000 count = 1\n",
"28326400 count = 1\n",
"15448000 count = 1\n",
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"33334400 count = 1\n",
"29948800 count = 1\n",
"17140800 count = 1\n",
"13366400 count = 1\n",
"14400000 count = 1\n",
"11918400 count = 1\n",
"8492800 count = 1\n",
"8134400 count = 1\n",
"14844800 count = 2\n",
"8652800 count = 1\n",
"8827200 count = 1\n",
"10027200 count = 1\n",
"6990400 count = 1\n",
"6432000 count = 1\n",
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"14585600 count = 1\n",
"22808000 count = 1\n",
"13638400 count = 1\n",
"4705600 count = 1\n",
"5400000 count = 1\n",
"7891200 count = 1\n",
"3828800 count = 1\n",
"11545600 count = 1\n",
"7499200 count = 1\n",
"6507200 count = 1\n",
"9036800 count = 2\n",
"14073600 count = 2\n",
"21200000 count = 1\n",
"15035200 count = 1\n",
"41262400 count = 1\n",
"24569600 count = 1\n",
"33691200 count = 2\n",
"15160000 count = 1\n",
"20174400 count = 1\n",
"42720000 count = 1\n",
"34699200 count = 1\n",
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"15840000 count = 1\n",
"11044800 count = 1\n",
"24323200 count = 1\n",
"35280000 count = 1\n",
"36694400 count = 1\n",
"18201600 count = 1\n",
"8963200 count = 2\n",
"9838400 count = 1\n",
"6932800 count = 1\n",
"10361600 count = 1\n",
"7001600 count = 2\n",
"12483200 count = 2\n",
"13227200 count = 1\n",
"14868800 count = 1\n",
"4715200 count = 1\n",
"10072000 count = 1\n",
"15353600 count = 1\n",
"8838400 count = 1\n",
"155107200 count = 1\n",
"53296000 count = 1\n",
"20704000 count = 1\n",
"17865600 count = 1\n",
"18830400 count = 1\n",
"91348800 count = 1\n",
"52492800 count = 1\n",
"64601600 count = 1\n",
"33582400 count = 1\n",
"28995200 count = 1\n",
"21974400 count = 2\n",
"13099200 count = 1\n",
"16052800 count = 1\n",
"16163200 count = 2\n",
"8216000 count = 1\n",
"32574400 count = 1\n",
"27968000 count = 1\n",
"26905600 count = 1\n",
"33883200 count = 1\n",
"14272000 count = 1\n",
"35913600 count = 1\n",
"20720000 count = 1\n",
"43569600 count = 1\n",
"37025600 count = 1\n",
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"51148800 count = 1\n",
"28988800 count = 1\n",
"45396800 count = 1\n",
"29169600 count = 1\n",
"19419200 count = 1\n",
"20251200 count = 1\n",
"27092800 count = 1\n",
"23091200 count = 1\n",
"13393600 count = 1\n",
"10697600 count = 1\n",
"14236800 count = 1\n",
"8064000 count = 1\n",
"19673600 count = 1\n",
"27465600 count = 1\n",
"44683200 count = 1\n",
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"67012800 count = 1\n",
"27630400 count = 1\n",
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"56521600 count = 1\n",
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"41870400 count = 1\n",
"65883200 count = 1\n",
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"28198400 count = 2\n",
"44153600 count = 1\n",
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"18510400 count = 1\n",
"33270400 count = 1\n",
"41048000 count = 1\n",
"21284800 count = 1\n",
"20052800 count = 1\n",
"12297600 count = 1\n",
"15694400 count = 1\n",
"16891200 count = 1\n",
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"13748800 count = 1\n",
"75950400 count = 1\n",
"30227200 count = 1\n",
"43256000 count = 1\n",
"29601600 count = 1\n",
"26436800 count = 1\n",
"29446400 count = 1\n",
"17380800 count = 1\n",
"12296000 count = 1\n",
"12038400 count = 1\n",
"43249600 count = 1\n",
"21246400 count = 1\n",
"15814400 count = 1\n",
"54043200 count = 1\n",
"23196800 count = 1\n",
"13568000 count = 1\n",
"23636800 count = 1\n",
"22196800 count = 2\n",
"8180800 count = 1\n",
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"13601600 count = 1\n",
"43329600 count = 1\n",
"10724800 count = 1\n",
"7755200 count = 1\n",
"7086400 count = 1\n",
"13790400 count = 1\n",
"15718400 count = 1\n",
"14448000 count = 1\n",
"22536000 count = 1\n",
"15017600 count = 1\n",
"12180800 count = 1\n",
"15043200 count = 2\n",
"29755200 count = 1\n",
"29259200 count = 1\n",
"12014400 count = 1\n",
"16035200 count = 1\n",
"6456000 count = 1\n",
"10100800 count = 1\n",
"17478400 count = 1\n",
"14211200 count = 1\n",
"23494400 count = 1\n",
"96963200 count = 1\n",
"35070400 count = 1\n",
"26440000 count = 1\n",
"20854400 count = 1\n",
"15356800 count = 1\n",
"18153600 count = 1\n",
"16988800 count = 1\n",
"15555200 count = 1\n",
"22312000 count = 1\n",
"7688000 count = 1\n",
"16760000 count = 1\n",
"27803200 count = 1\n",
"28356800 count = 1\n",
"17524800 count = 1\n",
"15136000 count = 1\n",
"16852800 count = 1\n",
"34308800 count = 1\n",
"12076800 count = 1\n",
"12636800 count = 1\n",
"8438400 count = 1\n",
"11729600 count = 1\n",
"19564800 count = 1\n",
"8083200 count = 1\n",
"16376000 count = 1\n",
"40486400 count = 1\n",
"29926400 count = 1\n",
"18110400 count = 1\n",
"13145600 count = 1\n",
"17776000 count = 1\n",
"15006400 count = 3\n",
"15028800 count = 2\n",
"30713600 count = 1\n",
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"14676800 count = 1\n",
"15041600 count = 1\n",
"19166400 count = 1\n",
"19091200 count = 1\n",
"23411200 count = 1\n",
"26649600 count = 1\n",
"26894400 count = 1\n",
"24675200 count = 1\n",
"12192000 count = 1\n",
"25968000 count = 1\n",
"12118400 count = 2\n",
"12128000 count = 1\n",
"11544000 count = 1\n",
"10096000 count = 1\n",
"18270400 count = 2\n",
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"12037600 count = 3\n",
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"33618000 count = 1\n",
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"15620800 count = 1\n",
"14090000 count = 1\n",
"12110800 count = 1\n",
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"2760800 count = 1\n",
"5840000 count = 1\n",
"6976400 count = 1\n",
"6948000 count = 1\n",
"9476800 count = 2\n",
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"18543600 count = 1\n",
"17722000 count = 1\n",
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"18553600 count = 1\n",
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"14024800 count = 1\n",
"13901600 count = 1\n",
"9051600 count = 1\n",
"21312400 count = 1\n",
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"20340400 count = 1\n",
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"13014400 count = 1\n",
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"11877600 count = 1\n",
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"21678400 count = 1\n",
"23330400 count = 1\n",
"15773200 count = 1\n",
"16816800 count = 1\n",
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"13410000 count = 1\n",
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"10560800 count = 1\n",
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"13027200 count = 1\n",
"12272800 count = 1\n",
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"10365600 count = 1\n",
"8839600 count = 1\n",
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"8368800 count = 2\n",
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"10201600 count = 1\n",
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"8886800 count = 1\n",
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"20007200 count = 1\n",
"16362800 count = 1\n",
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"22387200 count = 1\n",
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"25678000 count = 1\n",
"17960400 count = 1\n",
"18070000 count = 1\n",
"23107600 count = 1\n",
"17029600 count = 1\n",
"25134800 count = 1\n",
"9912400 count = 1\n",
"14983600 count = 1\n",
"16124400 count = 1\n",
"11985600 count = 1\n",
"17037600 count = 2\n",
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"12568000 count = 1\n",
"11967600 count = 1\n",
"27260000 count = 1\n",
"26127600 count = 1\n",
"16188000 count = 1\n",
"19342400 count = 1\n",
"25328000 count = 1\n",
"17732800 count = 1\n",
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"11916800 count = 1\n",
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"17630400 count = 1\n",
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"16889600 count = 1\n",
"22029600 count = 1\n",
"17730800 count = 1\n",
"30284000 count = 1\n",
"23519200 count = 2\n",
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"17374800 count = 1\n",
"17306400 count = 1\n",
"21996800 count = 1\n",
"30248000 count = 1\n",
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"33250000 count = 2\n",
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"21252000 count = 1\n",
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"13444400 count = 1\n",
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"11850400 count = 1\n",
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"15037200 count = 1\n",
"14262400 count = 1\n",
"17129200 count = 1\n",
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"14022800 count = 1\n",
"15532800 count = 1\n",
"16766800 count = 1\n",
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"19328000 count = 1\n",
"19556400 count = 1\n",
"16744400 count = 1\n",
"23352800 count = 1\n",
"16585600 count = 1\n",
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"18296800 count = 2\n",
"27023200 count = 2\n",
"19050000 count = 1\n",
"21058800 count = 1\n",
"18310400 count = 1\n",
"43244400 count = 1\n",
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"15534800 count = 1\n",
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"14944400 count = 1\n",
"18190800 count = 1\n",
"15902800 count = 1\n",
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"12016000 count = 1\n",
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"13445600 count = 1\n",
"13383600 count = 1\n",
"15027200 count = 1\n",
"13476400 count = 1\n",
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"10763200 count = 1\n",
"12452800 count = 1\n",
"12374400 count = 1\n",
"8216400 count = 1\n",
"13846800 count = 1\n",
"14442800 count = 1\n",
"14154800 count = 1\n",
"18273600 count = 1\n",
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"10676400 count = 1\n",
"13426000 count = 1\n",
"12764800 count = 1\n",
"12817200 count = 1\n",
"11526400 count = 1\n",
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"7944400 count = 1\n",
"4364800 count = 1\n",
"6422400 count = 1\n",
"5760400 count = 1\n",
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"13084800 count = 1\n",
"15736000 count = 1\n",
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"13817600 count = 1\n",
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"10834800 count = 1\n",
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"10406400 count = 1\n",
"11915600 count = 1\n",
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"25182000 count = 1\n",
"22420400 count = 1\n",
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"16347600 count = 1\n",
"10298800 count = 1\n",
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"15174000 count = 1\n",
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"12360400 count = 1\n",
"20950800 count = 1\n",
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"13568400 count = 1\n",
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"16738400 count = 1\n",
"20987200 count = 1\n",
"23471600 count = 1\n",
"11909200 count = 1\n",
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"12893600 count = 1\n",
"16022000 count = 1\n",
"20260400 count = 1\n",
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"11834800 count = 1\n",
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"24048000 count = 1\n",
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"32274400 count = 1\n",
"22938800 count = 1\n",
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"17868000 count = 1\n",
"24469200 count = 1\n",
"16649200 count = 1\n",
"18417200 count = 1\n",
"17401200 count = 1\n",
"13008800 count = 1\n",
"13854800 count = 1\n",
"18570800 count = 1\n",
"17094800 count = 1\n",
"17866400 count = 1\n",
"15342800 count = 1\n",
"24372800 count = 1\n",
"16407200 count = 1\n",
"12033200 count = 1\n",
"16754800 count = 1\n",
"11266400 count = 2\n",
"11753600 count = 1\n",
"18920800 count = 1\n",
"43365600 count = 1\n",
"22481200 count = 1\n",
"23306800 count = 1\n",
"21975200 count = 1\n",
"21508400 count = 1\n",
"49643200 count = 1\n",
"17748800 count = 2\n",
"17216800 count = 1\n",
"18504400 count = 1\n",
"20612000 count = 1\n",
"27375200 count = 1\n",
"23270000 count = 1\n",
"22377600 count = 1\n",
"14807600 count = 1\n",
"20356800 count = 1\n",
"14900800 count = 1\n",
"19253200 count = 1\n",
"17187600 count = 1\n",
"12495200 count = 1\n",
"22538000 count = 1\n",
"16937600 count = 1\n",
"18164400 count = 1\n",
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"9814000 count = 1\n",
"15002400 count = 1\n",
"12010000 count = 1\n",
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"14069600 count = 1\n",
"9216400 count = 1\n",
"10575600 count = 1\n",
"13976800 count = 1\n",
"22151600 count = 1\n",
"9841600 count = 2\n",
"9023200 count = 1\n",
"11615600 count = 1\n",
"11724800 count = 2\n",
"12616800 count = 1\n",
"15990800 count = 1\n",
"15651200 count = 1\n",
"19877200 count = 1\n",
"9966400 count = 1\n",
"16018000 count = 1\n",
"10264000 count = 2\n",
"11271600 count = 1\n",
"13081200 count = 1\n",
"10687200 count = 1\n",
"13654000 count = 1\n",
"17823600 count = 1\n",
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"11669200 count = 1\n",
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"10226000 count = 1\n",
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"7801200 count = 1\n",
"12926800 count = 1\n",
"12966400 count = 1\n",
"13539600 count = 1\n",
"11482800 count = 1\n",
"11968000 count = 1\n",
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"15056400 count = 1\n",
"9578800 count = 1\n",
"15178800 count = 1\n",
"13829600 count = 1\n",
"7939600 count = 1\n",
"11913200 count = 1\n",
"11393600 count = 1\n",
"22350800 count = 1\n",
"14365200 count = 2\n",
"13316000 count = 1\n",
"11622800 count = 2\n",
"9404400 count = 1\n",
"8464800 count = 1\n",
"8713200 count = 1\n",
"5837600 count = 1\n",
"7985200 count = 1\n",
"4130800 count = 1\n",
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"6555200 count = 1\n",
"9133200 count = 1\n",
"6558400 count = 1\n",
"10353200 count = 1\n",
"6354400 count = 1\n",
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"17445600 count = 1\n",
"14224400 count = 1\n",
"14455200 count = 1\n",
"13058000 count = 1\n",
"12684000 count = 1\n",
"17984000 count = 1\n",
"12538000 count = 1\n",
"14624800 count = 1\n",
"14888800 count = 1\n",
"7808800 count = 1\n",
"9692000 count = 1\n",
"10240800 count = 1\n",
"10026400 count = 1\n",
"13526400 count = 1\n",
"13060400 count = 1\n",
"8883200 count = 1\n",
"32538000 count = 1\n",
"22739600 count = 1\n",
"20618000 count = 1\n",
"16165600 count = 1\n",
"18373200 count = 2\n",
"16429600 count = 1\n",
"12728400 count = 1\n",
"11588400 count = 1\n",
"15749200 count = 1\n",
"8676800 count = 1\n",
"9682800 count = 1\n",
"9304800 count = 1\n",
"11630400 count = 1\n",
"5018400 count = 1\n",
"5847200 count = 1\n",
"4781600 count = 1\n",
"10294000 count = 1\n",
"8472000 count = 1\n",
"7982400 count = 1\n",
"8774000 count = 1\n",
"7459200 count = 1\n",
"8767200 count = 1\n",
"8110800 count = 2\n",
"8995600 count = 1\n",
"6582000 count = 1\n",
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"17682400 count = 1\n",
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"9004000 count = 1\n",
"10599600 count = 1\n",
"9435600 count = 1\n",
"10494000 count = 1\n",
"12129600 count = 2\n",
"11366800 count = 1\n",
"6800000 count = 1\n",
"5882800 count = 1\n",
"7990000 count = 2\n",
"17296400 count = 1\n",
"19805600 count = 1\n",
"14192800 count = 1\n",
"13925200 count = 1\n",
"16144800 count = 1\n",
"12761200 count = 1\n",
"10465600 count = 1\n",
"12434400 count = 1\n",
"11065200 count = 1\n",
"4116000 count = 1\n",
"8526800 count = 1\n",
"11102800 count = 1\n",
"13196000 count = 1\n",
"9282000 count = 1\n",
"10566400 count = 1\n",
"7366000 count = 1\n",
"8118000 count = 1\n",
"6943600 count = 1\n",
"8705200 count = 1\n",
"8023200 count = 1\n",
"11149600 count = 1\n",
"12144800 count = 1\n",
"7589200 count = 1\n",
"9569200 count = 1\n",
"13598000 count = 1\n",
"12641600 count = 1\n",
"9868000 count = 1\n",
"3276400 count = 1\n",
"2407200 count = 1\n",
"6926000 count = 1\n",
"8840000 count = 1\n",
"11532000 count = 1\n",
"13181200 count = 1\n",
"13903600 count = 1\n",
"19274000 count = 1\n",
"9690400 count = 1\n",
"13144000 count = 1\n",
"10259600 count = 1\n",
"8904400 count = 1\n",
"9261600 count = 1\n",
"13252000 count = 1\n",
"12955600 count = 1\n",
"10830000 count = 1\n",
"20161600 count = 1\n",
"10698800 count = 1\n",
"11152800 count = 1\n",
"14644800 count = 2\n",
"18117200 count = 1\n",
"17563200 count = 1\n",
"19098400 count = 1\n",
"12578000 count = 1\n",
"9709200 count = 1\n",
"12829200 count = 1\n",
"10595600 count = 1\n",
"10039200 count = 1\n",
"7564000 count = 1\n",
"8984400 count = 1\n",
"9246800 count = 1\n",
"13490400 count = 1\n",
"29023200 count = 1\n",
"13220800 count = 1\n",
"13382400 count = 1\n",
"12104400 count = 1\n",
"12122800 count = 1\n",
"19298400 count = 1\n",
"17881200 count = 1\n",
"33430400 count = 1\n",
"17753600 count = 1\n",
"13156000 count = 1\n",
"11044400 count = 1\n",
"7395200 count = 1\n",
"14230800 count = 1\n",
"14322400 count = 1\n",
"11234000 count = 2\n",
"16786800 count = 1\n",
"11380800 count = 2\n",
"12715600 count = 1\n",
"15135600 count = 1\n",
"11246000 count = 1\n",
"9808800 count = 2\n",
"12157600 count = 1\n",
"14674400 count = 1\n",
"17811200 count = 1\n",
"15044400 count = 2\n",
"16306000 count = 1\n",
"9903200 count = 1\n",
"10619200 count = 1\n",
"9957200 count = 1\n",
"11953600 count = 1\n",
"9425600 count = 1\n",
"13455200 count = 1\n",
"14040000 count = 1\n",
"8706000 count = 1\n",
"10446800 count = 1\n",
"14182000 count = 1\n",
"9746800 count = 1\n",
"7401600 count = 1\n",
"9633200 count = 1\n",
"11580000 count = 1\n",
"10090000 count = 1\n",
"15652400 count = 1\n",
"8268000 count = 1\n",
"10639200 count = 1\n",
"12259600 count = 1\n",
"21610000 count = 1\n",
"10364800 count = 1\n",
"8474800 count = 1\n",
"12244800 count = 1\n",
"9319600 count = 1\n",
"11548400 count = 1\n",
"9848400 count = 1\n",
"14965600 count = 1\n",
"12306000 count = 1\n",
"10154800 count = 1\n",
"13808400 count = 1\n",
"13010800 count = 1\n",
"8941200 count = 1\n",
"11935600 count = 1\n",
"8915600 count = 2\n",
"12256400 count = 1\n",
"6636800 count = 1\n",
"9579600 count = 1\n",
"15591600 count = 1\n",
"8080800 count = 1\n",
"7443600 count = 2\n",
"10683200 count = 1\n",
"7514800 count = 1\n",
"17056400 count = 1\n",
"17221600 count = 1\n",
"10714400 count = 1\n",
"12493200 count = 1\n",
"9206800 count = 1\n",
"12792000 count = 1\n",
"10358800 count = 1\n",
"15099600 count = 1\n",
"8870800 count = 1\n",
"7701200 count = 2\n",
"13168800 count = 1\n",
"14384800 count = 1\n",
"8901600 count = 1\n",
"8335600 count = 1\n",
"13946000 count = 1\n",
"10815600 count = 1\n",
"11558800 count = 1\n",
"9865600 count = 1\n",
"13694000 count = 1\n",
"12004000 count = 1\n",
"9716000 count = 1\n",
"18094000 count = 1\n",
"15961200 count = 2\n",
"14341600 count = 1\n",
"14059200 count = 1\n",
"12580400 count = 1\n",
"10203600 count = 1\n",
"9242000 count = 1\n",
"8066400 count = 1\n",
"15493600 count = 1\n",
"12008400 count = 1\n",
"16261200 count = 1\n",
"17891200 count = 1\n",
"18898000 count = 1\n",
"17652800 count = 1\n",
"24379200 count = 1\n",
"14237600 count = 1\n",
"13546400 count = 1\n",
"13589200 count = 1\n",
"13976000 count = 1\n",
"16312000 count = 1\n",
"11306400 count = 1\n",
"16205200 count = 2\n",
"17194800 count = 1\n",
"16024400 count = 1\n",
"10541200 count = 1\n",
"21988800 count = 1\n",
"10696400 count = 1\n",
"12002800 count = 1\n",
"9651600 count = 1\n",
"12441200 count = 1\n",
"11809600 count = 1\n",
"11963200 count = 2\n",
"13857200 count = 1\n",
"8058800 count = 1\n",
"10011600 count = 1\n",
"10439200 count = 1\n",
"11550400 count = 1\n",
"56257200 count = 1\n",
"18594400 count = 1\n",
"12330800 count = 1\n",
"10968800 count = 1\n",
"10862800 count = 1\n",
"10046400 count = 1\n",
"9805200 count = 1\n",
"10348800 count = 1\n",
"8508800 count = 1\n",
"9120800 count = 1\n",
"6140800 count = 1\n",
"12973200 count = 1\n",
"10364400 count = 1\n",
"10092000 count = 1\n",
"5194000 count = 1\n",
"8795600 count = 1\n",
"8164400 count = 1\n",
"8970000 count = 1\n",
"15573200 count = 1\n",
"7921200 count = 1\n",
"10689600 count = 1\n",
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"5734200 count = 1\n",
"8844500 count = 1\n",
"8286300 count = 1\n",
"8124700 count = 1\n",
"6845200 count = 1\n",
"7043800 count = 1\n",
"5356100 count = 1\n",
"5622400 count = 1\n",
"11221100 count = 1\n",
"7990800 count = 1\n",
"7321000 count = 1\n",
"7137300 count = 1\n",
"4826900 count = 1\n",
"8792400 count = 1\n",
"7671500 count = 1\n",
"6702300 count = 1\n",
"9444900 count = 1\n",
"8254500 count = 1\n",
"8544800 count = 1\n",
"18133600 count = 1\n",
"7413900 count = 2\n",
"5676500 count = 1\n",
"5804400 count = 1\n",
"6287300 count = 1\n",
"6493800 count = 1\n",
"6903000 count = 1\n",
"6216100 count = 1\n",
"5863700 count = 1\n",
"6784300 count = 1\n",
"4990200 count = 1\n",
"8276800 count = 1\n",
"6316400 count = 1\n",
"6322900 count = 1\n",
"6242700 count = 1\n",
"6841600 count = 1\n",
"8591200 count = 1\n",
"8866800 count = 1\n",
"6870100 count = 1\n",
"11403300 count = 1\n",
"11898200 count = 1\n",
"8669000 count = 1\n",
"5670500 count = 1\n",
"7183900 count = 1\n",
"7284600 count = 1\n",
"7185300 count = 1\n",
"14538400 count = 1\n",
"66610700 count = 1\n",
"23883400 count = 1\n",
"22153800 count = 1\n",
"18632200 count = 1\n",
"21901300 count = 1\n",
"24482600 count = 1\n",
"18591500 count = 1\n",
"15761900 count = 1\n",
"10953600 count = 1\n",
"10961100 count = 1\n",
"8826500 count = 1\n",
"10758500 count = 1\n",
"14436500 count = 1\n",
"11183800 count = 1\n",
"8916600 count = 1\n",
"22063400 count = 1\n",
"4651418 count = 1\n",
"Total count = 8036\n",
" Date Open Count\n",
"0 1992-06-26 0.328125 1\n",
"1 1992-06-29 0.339844 1\n",
"2 1992-06-30 0.367188 1\n",
"3 1992-07-01 0.351563 1\n",
"4 1992-07-02 0.359375 1\n",
"... ... ... ...\n",
"8031 2024-05-17 75.269997 1\n",
"8032 2024-05-20 77.680000 1\n",
"8033 2024-05-21 77.559998 1\n",
"8034 2024-05-22 77.699997 1\n",
"8035 2024-05-23 80.099998 1\n",
"\n",
"[8036 rows x 3 columns]\n"
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]
}
],
"source": [
1 lab fix
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"s_values = df[\"Volume\"].unique()\n",
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"print(s_values)\n",
"\n",
"s_total = 0\n",
"for s_value in s_values:\n",
1 lab fix
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" count = df[df[\"Volume\"] == s_value].shape[0]\n",
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" s_total += count\n",
" print(s_value, \"count =\", count)\n",
"print(\"Total count = \", s_total)\n",
"\n",
1 lab fix
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"print(df.groupby([\"Date\", \"Open\"]).size().reset_index(name=\"Count\")) # type: ignore"
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Визуализация - Исходные данные"
]
},
{
"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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" Volume Open Low\n",
"Date \n",
"1992-06-26 224358400 0.328125 0.320313\n",
"1992-06-29 58732800 0.339844 0.332031\n",
"1992-06-30 34777600 0.367188 0.343750\n",
"1992-07-01 18316800 0.351563 0.339844\n",
"1992-07-02 13996800 0.359375 0.347656\n",
"... ... ... ...\n",
"2024-05-17 14436500 75.269997 74.919998\n",
"2024-05-20 11183800 77.680000 76.709999\n",
"2024-05-21 8916600 77.559998 77.500000\n",
"2024-05-22 22063400 77.699997 77.440002\n",
"2024-05-23 4651418 80.099998 79.169998\n",
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"\n",
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"[8036 rows x 3 columns]\n"
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]
}
],
"source": [
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"data = df[[\"Volume\", \"Open\", \"Low\"]].copy()\n",
"data.dropna(subset=[\"Low\"], inplace=True)\n",
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"print(data)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Визуализация - Сводка пяти чисел\n",
"\n",
"<img src=\"assets/quantile.png\" width=\"400\" style=\"background-color: white\">"
]
},
{
"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
1 lab fix
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" Low \\\n",
" min q1 q2 median q3 \n",
"Open \n",
"0.328125 0.320313 0.320313 0.320313 0.320313 0.320313 \n",
"0.339844 0.332031 0.332031 0.332031 0.332031 0.332031 \n",
"0.351563 0.339844 0.343750 0.347656 0.347656 0.347656 \n",
"0.355469 0.343750 0.344726 0.345703 0.345703 0.346680 \n",
"0.359375 0.347656 0.348633 0.349610 0.349610 0.350586 \n",
"... ... ... ... ... ... \n",
"122.559998 121.389999 121.389999 121.389999 121.389999 121.389999 \n",
"122.930000 122.139999 122.139999 122.139999 122.139999 122.139999 \n",
"124.550003 123.919998 123.919998 123.919998 123.919998 123.919998 \n",
"125.739998 124.250000 124.250000 124.250000 124.250000 124.250000 \n",
"126.080002 124.809998 124.809998 124.809998 124.809998 124.809998 \n",
"\n",
" \n",
" max \n",
"Open \n",
"0.328125 0.320313 \n",
"0.339844 0.332031 \n",
"0.351563 0.347656 \n",
"0.355469 0.347656 \n",
"0.359375 0.351563 \n",
"... ... \n",
"122.559998 121.389999 \n",
"122.930000 122.139999 \n",
"124.550003 123.919998 \n",
"125.739998 124.250000 \n",
"126.080002 124.809998 \n",
"\n",
"[5300 rows x 6 columns]\n",
" Open \n",
" low_iqr iqr high_iqr\n",
"Low \n",
"0.320313 0.328125 0.000000 0.328125\n",
"0.332031 0.339844 0.000000 0.339844\n",
"0.339844 0.351563 0.000000 0.351563\n",
"0.343750 0.349609 0.005860 0.373048\n",
"0.347656 0.344239 0.004882 0.363769\n",
"... ... ... ...\n",
"121.389999 122.559998 0.000000 122.559998\n",
"122.139999 122.930000 0.000000 122.930000\n",
"123.919998 124.550003 0.000000 124.550003\n",
"124.250000 125.739998 0.000000 125.739998\n",
"124.809998 126.080002 0.000000 126.080002\n",
"\n",
"[5223 rows x 3 columns]\n"
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]
},
{
"data": {
"text/plain": [
1 lab fix
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"<Axes: title={'center': 'Open'}, xlabel='Low'>"
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]
},
1 lab fix
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"execution_count": 8,
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"metadata": {},
"output_type": "execute_result"
},
{
"data": {
1 lab fix
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"image/png": "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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def q1(x):\n",
" return x.quantile(0.25)\n",
"\n",
"\n",
"# median = quantile(0.5)\n",
"def q2(x):\n",
" return x.quantile(0.5)\n",
"\n",
"\n",
"def q3(x):\n",
" return x.quantile(0.75)\n",
"\n",
"\n",
"def iqr(x):\n",
" return q3(x) - q1(x)\n",
"\n",
"\n",
"def low_iqr(x):\n",
" return max(0, q1(x) - 1.5 * iqr(x))\n",
"\n",
"\n",
"def high_iqr(x):\n",
" return q3(x) + 1.5 * iqr(x)\n",
"\n",
"\n",
1 lab fix
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"quantiles = data[[\"Low\", \"Open\"]].groupby([\"Open\"]).aggregate([\"min\", q1, q2, \"median\", q3, \"max\"])\n",
1 and 2 lab
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"print(quantiles)\n",
"\n",
1 lab fix
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"iqrs = data[[\"Open\", \"Low\"]].groupby([\"Low\"]).aggregate([low_iqr, iqr, high_iqr])\n",
1 and 2 lab
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"print(iqrs)\n",
"\n",
1 lab fix
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"data.boxplot(column=\"Open\", by=\"Low\")"
1 and 2 lab
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Визуализация - Гистограмма"
]
},
{
"cell_type": "code",
1 lab fix
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"execution_count": 9,
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: ylabel='Frequency'>"
]
},
1 lab fix
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"execution_count": 9,
1 and 2 lab
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"metadata": {},
"output_type": "execute_result"
},
{
"data": {
1 lab fix
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"image/png": "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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
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"data.plot.hist(column=[\"Open\"], bins=80)"
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Визуализация - Точечная диаграмма"
]
},
{
"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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"<Axes: xlabel='Open', ylabel='Low'>"
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]
},
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"execution_count": 10,
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"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"image/png": "iVBORw0KGgoAAAANSUhEUgAAAjsAAAGwCAYAAABPSaTdAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/GU6VOAAAACXBIWXMAAA9hAAAPYQGoP6dpAABEmElEQVR4nO3deXRU9f3/8dckQFizEEJCIECAKCD7agiCaCpWRBGqlWJBSuHXyiIiVazFrWhQ61IWQYUCVkDrt2oVKxWRBIEAgYCiIouBAMZACExCZiATkvv7gzJlIIGQubNk8nyck3PInXs/9517hLz83M9iMQzDEAAAQIAK8nUBAAAAnkTYAQAAAY2wAwAAAhphBwAABDTCDgAACGiEHQAAENAIOwAAIKDV8nUB/qCsrEw5OTlq1KiRLBaLr8sBAACVYBiGTp06pdjYWAUFVdx/Q9iRlJOTo7i4OF+XAQAAquDw4cNq0aJFhZ8TdiQ1atRI0rmHFRoa6uNqAABAZRQWFiouLs75e7wihB3J+eoqNDSUsAMAQDVzpSEoDFAGAAABjbADAAACGmEHAAAENMIOAAAIaIQdAAAQ0Ag7AAAgoBF2AABAQCPsAACAgEbYAQAAAY2wAwAAAhrbRQAAAI/JyitS9gm7Wkc2UHyTBj6pgbADAABMZ7U7NP6tbco4eNJ5bEBClOaO7K6w+rW9WguvsQAAgKmsdocG/SXVJehI0sb9eZq8cofX6yHsAAAAU/122TadtJdccrzUkNbvy9OB4zav1kPYAQAApsnKK9K27JOXPedgPmEHAABUU9kn7Fc8p1aQxQuV/A9hBwAAmKZV4/pXPOdsmeGFSv6HsAMAAK5aVl6R1u05dsn4mzZRDdW7dcRlr20d6d0p6Ew9BwAAlWa1OzRl5U6t35fnPHbxlPJFo3vrxr+su2SQcpCk/glRXl9vh54dAABQaVNW7tSG/XkuxzbuP+4ypTysfm2lTh+k3q1ce3j6/zcUeRs9OwAAoFK+OnzSpUfnvFLDcE4pP99rE1a/tt77fT8dOG7TwXwbKygDAAD/ZrU7NGrRlsueczDfdkmgiW/iu5BzHq+xAADAFY1/a5uKiksve463Bx5Xlk/Dzvr16zV06FDFxsbKYrHoww8/dH5WUlKiRx99VJ07d1aDBg0UGxur0aNHKycnx6WNEydOaNSoUQoNDVV4eLjGjRunoqIiL/8kAAAErqy8oku2frhYp+ahPu/BqYhPw47NZlPXrl01f/78Sz6z2+3KzMzUzJkzlZmZqffff1979uzRHXfc4XLeqFGj9O2332rNmjVatWqV1q9frwkTJnjrRwAAIKCUN6W8MgsFPndXZ0+W5RaLYRjeXdmnAhaLRR988IGGDRtW4TkZGRnq06ePsrOz1bJlS+3evVsdO3ZURkaGevXqJUlavXq1brvtNh05ckSxsbGVundhYaHCwsJUUFCg0NBQM34cAACqlctNKc+3Feuml9IqvLZ3qwi99/t+3ijTRWV/f1erMTsFBQWyWCwKDw+XJKWnpys8PNwZdCQpOTlZQUFB2rKl4kFUxcXFKiwsdPkCAKAmm7JypzbuP+5y7OIp5RWZeXtHT5VlimoTds6cOaNHH31UI0eOdKa33NxcNW3a1OW8WrVqqXHjxsrNza2wrZSUFIWFhTm/4uLiPFo7AAD+7N2th7R+X55KL3rZc35K+dYDJy57fb7d4cny3FYtpp6XlJTonnvukWEYWrBggdvtPfbYY5o2bZrz+8LCQgIPAKBGycor0r+//klz1+1X8dmyy5577FTxZT/39saeV8vvw875oJOdna0vvvjC5Z1cTEyMjh075nL+2bNndeLECcXExFTYZkhIiEJCQjxWMwAA/spqd+j3b2cqPSu/0tdcKct4e2PPq+XXr7HOB519+/bp888/V2RkpMvniYmJslqt2r59u/PYF198obKyMvXt29fb5QIA4Pfu/1vGVQUdSYpsWOeyn/vr+jrn+bRnp6ioSPv373d+f+DAAe3cuVONGzdWs2bN9Itf/EKZmZlatWqVSktLneNwGjdurDp16qhDhw669dZbNX78eC1cuFAlJSWaNGmS7r333krPxAIAoCaw2h0auyRDO49Yr/ra69s00YCEKG3cf9xlXE+wxaKkdk38dn2d83w69Tw1NVWDBg265PiYMWP01FNPKT4+vtzr1q1bpxtvvFHSuUUFJ02apI8//lhBQUEaMWKE5syZo4YNG1a6DqaeAwAC3d0LN11xYcDyhNatpa+fGqwCe4kmr9xx2d3Ova2yv7/9Zp0dXyLsAAACVVZekf6enq0lmw5WuY1102909t74w8ae51X297ffD1AGAABXz2p36NeLt2jXj+6vJXfhBp/+sLHn1SLsAAAQYKx2hxJT1up0yeWnlFeWvw9AvhLCDgAAASIrr0hpe/P09MffmdJedRmAfCWEHQAAqrmdh07qT//6Rt+4+cqqYUiwiopLnd8ntWuiuSO7u1uezxF2AACopsrbvLMqWjWup7kje6hLXLhfDUA2C2EHAIBq6rfLtmlb9tVPJ7/Y0t/0rdYDkK/Er1dQBgAA5fvk6xxTgk5CdOCFm4vRswMAQDVitTs04a1t2lqFBQLL89Ld3Uxpx58RdgAAqCay8oo0dmmGsvPtprTXLS5cXVqEm9KWPyPsAADg58zuzZHObQOxbGwf09rzZ4QdAAD8WNqeY5r23lfKL3KY1mbDkGB9+chNPtvTytsIOwAA+KHsfJuGzt2gwjNnTW/7+eFdakzQkQg7AAD4pZ//db3sDnO2e7hYx+ZhHmnXXzH1HAAAP5Kdb1O7GZ94LOgMSIgK+KnmFyPsAADgJ7LzbRr4YqrMeHHVoM6lv+L7tY0MiO0frhavsQAA8ANWu0ODXkw1pa0BCVGaO7K7Ttgd2pyVL4ukvm0ia1yPznmEHQAAfMxqd6jf7LVy98VVh5hGen5EF3WJC5ckhdWvXWMDzoV4jQUAgA9Z7Q4lzf7C7TE6QRYpqlFdZ9DB/xB2AADwoV8v3iKbo9TtdsoMaf2+PB04bjOhqsDCaywAALwsK69I3/5UqNfW7dfun06Z2vbBfBuvri5C2AEAwEusdoemrNyp9fvyPHaP1pEEnYsRdgAA8JL7/5ahnUesbrdjkWSxnHt1dV6wxaKkdk3o1SkHY3YAAPCwnYdO6mcvp5kSdM4Lq+e63UNSuyY1cg2dyqBnBwAAD/HUaytD0kl7if4+ro/OlhlqHdmAHp3LIOwAAOABWXlFGv23rTpy8rTH7nG2zNCga5t6rP1AQdgBAMBEVrtD49/apoyDJz1+LwYjVw5hBwAAE418Y7N255o7nfxiDEa+OoQdAABM8OXeYxq3NENmblYeJKlrXLga1a3tMu6HwchXh7ADAIAbrHaHbp/zpY5Yz5jedv//bugZVr+2Dhy36WC+jcHIVUDYAQCgijbtz9OvFm01tc37+7XSwGubXhJq4psQcqqKsAMAQBVY7Q7Tg44k3dwhWjckRJnebk3GooIAAFyl7Hybuj2zxvR2I+rXJuh4AGEHAICrsHrXTxr4Yqrp7UbUr62PJvY3vV3wGgsAgEqx2h0a8dpG/XDc7nZbFkntmjbUhAFtlFNwWj1aRtCj40H07AAAcAXZ+Tb1+PMaU4KOdG67h33HivSH//taW7JOqEvzcFPaRfkIOwAAXIbV7tDAF1Nddhg306Yf8jV55Q7PNA5JhB0AACr0z+2HPDIQ+WLr9+XpwHGbx+9TUzFmBwCAi3x1+KQeWJ6pHz2wUGBFDubbWEfHQwg7AADo3C7l3/5UqJf/s0cH8s0Zm3M12NTTcwg7AIAazWp3aMrKnS57T3lCWL1aKjh9ttzPBiRE0avjQYzZAQDUaL9/O9PjQUeSCk6fVfe4sEuO92sbyaaeHkbPDgCgxvp0V47Ss/K9dr8pydeodWQDbc7Kl0VS3zaR9Oh4AWEHAFAj/XP7IT383i6v3vP85p4EHO/y6Wus9evXa+jQoYqNjZXFYtGHH37o8rlhGHriiSfUrFkz1atXT8nJydq3b5/LOSdOnNCoUaMUGhqq8PBwjRs3TkVFRV7
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
1 lab fix
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"image/png": "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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
1 lab fix
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"df.plot.scatter(x=\"High\", y=\"Low\")\n",
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"\n",
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"df.plot.scatter(x=\"Open\", y=\"Low\")"
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Визуализация - Столбчатая диаграмма"
]
},
{
"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
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"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"\n",
"data = {\n",
" \"Date\": [\"1992-06-26\", \"1992-06-29\", \"1992-06-30\", \"1992-07-01\"],\n",
" \"Open\": [0.328125, 0.339844, 0.367188, 0.351563],\n",
" \"High\": [0.347656, 0.367188, 0.371094, 0.359375],\n",
" \"Low\": [0.320313, 0.332031, 0.343750, 0.339844],\n",
" \"Close\": [0.335938, 0.359375, 0.347656, 0.355469],\n",
" \"Adj Close\": [0.260703, 0.278891, 0.269797, 0.275860],\n",
" \"Volume\": [224358400, 58732800, 34777600, 18316800],\n",
"}\n",
"\n",
"# Создание DataFrame\n",
"df = pd.DataFrame(data)\n",
"\n",
"# Группировка данных и построение графика\n",
"plot = df.groupby([\"Date\", \"Low\"]).size().unstack().plot.bar(color=[\"pink\", \"green\"])\n",
"\n",
"# Настройка легенды\n",
"plot.legend([\"Date\", \"Low\"])\n",
"\n",
"# Показать график\n",
"plt.show()"
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Визуализация - Временные ряды"
]
},
{
"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 243 entries, 0 to 242\n",
"Data columns (total 6 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 my_date 243 non-null object \n",
" 1 my_value 243 non-null float64 \n",
" 2 bullet 2 non-null object \n",
" 3 bulletClass 2 non-null object \n",
" 4 label 2 non-null object \n",
" 5 date 243 non-null datetime64[ns]\n",
"dtypes: datetime64[ns](1), float64(1), object(4)\n",
"memory usage: 11.5+ KB\n",
" my_date my_value bullet bulletClass label date\n",
"0 28.03.2023 76.5662 NaN NaN NaN 2023-03-28\n",
"1 31.03.2023 77.0863 NaN NaN NaN 2023-03-31\n",
"2 01.04.2023 77.3233 NaN NaN NaN 2023-04-01\n",
"3 04.04.2023 77.9510 NaN NaN NaN 2023-04-04\n",
"4 05.04.2023 79.3563 NaN NaN NaN 2023-04-05\n",
".. ... ... ... ... ... ...\n",
"238 20.03.2024 92.2243 NaN NaN NaN 2024-03-20\n",
"239 21.03.2024 92.6861 NaN NaN NaN 2024-03-21\n",
"240 22.03.2024 91.9499 NaN NaN NaN 2024-03-22\n",
"241 23.03.2024 92.6118 NaN NaN NaN 2024-03-23\n",
"242 26.03.2024 92.7761 NaN NaN NaN 2024-03-26\n",
"\n",
"[243 rows x 6 columns]\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from datetime import datetime\n",
"import matplotlib.dates as md\n",
1 lab fix
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"import pandas as pd\n",
1 and 2 lab
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"\n",
"ts = pd.read_csv(\"data/dollar.csv\")\n",
"ts[\"date\"] = ts.apply(lambda row: datetime.strptime(row[\"my_date\"], \"%d.%m.%Y\"), axis=1)\n",
"ts.info()\n",
"\n",
"print(ts)\n",
"\n",
"plot = ts.plot.line(x=\"date\", y=\"my_value\")\n",
"plot.xaxis.set_major_locator(md.DayLocator(interval=10))\n",
"plot.xaxis.set_major_formatter(md.DateFormatter(\"%d.%m.%Y\"))\n",
"plot.tick_params(axis=\"x\", labelrotation=90)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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