chore: 添加Stock-Prediction-Models项目文件
添加了Stock-Prediction-Models项目的多个文件，包括数据集、模型代码、README文档和CSS样式文件。这些文件用于股票预测模型的训练和展示，涵盖了LSTM、GRU等深度学习模型的应用。
This commit is contained in:
zhoujie committed
1 parent
f57150dae8
commit
2757a4d0d2
200 files changed
+79402
No files matched your search
+1398
File diff suppressed because it is too large.
Load diff
+807
@@ -0,0 +1,807 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import tensorflow as tf\n",
|
||||
"import numpy as np\n",
|
||||
"import pandas as pd\n",
|
||||
"from datetime import datetime\n",
|
||||
"from datetime import timedelta"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style>\n",
|
||||
" .dataframe thead tr:only-child th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: left;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>date</th>\n",
|
||||
" <th>Cami Dresses</th>\n",
|
||||
" <th>Shirts</th>\n",
|
||||
" <th>Tote Bags</th>\n",
|
||||
" <th>Sneakers</th>\n",
|
||||
" <th>Crop Tops</th>\n",
|
||||
" <th>Polos</th>\n",
|
||||
" <th>Cross Body Bags</th>\n",
|
||||
" <th>Casual Jackets</th>\n",
|
||||
" <th>Swimwear Bottoms</th>\n",
|
||||
" <th>...</th>\n",
|
||||
" <th>Heels</th>\n",
|
||||
" <th>T-Shirts</th>\n",
|
||||
" <th>Activewear Tops & T-Shirts</th>\n",
|
||||
" <th>Watches & Timepieces</th>\n",
|
||||
" <th>Wallets & Card Holders</th>\n",
|
||||
" <th>Bodycon Dresses</th>\n",
|
||||
" <th>Beauty Tools & Accessories</th>\n",
|
||||
" <th>Skinny Jeans</th>\n",
|
||||
" <th>Beauty Eyes</th>\n",
|
||||
" <th>Beauty Face</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>2017-08-04</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>2017-08-07</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>2017-08-10</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>2017-08-13</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>2017-08-16</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>5 rows × 46 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" date Cami Dresses Shirts Tote Bags Sneakers Crop Tops Polos \\\n",
|
||||
"0 2017-08-04 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"1 2017-08-07 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"2 2017-08-10 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"3 2017-08-13 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"4 2017-08-16 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
" Cross Body Bags Casual Jackets Swimwear Bottoms ... Heels \\\n",
|
||||
"0 0.0 0.0 0.0 ... 1.0 \n",
|
||||
"1 0.0 0.0 0.0 ... 1.0 \n",
|
||||
"2 0.0 0.0 0.0 ... 1.0 \n",
|
||||
"3 0.0 0.0 0.0 ... 1.0 \n",
|
||||
"4 0.0 0.0 0.0 ... 1.0 \n",
|
||||
"\n",
|
||||
" T-Shirts Activewear Tops & T-Shirts Watches & Timepieces \\\n",
|
||||
"0 0.0 0.0 0.0 \n",
|
||||
"1 0.0 0.0 0.0 \n",
|
||||
"2 0.0 0.0 0.0 \n",
|
||||
"3 0.0 0.0 0.0 \n",
|
||||
"4 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
" Wallets & Card Holders Bodycon Dresses Beauty Tools & Accessories \\\n",
|
||||
"0 0.0 0.0 0.0 \n",
|
||||
"1 0.0 0.0 0.0 \n",
|
||||
"2 0.0 0.0 0.0 \n",
|
||||
"3 0.0 0.0 0.0 \n",
|
||||
"4 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
" Skinny Jeans Beauty Eyes Beauty Face \n",
|
||||
"0 0.0 0.0 0.0 \n",
|
||||
"1 0.0 0.0 0.0 \n",
|
||||
"2 0.0 0.0 0.0 \n",
|
||||
"3 0.0 0.0 0.0 \n",
|
||||
"4 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
"[5 rows x 46 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df = pd.read_csv('fashion.csv')\n",
|
||||
"df.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"date_ori = pd.to_datetime(df.iloc[:, 0]).tolist()\n",
|
||||
"df = df.iloc[:,1:]\n",
|
||||
"df_copy = df.copy()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"num_layers = 1\n",
|
||||
"learning_rate = 0.01\n",
|
||||
"size_layer = 128\n",
|
||||
"timestamp = 5\n",
|
||||
"epoch = 500\n",
|
||||
"dropout_rate = 0.7\n",
|
||||
"future_weeks = 30"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"class Model:\n",
|
||||
" def __init__(self, learning_rate, num_layers, \n",
|
||||
" size, size_layer, forget_bias = 0.8):\n",
|
||||
" \n",
|
||||
" def lstm_cell(size_layer):\n",
|
||||
" return tf.nn.rnn_cell.LSTMCell(size_layer, state_is_tuple = False)\n",
|
||||
" rnn_cells = tf.nn.rnn_cell.MultiRNNCell([lstm_cell(size_layer) for _ in range(num_layers)], \n",
|
||||
" state_is_tuple = False)\n",
|
||||
" self.X = tf.placeholder(tf.float32, (None, None, size))\n",
|
||||
" self.Y = tf.placeholder(tf.float32, (None, size))\n",
|
||||
" drop = tf.contrib.rnn.DropoutWrapper(rnn_cells, output_keep_prob = forget_bias)\n",
|
||||
" self.hidden_layer = tf.placeholder(tf.float32, \n",
|
||||
" (None, num_layers * 2 * size_layer))\n",
|
||||
" self.outputs, self.last_state = tf.nn.dynamic_rnn(drop, self.X, \n",
|
||||
" initial_state = self.hidden_layer, \n",
|
||||
" dtype = tf.float32)\n",
|
||||
" self.logits = tf.layers.dense(self.outputs[-1],size,\n",
|
||||
" kernel_initializer=tf.glorot_uniform_initializer())\n",
|
||||
" self.cost = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(labels=self.Y,logits=self.logits))\n",
|
||||
" self.optimizer = tf.train.AdamOptimizer(learning_rate).minimize(self.cost)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"WARNING:tensorflow:<tensorflow.python.ops.rnn_cell_impl.LSTMCell object at 0x7feb0aebbfd0>: Using a concatenated state is slower and will soon be deprecated. Use state_is_tuple=True.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"tf.reset_default_graph()\n",
|
||||
"modelnn = Model(learning_rate, num_layers, df.shape[1], size_layer, dropout_rate)\n",
|
||||
"sess = tf.InteractiveSession()\n",
|
||||
"sess.run(tf.global_variables_initializer())"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"epoch: 100 avg loss: 0.032256167317772734\n",
|
||||
"epoch: 200 avg loss: 0.01611048075348412\n",
|
||||
"epoch: 300 avg loss: 0.010450065255883663\n",
|
||||
"epoch: 400 avg loss: 0.010217295865004417\n",
|
||||
"epoch: 500 avg loss: 0.009890825056635518\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for i in range(epoch):\n",
|
||||
" init_value = np.zeros((1, num_layers * 2 * size_layer))\n",
|
||||
" total_loss = 0\n",
|
||||
" for k in range(0, (df.shape[0] // timestamp) * timestamp, timestamp):\n",
|
||||
" batch_x = np.expand_dims(df.iloc[k: k + timestamp].values, axis = 0)\n",
|
||||
" batch_y = df.iloc[k + 1: k + timestamp + 1].values\n",
|
||||
" last_state, _, loss = sess.run([modelnn.last_state, \n",
|
||||
" modelnn.optimizer, \n",
|
||||
" modelnn.cost], feed_dict={modelnn.X: batch_x, \n",
|
||||
" modelnn.Y: batch_y, \n",
|
||||
" modelnn.hidden_layer: init_value})\n",
|
||||
" init_value = last_state\n",
|
||||
" total_loss += loss\n",
|
||||
" total_loss /= (df.shape[0] // timestamp)\n",
|
||||
" if (i + 1) % 100 == 0:\n",
|
||||
" print('epoch:', i + 1, 'avg loss:', total_loss)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"output_predict = np.zeros((df.shape[0] + future_weeks, df.shape[1]))\n",
|
||||
"output_predict[0, :] = df.iloc[0] \n",
|
||||
"upper_b = (df.shape[0] // timestamp) * timestamp\n",
|
||||
"init_value = np.zeros((1, num_layers * 2 * size_layer))\n",
|
||||
"for k in range(0, (df.shape[0] // timestamp) * timestamp, timestamp):\n",
|
||||
" out_logits, last_state = sess.run([tf.nn.sigmoid(modelnn.logits), modelnn.last_state], \n",
|
||||
" feed_dict = {modelnn.X:np.expand_dims(df.iloc[k: k + timestamp], axis = 0),\n",
|
||||
" modelnn.hidden_layer: init_value})\n",
|
||||
" init_value = last_state\n",
|
||||
" output_predict[k + 1: k + timestamp + 1] = out_logits\n",
|
||||
" \n",
|
||||
"out_logits, last_state = sess.run([tf.nn.sigmoid(modelnn.logits), modelnn.last_state], \n",
|
||||
" feed_dict = {modelnn.X:np.expand_dims(df.iloc[upper_b:], axis = 0),\n",
|
||||
" modelnn.hidden_layer: init_value})\n",
|
||||
"init_value = last_state\n",
|
||||
"output_predict[upper_b + 1: df.shape[0] + 1] = out_logits\n",
|
||||
"df.loc[df.shape[0]] = out_logits[-1]\n",
|
||||
"date_ori.append(date_ori[-1]+timedelta(days=3))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"for i in range(future_weeks - 1):\n",
|
||||
" out_logits, last_state = sess.run([tf.nn.sigmoid(modelnn.logits), modelnn.last_state], feed_dict = \n",
|
||||
" {modelnn.X:np.expand_dims(df.iloc[-timestamp:], axis = 0),\n",
|
||||
" modelnn.hidden_layer: init_value})\n",
|
||||
" init_value = last_state\n",
|
||||
" output_predict[df.shape[0], :] = out_logits[-1, :]\n",
|
||||
" df.loc[df.shape[0]] = out_logits[-1, :]\n",
|
||||
" date_ori.append(date_ori[-1]+timedelta(days=3))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"date_ori=pd.Series(date_ori).dt.strftime(date_format='%Y-%m-%d').tolist()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"array([35, 21, 34, 10, 3, 33])"
|
||||
]
|
||||
},
|
||||
"execution_count": 11,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"index = (-np.round(df.values).sum(axis=0)).argsort()[4:10]\n",
|
||||
"index"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import seaborn as sns\n",
|
||||
"sns.set()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7feaa86c4550>"
|
||||
]
|
||||
},
|
||||
"metadata": {
|
||||
"needs_background": "light"
|
||||
},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"fig = plt.figure(figsize = (15,15))\n",
|
||||
"for no, i in enumerate(index):\n",
|
||||
" plt.subplot(6,1,no+1)\n",
|
||||
" label = list(df)[i]\n",
|
||||
" plt.plot(np.around(df.iloc[:,i]),label='predicted ' + label,alpha=0.7)\n",
|
||||
" plt.plot(np.around(df_copy.iloc[:,i]),label='real ' + label,alpha=0.7)\n",
|
||||
" plt.legend()\n",
|
||||
" x_range_future = np.arange(df.shape[0])\n",
|
||||
" plt.xticks(x_range_future[::20], date_ori[::20])\n",
|
||||
"plt.show()\n",
|
||||
"plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 33,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def df_shift(df,lag=0,rejected_columns = []):\n",
|
||||
" df = df.copy()\n",
|
||||
" if not lag:\n",
|
||||
" return df\n",
|
||||
" cols ={}\n",
|
||||
" for i in range(1,lag+1):\n",
|
||||
" for x in list(df.columns):\n",
|
||||
" if x not in rejected_columns:\n",
|
||||
" if not x in cols:\n",
|
||||
" cols[x] = ['{}_{}'.format(x, i)]\n",
|
||||
" else:\n",
|
||||
" cols[x].append('{}_{}'.format(x, i))\n",
|
||||
" for k,v in cols.items():\n",
|
||||
" columns = v\n",
|
||||
" dfn = pd.DataFrame(data=None, columns=columns, index=df.index) \n",
|
||||
" i = 1\n",
|
||||
" for c in columns:\n",
|
||||
" dfn[c] = df[k].shift(periods=i)\n",
|
||||
" i+=1\n",
|
||||
" df = pd.concat([df, dfn], axis=1, join_axes=[df.index])\n",
|
||||
" return df"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 34,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"(179, 135)"
|
||||
]
|
||||
},
|
||||
"execution_count": 34,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df_new = df_shift(df, 2)\n",
|
||||
"df_new.shape"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 35,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style>\n",
|
||||
" .dataframe thead tr:only-child th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: left;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>Cami Dresses</th>\n",
|
||||
" <th>Shirts</th>\n",
|
||||
" <th>Tote Bags</th>\n",
|
||||
" <th>Sneakers</th>\n",
|
||||
" <th>Crop Tops</th>\n",
|
||||
" <th>Polos</th>\n",
|
||||
" <th>Cross Body Bags</th>\n",
|
||||
" <th>Casual Jackets</th>\n",
|
||||
" <th>Swimwear Bottoms</th>\n",
|
||||
" <th>Scarves</th>\n",
|
||||
" <th>...</th>\n",
|
||||
" <th>Scarves_1</th>\n",
|
||||
" <th>Scarves_2</th>\n",
|
||||
" <th>Beauty Eyes_1</th>\n",
|
||||
" <th>Beauty Eyes_2</th>\n",
|
||||
" <th>Swimwear Tops_1</th>\n",
|
||||
" <th>Swimwear Tops_2</th>\n",
|
||||
" <th>Bracelets_1</th>\n",
|
||||
" <th>Bracelets_2</th>\n",
|
||||
" <th>Wallets & Card Holders_1</th>\n",
|
||||
" <th>Wallets & Card Holders_2</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" <td>0.0</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>5 rows × 135 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Cami Dresses Shirts Tote Bags Sneakers Crop Tops Polos \\\n",
|
||||
"0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"1 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"2 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"3 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"4 0.0 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
" Cross Body Bags Casual Jackets Swimwear Bottoms Scarves \\\n",
|
||||
"0 0.0 0.0 0.0 0.0 \n",
|
||||
"1 0.0 0.0 0.0 0.0 \n",
|
||||
"2 0.0 0.0 0.0 0.0 \n",
|
||||
"3 0.0 0.0 0.0 0.0 \n",
|
||||
"4 0.0 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
" ... Scarves_1 Scarves_2 Beauty Eyes_1 \\\n",
|
||||
"0 ... NaN NaN NaN \n",
|
||||
"1 ... 0.0 NaN 0.0 \n",
|
||||
"2 ... 0.0 0.0 0.0 \n",
|
||||
"3 ... 0.0 0.0 0.0 \n",
|
||||
"4 ... 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
" Beauty Eyes_2 Swimwear Tops_1 Swimwear Tops_2 Bracelets_1 Bracelets_2 \\\n",
|
||||
"0 NaN NaN NaN NaN NaN \n",
|
||||
"1 NaN 0.0 NaN 0.0 NaN \n",
|
||||
"2 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"3 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"4 0.0 0.0 0.0 0.0 0.0 \n",
|
||||
"\n",
|
||||
" Wallets & Card Holders_1 Wallets & Card Holders_2 \n",
|
||||
"0 NaN NaN \n",
|
||||
"1 0.0 NaN \n",
|
||||
"2 0.0 0.0 \n",
|
||||
"3 0.0 0.0 \n",
|
||||
"4 0.0 0.0 \n",
|
||||
"\n",
|
||||
"[5 rows x 135 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 35,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df_new.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 36,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"df_new = df_new.dropna()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 37,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7fea8ff87cc0>"
|
||||
]
|
||||
},
|
||||
"metadata": {
|
||||
"needs_background": "light"
|
||||
},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"colormap = plt.cm.RdBu\n",
|
||||
"plt.figure(figsize=(15,10))\n",
|
||||
"plt.title('2 days correlation', y=1.05, size=16)\n",
|
||||
"\n",
|
||||
"mask = np.zeros_like(df_new.corr())\n",
|
||||
"mask[np.triu_indices_from(mask)] = True\n",
|
||||
"\n",
|
||||
"sns.heatmap(df_new.corr(), mask=mask, linewidths=0.1,vmax=1.0, \n",
|
||||
" square=True, cmap=colormap, linecolor='white', annot=False)\n",
|
||||
"plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"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": "3.5.2"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
+150
@@ -0,0 +1,150 @@
|
||||
date,Cami Dresses,Shirts,Tote Bags,Sneakers,Crop Tops,Polos,Cross Body Bags,Casual Jackets,Swimwear,Scarves,Coats,Wedges,Sandals & Flip Flops,Necklaces,Activewear Shoes,Blazers,Flats,Sweatshirts,Coats,Scarves,Earrings,Blouses,Swing & Trapeze Dresses,Boots,Beauty Skin Care,Pumps,Backpacks,Casual Jackets,Swimwear Tops,Scarves & Hijabs,Ethnicwear,Bracelets,Smart Jackets,Ethnicwear Dresses,Swimwear,Heels,T-Shirts,Activewear Tops & T-Shirts,Watches & Timepieces,Wallets & Card Holders,Bodycon Dresses,Beauty Tools & Accessories,Skinny Jeans,Beauty Eyes,Beauty Face
|
||||
2017-08-04,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-07,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-10,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-13,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-16,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-19,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-22,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-25,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-28,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-08-31,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-03,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-06,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-09,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-12,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-18,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-21,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-27,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-09-30,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-03,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-06,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-09,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-12,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-18,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-21,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-27,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-10-30,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-02,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-08,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-11,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-14,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-17,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-20,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-23,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-26,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-11-29,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-02,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-08,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-11,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-14,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-17,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-20,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-23,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-26,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2017-12-29,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-01,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-04,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-07,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-10,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-13,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-16,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-19,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-22,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-25,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-28,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-01-31,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-03,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-06,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-09,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-12,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-15,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-18,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-21,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-24,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-02-27,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-02,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-05,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-08,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-11,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-14,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-17,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-20,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-23,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-26,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-03-29,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-01,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-04,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-07,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-10,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-13,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-16,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-19,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-22,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-25,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-04-28,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-01,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-04,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-07,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-10,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-13,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-16,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-19,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-22,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-25,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-28,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-05-31,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-03,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-06,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-09,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-12,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-15,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-18,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-21,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-24,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-27,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-06-30,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-03,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-06,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-09,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-12,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-15,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-18,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-21,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-24,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-27,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-07-30,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-02,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-05,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-08,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-11,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-14,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-17,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-20,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-23,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-26,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-08-29,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-01,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-04,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-07,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-10,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-13,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-16,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-19,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-22,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-25,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-09-28,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-01,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-04,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-07,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-10,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-13,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-16,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-19,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
2018-10-22,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
||||
|
+1954
File diff suppressed because it is too large.
Load diff
+1148
File diff suppressed because it is too large.
Load diff
BIN
Binary file not shown.
|
After Width: | Height: | Size: 59 KiB |
+389
@@ -0,0 +1,389 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import pandas as pd\n",
|
||||
"import numpy as np\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import matplotlib.dates as mdates\n",
|
||||
"import matplotlib.ticker as mticker\n",
|
||||
"import matplotlib\n",
|
||||
"from mpl_finance import candlestick_ohlc\n",
|
||||
"from datetime import datetime\n",
|
||||
"import seaborn as sns\n",
|
||||
"sns.set()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"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>Date</th>\n",
|
||||
" <th>Open</th>\n",
|
||||
" <th>High</th>\n",
|
||||
" <th>Low</th>\n",
|
||||
" <th>Close</th>\n",
|
||||
" <th>Adj Close</th>\n",
|
||||
" <th>Volume</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>2018-05-23</td>\n",
|
||||
" <td>277.760010</td>\n",
|
||||
" <td>279.910004</td>\n",
|
||||
" <td>274.000000</td>\n",
|
||||
" <td>279.070007</td>\n",
|
||||
" <td>279.070007</td>\n",
|
||||
" <td>5953100</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>2018-05-24</td>\n",
|
||||
" <td>278.399994</td>\n",
|
||||
" <td>281.109985</td>\n",
|
||||
" <td>274.890015</td>\n",
|
||||
" <td>277.850006</td>\n",
|
||||
" <td>277.850006</td>\n",
|
||||
" <td>4176700</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>2018-05-25</td>\n",
|
||||
" <td>277.630005</td>\n",
|
||||
" <td>279.640015</td>\n",
|
||||
" <td>275.609985</td>\n",
|
||||
" <td>278.850006</td>\n",
|
||||
" <td>278.850006</td>\n",
|
||||
" <td>3875100</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>2018-05-29</td>\n",
|
||||
" <td>278.510010</td>\n",
|
||||
" <td>286.500000</td>\n",
|
||||
" <td>276.149994</td>\n",
|
||||
" <td>283.760010</td>\n",
|
||||
" <td>283.760010</td>\n",
|
||||
" <td>5666600</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>2018-05-30</td>\n",
|
||||
" <td>283.290009</td>\n",
|
||||
" <td>295.010010</td>\n",
|
||||
" <td>281.600006</td>\n",
|
||||
" <td>291.720001</td>\n",
|
||||
" <td>291.720001</td>\n",
|
||||
" <td>7489700</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Date Open High Low Close Adj Close \\\n",
|
||||
"0 2018-05-23 277.760010 279.910004 274.000000 279.070007 279.070007 \n",
|
||||
"1 2018-05-24 278.399994 281.109985 274.890015 277.850006 277.850006 \n",
|
||||
"2 2018-05-25 277.630005 279.640015 275.609985 278.850006 278.850006 \n",
|
||||
"3 2018-05-29 278.510010 286.500000 276.149994 283.760010 283.760010 \n",
|
||||
"4 2018-05-30 283.290009 295.010010 281.600006 291.720001 291.720001 \n",
|
||||
"\n",
|
||||
" Volume \n",
|
||||
"0 5953100 \n",
|
||||
"1 4176700 \n",
|
||||
"2 3875100 \n",
|
||||
"3 5666600 \n",
|
||||
"4 7489700 "
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"df = pd.read_csv('TSLA.csv')\n",
|
||||
"df.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"date = [datetime.strptime(d, '%Y-%m-%d') for d in df['Date']]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"candlesticks = list(zip(mdates.date2num(date),df['Open'],\n",
|
||||
" df['High'],df['Low'],df['Close'],df['Volume']))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 1080x1080 with 2 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {
|
||||
"needs_background": "light"
|
||||
},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"fig = plt.figure(figsize = (15, 15))\n",
|
||||
"ax = fig.add_subplot(1,1,1)\n",
|
||||
"ax.set_ylabel('Quote ($)', size=20)\n",
|
||||
"\n",
|
||||
"dates = [x[0] for x in candlesticks]\n",
|
||||
"dates = np.asarray(dates)\n",
|
||||
"volume = [x[5] for x in candlesticks]\n",
|
||||
"volume = np.asarray(volume)\n",
|
||||
"\n",
|
||||
"candlestick_ohlc(ax, candlesticks, width=1,\n",
|
||||
" colorup='g', colordown='r')\n",
|
||||
"pad = 0.25\n",
|
||||
"yl = ax.get_ylim()\n",
|
||||
"ax.set_ylim(yl[0]-(yl[1]-yl[0])*pad,yl[1])\n",
|
||||
"ax2 = ax.twinx()\n",
|
||||
"\n",
|
||||
"ax2.set_position(matplotlib.transforms.Bbox([[0.125,0],[0.9,0.32]]))\n",
|
||||
"\n",
|
||||
"pos = df['Open'] - df['Close']<0\n",
|
||||
"neg = df['Open'] - df['Close']>0\n",
|
||||
"ax2.bar(dates[pos],volume[pos],color='green',width=1,align='center')\n",
|
||||
"ax2.bar(dates[neg],volume[neg],color='red',width=1,align='center')\n",
|
||||
"\n",
|
||||
"ax2.set_xlim(min(dates),max(dates))\n",
|
||||
"yticks = ax2.get_yticks()\n",
|
||||
"ax2.set_yticks(yticks[::3])\n",
|
||||
"\n",
|
||||
"ax2.yaxis.set_label_position(\"right\")\n",
|
||||
"ax2.set_ylabel('Volume', size=20)\n",
|
||||
"\n",
|
||||
"ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
|
||||
"ax.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
|
||||
"\n",
|
||||
"plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def removal(signal, repeat):\n",
|
||||
" copy_signal = np.copy(signal)\n",
|
||||
" for j in range(repeat):\n",
|
||||
" for i in range(3, len(signal)):\n",
|
||||
" copy_signal[i - 1] = (copy_signal[i - 2] + copy_signal[i]) / 2\n",
|
||||
" return copy_signal\n",
|
||||
"\n",
|
||||
"def get(original_signal, removed_signal):\n",
|
||||
" buffer = []\n",
|
||||
" for i in range(len(removed_signal)):\n",
|
||||
" buffer.append(original_signal[i] - removed_signal[i])\n",
|
||||
" return np.array(buffer)\n",
|
||||
"\n",
|
||||
"signal = np.copy(df.Open.values)\n",
|
||||
"removed_signal = removal(signal, 30)\n",
|
||||
"noise_open = get(signal, removed_signal)\n",
|
||||
"\n",
|
||||
"signal = np.copy(df.High.values)\n",
|
||||
"removed_signal = removal(signal, 30)\n",
|
||||
"noise_high = get(signal, removed_signal)\n",
|
||||
"\n",
|
||||
"signal = np.copy(df.Low.values)\n",
|
||||
"removed_signal = removal(signal, 30)\n",
|
||||
"noise_low = get(signal, removed_signal)\n",
|
||||
"\n",
|
||||
"signal = np.copy(df.Close.values)\n",
|
||||
"removed_signal = removal(signal, 30)\n",
|
||||
"noise_close = get(signal, removed_signal)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 1080x360 with 1 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {
|
||||
"needs_background": "light"
|
||||
},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"noise_candlesticks = list(zip(mdates.date2num(date),noise_open,\n",
|
||||
" noise_high,noise_low,noise_close))\n",
|
||||
"\n",
|
||||
"fig = plt.figure(figsize = (15, 5))\n",
|
||||
"ax = fig.add_subplot(1,1,1)\n",
|
||||
"ax.set_ylabel('Quote ($)', size=20)\n",
|
||||
"\n",
|
||||
"candlestick_ohlc(ax, noise_candlesticks, width=1,\n",
|
||||
" colorup='g', colordown='r')\n",
|
||||
"ax.plot(dates, [np.percentile(noise_close, 95)] * len(noise_candlesticks), color = (1.0, 0.792156862745098, 0.8, 0.7),\n",
|
||||
" linewidth=10.0, label = 'overbought line')\n",
|
||||
"\n",
|
||||
"ax.plot(dates, [np.percentile(noise_close, 10)] * len(noise_candlesticks), \n",
|
||||
" color = (0.6627450980392157, 1.0, 0.6392156862745098, 0.7),\n",
|
||||
" linewidth=10.0, label = 'oversold line')\n",
|
||||
"\n",
|
||||
"ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
|
||||
"ax.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
|
||||
"\n",
|
||||
"plt.legend()\n",
|
||||
"plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 1080x864 with 3 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {
|
||||
"needs_background": "light"
|
||||
},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"fig = plt.figure(figsize = (15, 12))\n",
|
||||
"ax1 = plt.subplot2grid((3, 1), (0, 0), rowspan=2)\n",
|
||||
"\n",
|
||||
"ax1.set_ylabel('Quote ($)', size=20)\n",
|
||||
"\n",
|
||||
"dates = [x[0] for x in candlesticks]\n",
|
||||
"dates = np.asarray(dates)\n",
|
||||
"volume = [x[5] for x in candlesticks]\n",
|
||||
"volume = np.asarray(volume)\n",
|
||||
"\n",
|
||||
"candlestick_ohlc(ax1, candlesticks, width=1,\n",
|
||||
" colorup='g', colordown='r')\n",
|
||||
"pad = 0.25\n",
|
||||
"yl = ax1.get_ylim()\n",
|
||||
"ax1.set_ylim(yl[0]-(yl[1]-yl[0])*pad,yl[1])\n",
|
||||
"ax2 = ax1.twinx()\n",
|
||||
"\n",
|
||||
"pos = df['Open'] - df['Close']<0\n",
|
||||
"neg = df['Open'] - df['Close']>0\n",
|
||||
"ax2.bar(dates[pos],volume[pos],color='green',width=1,align='center')\n",
|
||||
"ax2.bar(dates[neg],volume[neg],color='red',width=1,align='center')\n",
|
||||
"\n",
|
||||
"ax2.set_xlim(min(dates),max(dates))\n",
|
||||
"yticks = ax2.get_yticks()\n",
|
||||
"ax2.set_yticks(yticks[::3])\n",
|
||||
"\n",
|
||||
"ax2.yaxis.set_label_position(\"right\")\n",
|
||||
"ax2.set_ylabel('Volume', size=20)\n",
|
||||
"\n",
|
||||
"ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
|
||||
"ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
|
||||
"\n",
|
||||
"ax2 = plt.subplot2grid((3, 1), (2, 0))\n",
|
||||
"\n",
|
||||
"ax2.set_ylabel('Quote ($)', size=20)\n",
|
||||
"\n",
|
||||
"candlestick_ohlc(ax2, noise_candlesticks, width=1,\n",
|
||||
" colorup='g', colordown='r')\n",
|
||||
"ax2.plot(dates, [np.percentile(noise_close, 95)] * len(noise_candlesticks), color = (1.0, 0.792156862745098, 0.8, 1.0),\n",
|
||||
" linewidth=5.0, label = 'overbought line')\n",
|
||||
"\n",
|
||||
"ax2.plot(dates, [np.percentile(noise_close, 10)] * len(noise_candlesticks), \n",
|
||||
" color = (0.6627450980392157, 1.0, 0.6392156862745098, 1.0),\n",
|
||||
" linewidth=5.0, label = 'oversold line')\n",
|
||||
"\n",
|
||||
"ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
|
||||
"ax2.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
|
||||
"\n",
|
||||
"plt.legend()\n",
|
||||
"plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"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": "3.6.8"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
BIN
Binary file not shown.
|
After Width: | Height: | Size: 43 KiB |
+295
@@ -0,0 +1,295 @@
|
||||
,Polarity,Sensitivity,Tweet_vol,Open,High,Low,Volume_BTC,Volume_Dollar,Close_Price
|
||||
2018-07-11 20:00:00,0.10265670748614598,0.21614845947129513,4354.0,6342.97,6354.19,6291.0,986.73,6231532.37,6350.0
|
||||
2018-07-11 21:00:00,0.09800395297609978,0.21861239516350178,4432.0,6352.99,6370.0,6345.76,126.46,804221.55,6356.48
|
||||
2018-07-11 22:00:00,0.0966881579841847,0.23134226427071872,3980.0,6350.85,6378.47,6345.0,259.1,1646353.87,6361.93
|
||||
2018-07-11 23:00:00,0.10399680386738332,0.21773906718462835,3830.0,6362.36,6381.25,6356.74,81.54,519278.69,6368.78
|
||||
2018-07-12 00:00:00,0.09438312650721571,0.19525553005949395,3998.0,6369.49,6381.25,6361.83,124.55,793560.22,6380.0
|
||||
2018-07-12 01:00:00,0.10083589375817453,0.22307632548845868,3713.0,6379.13,6380.0,6347.72,141.5,900280.85,6365.43
|
||||
2018-07-12 02:00:00,0.1119643429977597,0.19504306787217293,3843.0,6365.24,6371.8,6324.48,141.3,896772.74,6327.94
|
||||
2018-07-12 03:00:00,0.1058881862567765,0.20993930342403333,3831.0,6328.4,6348.45,6302.18,162.37,1026431.72,6326.98
|
||||
2018-07-12 04:00:00,0.10811700734669419,0.20800324193424663,3743.0,6327.49,6343.22,6327.49,58.62,371327.65,6339.5
|
||||
2018-07-12 05:00:00,0.10666706633974722,0.21723050559221563,3480.0,6342.22,6344.57,6328.0,74.75,473450.28,6333.05
|
||||
2018-07-12 06:00:00,0.09819201661175406,0.20621768833627063,3954.0,6333.05,6335.55,6305.0,130.84,827194.5,6329.57
|
||||
2018-07-12 07:00:00,0.08077478187342219,0.19081446008983832,4561.0,6329.9,6334.74,6177.45,1211.64,7536289.75,6217.63
|
||||
2018-07-12 08:00:00,0.08877735580061671,0.18471850163515388,5621.0,6217.03,6223.14,6131.35,758.15,4677685.75,6180.5
|
||||
2018-07-12 09:00:00,0.0975813393389163,0.20191214692260084,5046.0,6180.46,6200.82,6085.59,1090.25,6719480.12,6200.82
|
||||
2018-07-12 10:00:00,0.09191287676658966,0.19896478587190353,5511.0,6200.23,6205.0,6175.01,289.87,1794667.77,6185.82
|
||||
2018-07-12 11:00:00,0.08382532077920497,0.2173181646652594,5277.0,6185.4,6187.99,6157.03,212.3,1310453.07,6175.18
|
||||
2018-07-12 12:00:00,0.07710081294119067,0.195526425954516,5493.0,6174.5,6182.13,6144.35,261.02,1608275.15,6162.41
|
||||
2018-07-12 13:00:00,0.07714852137139569,0.20891735896754152,5455.0,6167.17,6191.99,6155.0,246.37,1522744.15,6180.31
|
||||
2018-07-12 14:00:00,0.09711192039767944,0.23622240576351197,5811.0,6180.3,6183.99,6170.99,258.89,1599120.65,6182.99
|
||||
2018-07-12 15:00:00,0.09680845597780344,0.21027440482122414,5676.0,6182.98,6199.57,6173.5,275.0,1700530.69,6180.97
|
||||
2018-07-12 16:00:00,0.08795242249876721,0.2015228691350621,5983.0,6178.59,6182.55,6159.01,166.21,1025666.81,6169.51
|
||||
2018-07-12 17:00:00,0.09484858580146976,0.21709007457257168,5699.0,6168.44,6192.89,6166.78,342.08,2115989.77,6181.23
|
||||
2018-07-12 18:00:00,0.10102371245440864,0.21088171207458128,5273.0,6184.08,6189.0,6167.64,168.14,1039237.28,6179.12
|
||||
2018-07-12 19:00:00,0.08611796809952094,0.21457562723378348,4950.0,6179.12,6185.0,6165.22,103.57,639670.03,6173.99
|
||||
2018-07-12 20:00:00,0.07871816379987927,0.20741734995274108,4874.0,6171.06,6180.17,6150.43,148.79,916929.71,6174.76
|
||||
2018-07-12 21:00:00,0.08719564027112056,0.21046084704329646,4289.0,6179.38,6187.42,6166.91,120.99,747520.42,6173.05
|
||||
2018-07-12 22:00:00,0.09749038298261753,0.20786096842163354,4290.0,6170.03,6176.66,6153.52,81.22,500729.79,6171.68
|
||||
2018-07-12 23:00:00,0.09420668493105258,0.20923114266523765,4404.0,6171.94,6173.61,6110.08,309.59,1901284.59,6149.11
|
||||
2018-07-13 00:00:00,0.10956030065574283,0.20687239073099853,4339.0,6149.11,6267.31,6072.0,1039.01,6412278.5,6243.88
|
||||
2018-07-13 01:00:00,0.1059331692447039,0.2131436722864254,4112.0,6243.53,6284.05,6214.94,466.27,2910899.5,6236.88
|
||||
2018-07-13 02:00:00,0.10359979844473512,0.20187772547668398,4080.0,6236.88,6249.82,6231.94,114.45,714175.12,6232.71
|
||||
2018-07-13 03:00:00,0.12033375545093336,0.21227923614457422,4205.0,6232.88,6254.67,6228.76,187.3,1168928.22,6242.9
|
||||
2018-07-13 04:00:00,0.09555287236451522,0.21991078312830262,4395.0,6242.89,6252.93,6236.55,139.55,871611.63,6249.87
|
||||
2018-07-13 05:00:00,0.10343047308156315,0.2078529458176204,4179.0,6248.2,6264.75,6236.01,219.95,1375165.61,6245.68
|
||||
2018-07-13 06:00:00,0.10165723968487417,0.20809832469539916,3760.0,6245.68,6256.75,6229.16,242.49,1513210.93,6244.39
|
||||
2018-07-13 07:00:00,0.1022300476629104,0.21493596730628992,3875.0,6243.18,6247.98,6212.21,184.38,1148580.47,6230.01
|
||||
2018-07-13 08:00:00,0.10611204722476755,0.21574199226407334,5072.0,6230.4,6253.9,6229.38,236.18,1474017.93,6249.19
|
||||
2018-07-13 09:00:00,0.09147283872454691,0.18770163229568818,4500.0,6247.92,6250.0,6229.1,128.9,804393.43,6233.96
|
||||
2018-07-13 10:00:00,0.09960890509981776,0.1912204222641126,4818.0,6232.96,6245.47,6230.0,154.3,962281.91,6234.85
|
||||
2018-07-13 11:00:00,0.09279532026486634,0.19179629084253394,4671.0,6234.85,6245.87,6226.18,94.38,588479.19,6234.22
|
||||
2018-07-13 12:00:00,0.08698310262415916,0.19715054617599925,5181.0,6232.0,6248.99,6228.08,62.82,391997.33,6241.75
|
||||
2018-07-13 13:00:00,0.09692751891658306,0.2049111160954308,5298.0,6240.4,6286.36,6238.0,423.94,2655456.13,6269.06
|
||||
2018-07-13 14:00:00,0.09758484220495918,0.2026232776304885,5200.0,6272.4,6275.68,6228.67,394.0,2460513.08,6244.01
|
||||
2018-07-13 15:00:00,0.10318213207626459,0.21142511129952427,5116.0,6237.15,6264.35,6224.15,255.99,1599106.41,6245.99
|
||||
2018-07-13 16:00:00,0.09606416499703098,0.21215766204215622,5240.0,6245.99,6259.88,6237.0,195.93,1224745.98,6259.88
|
||||
2018-07-13 17:00:00,0.09716123209848196,0.21828153018266383,5558.0,6259.88,6268.05,6240.81,211.09,1319500.19,6254.99
|
||||
2018-07-13 18:00:00,0.08435959209609722,0.21622885818149568,5611.0,6254.99,6267.99,6247.11,97.84,612655.54,6264.94
|
||||
2018-07-13 19:00:00,0.08853718581752733,0.2203785027686753,5462.0,6264.91,6337.25,6226.99,571.75,3589882.19,6237.5
|
||||
2018-07-13 20:00:00,0.0923034543430851,0.21997207545969977,5030.0,6237.5,6245.78,6166.44,521.21,3228298.36,6174.99
|
||||
2018-07-13 21:00:00,0.10018122677823708,0.2161121468814689,4852.0,6177.35,6227.63,6121.01,612.28,3779623.53,6186.39
|
||||
2018-07-13 22:00:00,0.10095012149820652,0.23085818907913794,4449.0,6185.5,6229.0,6180.01,125.81,780174.87,6215.85
|
||||
2018-07-13 23:00:00,0.1134672424714027,0.22556652665784138,4208.0,6211.37,6225.39,6190.26,123.72,767545.63,6219.58
|
||||
2018-07-14 00:00:00,0.05169492007778924,0.21856501239382975,4371.0,6219.99,6248.94,6196.0,136.74,850825.64,6215.59
|
||||
2018-07-14 01:00:00,0.09950923554101708,0.2206044590073266,3907.0,6208.78,6273.97,6208.78,219.37,1370473.06,6237.99
|
||||
2018-07-14 02:00:00,0.11187410939405736,0.2202844564046976,3231.0,6237.98,6277.72,6214.11,171.24,1069456.99,6234.38
|
||||
2018-07-14 03:00:00,0.10049279048164668,0.20310504263708248,3558.0,6231.23,6240.0,6219.1,56.15,349888.49,6225.99
|
||||
2018-07-14 04:00:00,0.11271226782328998,0.22446433324987566,3130.0,6226.86,6227.67,6193.5,94.03,583969.64,6206.99
|
||||
2018-07-14 05:00:00,0.09652272423735678,0.2239328919413113,3415.0,6203.33,6224.8,6200.03,66.12,411019.51,6216.99
|
||||
2018-07-14 06:00:00,0.09735811595016991,0.20637940889185244,3114.0,6218.51,6233.38,6210.57,78.19,486424.82,6220.53
|
||||
2018-07-14 07:00:00,0.103780244266209,0.19285173493268673,3499.0,6220.53,6230.1,6201.97,75.07,466915.22,6212.81
|
||||
2018-07-14 08:00:00,0.0945108516295059,0.20254888141149976,4442.0,6212.92,6225.0,6204.91,95.79,595704.78,6220.06
|
||||
2018-07-14 09:00:00,0.09481203456127495,0.20144380409280152,3641.0,6221.8,6225.0,6203.79,98.38,611258.48,6216.2
|
||||
2018-07-14 10:00:00,0.0785761518393219,0.21936172359370504,4093.0,6216.2,6219.54,6180.0,130.22,807423.98,6195.32
|
||||
2018-07-14 11:00:00,0.08584598156862443,0.19659144803432665,4381.0,6203.99,6223.48,6195.73,39.45,244914.76,6220.48
|
||||
2018-07-14 12:00:00,0.08813036199981576,0.19326561881496315,4271.0,6220.48,6239.45,6215.79,42.5,264821.93,6233.0
|
||||
2018-07-14 13:00:00,0.08948837953046178,0.17648722495220495,4890.0,6231.13,6242.21,6224.63,82.37,513436.44,6236.12
|
||||
2018-07-14 14:00:00,0.09100328219923795,0.19926593911037158,4768.0,6235.76,6240.92,6222.8,32.42,201957.74,6237.0
|
||||
2018-07-14 15:00:00,0.08687249609815068,0.1916351459166314,4637.0,6231.95,6244.43,6226.23,48.81,304512.55,6238.2
|
||||
2018-07-14 16:00:00,0.08541838397706562,0.21048857295933318,4399.0,6238.2,6240.0,6216.18,47.57,296455.69,6239.99
|
||||
2018-07-14 17:00:00,0.08328018219976774,0.229995432773997,4293.0,6239.55,6270.69,6239.55,133.93,838019.93,6262.0
|
||||
2018-07-14 18:00:00,0.07986841649398302,0.23248332235550545,3861.0,6262.99,6270.59,6248.74,259.41,1624071.38,6255.49
|
||||
2018-07-14 19:00:00,0.08645546626420936,0.21603397917127862,3862.0,6259.54,6298.0,6229.48,68.14,426747.86,6237.68
|
||||
2018-07-14 20:00:00,0.08030492195122882,0.2035296529301922,3989.0,6239.99,6269.53,6200.01,146.93,916476.48,6267.99
|
||||
2018-07-14 21:00:00,0.09313462281643667,0.21950797348744847,4056.0,6269.53,6317.84,6205.47,425.57,2664428.61,6270.31
|
||||
2018-07-14 22:00:00,0.10330089707235544,0.22135970695783896,3466.0,6270.3,6286.37,6257.13,54.81,343757.75,6265.61
|
||||
2018-07-14 23:00:00,0.1016246044466634,0.21187473667744477,3453.0,6265.07,6277.9,6238.48,63.91,399501.47,6246.57
|
||||
2018-07-15 00:00:00,0.08645926265533192,0.19637008784261328,3344.0,6250.99,6261.06,6238.56,54.37,339748.71,6243.98
|
||||
2018-07-15 01:00:00,0.07440800340954949,0.17433025080936304,3890.0,6245.99,6255.86,6227.76,63.46,396208.02,6243.42
|
||||
2018-07-15 02:00:00,0.09153586908711045,0.19087176337574915,3136.0,6243.42,6247.97,6227.94,36.89,230131.13,6243.93
|
||||
2018-07-15 03:00:00,0.09914894113188619,0.22633646719980086,3121.0,6238.55,6250.64,6232.06,38.61,240983.43,6249.61
|
||||
2018-07-15 04:00:00,0.09269128033174348,0.20158160932478605,3397.0,6249.61,6252.85,6235.12,175.88,1097749.25,6248.6
|
||||
2018-07-15 05:00:00,0.0969583905604344,0.19882088768184264,3391.0,6248.6,6277.28,6248.6,77.26,484027.1,6266.27
|
||||
2018-07-15 06:00:00,0.12450486511852168,0.22112820700711266,3328.0,6266.16,6280.41,6258.72,46.05,288836.56,6275.95
|
||||
2018-07-15 07:00:00,0.0988669935841507,0.19227725225395115,3751.0,6278.82,6283.57,6266.26,86.17,540629.42,6274.99
|
||||
2018-07-15 08:00:00,0.09638586963250599,0.23420282158809222,4613.0,6270.26,6279.5,6256.5,22.0,137960.07,6277.0
|
||||
2018-07-15 09:00:00,0.11079858545480217,0.22384213168365805,3865.0,6277.0,6349.47,6267.31,299.95,1891954.57,6311.47
|
||||
2018-07-15 10:00:00,0.12746877528258913,0.22103256652160957,4084.0,6305.67,6330.99,6296.72,199.63,1260251.48,6302.99
|
||||
2018-07-15 11:00:00,0.11613103897994907,0.20725430234489406,4156.0,6303.85,6384.47,6303.85,508.32,3225731.02,6336.0
|
||||
2018-07-15 12:00:00,0.12037205312234465,0.2153608557262819,4178.0,6332.99,6359.81,6325.96,357.15,2268610.84,6353.01
|
||||
2018-07-15 13:00:00,0.12241130247880065,0.23832342374193266,4683.0,6353.01,6360.89,6324.21,91.99,583242.7,6329.26
|
||||
2018-07-15 14:00:00,0.11634313134396271,0.22410089987047968,4303.0,6329.26,6359.06,6322.03,111.84,709071.63,6354.96
|
||||
2018-07-15 15:00:00,0.11613708011053471,0.21907138095607467,4397.0,6356.86,6362.94,6327.14,140.14,889382.77,6347.99
|
||||
2018-07-15 16:00:00,0.10994101696467036,0.2279774612159839,3801.0,6347.98,6376.98,6342.62,249.59,1586484.37,6372.36
|
||||
2018-07-15 17:00:00,0.10674266070473037,0.22293243238284427,4492.0,6374.58,6397.21,6362.7,106.36,678296.77,6374.74
|
||||
2018-07-15 18:00:00,0.10997613960865044,0.23374366728242194,3964.0,6378.88,6393.51,6354.12,294.5,1879818.44,6383.0
|
||||
2018-07-15 19:00:00,0.09045161714398472,0.226387896197765,3445.0,6383.0,6383.0,6349.47,65.63,417658.22,6349.72
|
||||
2018-07-15 20:00:00,0.08711509708244272,0.20652699734090638,3505.0,6354.97,6372.94,6349.47,72.23,459477.97,6362.99
|
||||
2018-07-15 21:00:00,0.09560266939710718,0.2363889192541693,3590.0,6362.99,6372.69,6355.29,83.2,529393.61,6372.69
|
||||
2018-07-15 22:00:00,0.08745570188051328,0.2233889519208471,3198.0,6372.87,6397.21,6369.12,157.75,1006828.31,6379.95
|
||||
2018-07-15 23:00:00,0.10067384092591493,0.22686999793487145,3187.0,6379.95,6388.82,6350.11,177.91,1133835.24,6361.63
|
||||
2018-07-16 00:00:00,0.10101162074136538,0.22640124740108136,2998.0,6361.68,6373.07,6336.01,93.76,595245.86,6349.3
|
||||
2018-07-16 01:00:00,0.10680389406136824,0.21421138664372752,3695.0,6353.25,6377.82,6340.53,117.74,748249.33,6350.52
|
||||
2018-07-16 02:00:00,0.10851873206700743,0.19241046825043137,3771.0,6349.46,6354.99,6339.58,112.25,712492.32,6345.61
|
||||
2018-07-16 03:00:00,0.13063382784526958,0.2287674128269762,3299.0,6345.49,6363.53,6333.63,223.51,1417294.48,6351.87
|
||||
2018-07-16 04:00:00,0.11510180723062069,0.22669744921558144,3171.0,6351.68,6370.0,6346.49,198.15,1260752.84,6352.93
|
||||
2018-07-16 05:00:00,0.12421010338306845,0.22375148377130483,3683.0,6352.99,6357.17,6338.86,97.74,620504.75,6344.03
|
||||
2018-07-16 06:00:00,0.10025139746450867,0.19986633661542283,3831.0,6344.03,6367.99,6342.76,158.7,1009238.67,6362.99
|
||||
2018-07-16 07:00:00,0.12006243489878883,0.22294543258347688,3948.0,6362.99,6380.01,6355.07,119.64,761752.33,6363.13
|
||||
2018-07-16 08:00:00,0.10381535148494465,0.20600678278535753,4602.0,6362.98,6365.67,6348.41,157.83,1002695.44,6359.74
|
||||
2018-07-16 09:00:00,0.08866044469405737,0.18684176442941855,4378.0,6359.74,6396.08,6340.0,372.24,2369598.53,6368.02
|
||||
2018-07-16 10:00:00,0.09820637577528228,0.20079615873035667,5585.0,6367.99,6530.0,6360.0,1147.69,7418674.01,6522.15
|
||||
2018-07-16 11:00:00,0.09356232328934051,0.19267955935679773,5841.0,6516.03,6553.0,6496.46,610.8,3983335.56,6542.77
|
||||
2018-07-16 12:00:00,0.09658528762607374,0.20456811655826818,6359.0,6542.99,6667.0,6527.19,912.03,6022860.97,6625.99
|
||||
2018-07-16 13:00:00,0.0920606179084515,0.2004977756567735,7133.0,6627.99,6633.18,6587.3,436.89,2886535.04,6599.25
|
||||
2018-07-16 14:00:00,0.08435536040922681,0.1919805585897622,7280.0,6598.72,6619.97,6576.8,398.27,2627631.55,6588.18
|
||||
2018-07-16 15:00:00,0.08570224612525415,0.2124886445303301,6690.0,6581.87,6631.4,6580.0,369.45,2443755.81,6621.57
|
||||
2018-07-16 16:00:00,0.08231677287304599,0.21623361865548088,6271.0,6627.63,6647.85,6608.26,320.53,2124754.87,6623.44
|
||||
2018-07-16 17:00:00,0.10487584012803053,0.2243072925380704,5898.0,6628.12,6652.26,6610.63,697.8,4633743.83,6617.04
|
||||
2018-07-16 18:00:00,0.09189594855473134,0.22327380578556308,5539.0,6619.98,6724.78,6613.72,933.84,6232959.77,6665.62
|
||||
2018-07-16 19:00:00,0.10079133823349068,0.22437945772881338,4967.0,6665.8,6700.0,6659.51,436.1,2913361.09,6660.56
|
||||
2018-07-16 20:00:00,0.09804340086611071,0.20411718528510037,4937.0,6661.02,6689.94,6635.0,297.5,1981897.93,6675.01
|
||||
2018-07-16 21:00:00,0.09274331640552064,0.2182669786906523,4692.0,6674.96,6674.96,6651.01,245.83,1638392.23,6661.11
|
||||
2018-07-16 22:00:00,0.09794827588098044,0.23045003961517432,4290.0,6656.59,6668.32,6641.35,151.51,1008524.63,6661.66
|
||||
2018-07-16 23:00:00,0.08960596210615838,0.2111357903786806,3996.0,6659.17,6697.23,6651.91,188.37,1257005.96,6671.97
|
||||
2018-07-17 00:00:00,0.08441498966342238,0.20378772478045137,4159.0,6668.87,6755.0,6662.04,699.65,4700740.52,6721.04
|
||||
2018-07-17 01:00:00,0.07757985257908741,0.18945709572627056,4146.0,6721.21,6741.59,6700.36,375.73,2526123.13,6740.87
|
||||
2018-07-17 02:00:00,0.07779411857484492,0.1815114455443646,4063.0,6741.59,6749.11,6696.0,247.99,1666318.6,6721.0
|
||||
2018-07-17 03:00:00,0.08803316649020868,0.19529453582262724,3542.0,6720.99,6734.87,6712.29,194.25,1307163.64,6734.4
|
||||
2018-07-17 04:00:00,0.08060551768147316,0.18854092053740948,3596.0,6734.4,6749.7,6724.5,247.25,1665494.07,6738.86
|
||||
2018-07-17 05:00:00,0.07906925575205595,0.19812163257553825,3943.0,6738.86,6755.14,6702.91,328.33,2207847.78,6707.47
|
||||
2018-07-17 06:00:00,0.08166557090545296,0.1988207290633254,3782.0,6706.12,6718.3,6679.58,306.45,2053621.55,6688.11
|
||||
2018-07-17 07:00:00,0.08926668742545174,0.19717730891360574,3740.0,6689.3,6696.63,6657.95,387.29,2587491.88,6670.93
|
||||
2018-07-17 08:00:00,0.08669627364776862,0.20270935828254527,4895.0,6671.21,6702.19,6668.64,194.46,1300997.96,6698.76
|
||||
2018-07-17 09:00:00,0.08404939264271777,0.19747495622359704,4598.0,6699.66,6734.78,6694.19,341.46,2294438.1,6715.07
|
||||
2018-07-17 10:00:00,0.07728310090551331,0.21391281443005386,4858.0,6719.97,6719.97,6693.17,173.23,1161670.06,6702.3
|
||||
2018-07-17 11:00:00,0.0880541898029586,0.21086802375649066,5356.0,6697.33,6720.0,6696.01,155.38,1042120.84,6718.26
|
||||
2018-07-17 12:00:00,0.09866325851638928,0.228294372473011,5903.0,6719.21,6724.34,6675.63,201.22,1348614.56,6683.14
|
||||
2018-07-17 13:00:00,0.0994711918334477,0.21600808100382365,5666.0,6682.19,6708.01,6674.6,341.78,2287346.9,6699.3
|
||||
2018-07-17 14:00:00,0.1038629340479667,0.2376332340151667,5770.0,6699.76,6710.0,6682.88,207.8,1391864.94,6697.53
|
||||
2018-07-17 15:00:00,0.10365502473897802,0.2271468083106771,5911.0,6696.0,6764.47,6690.25,477.88,3212613.38,6718.0
|
||||
2018-07-17 16:00:00,0.09877498471380865,0.21739572998063109,6300.0,6718.0,6789.0,6711.68,407.12,2747512.48,6779.23
|
||||
2018-07-17 17:00:00,0.09924709835707932,0.21905868387840996,5622.0,6778.18,6778.18,6733.51,294.3,1986746.72,6751.72
|
||||
2018-07-17 18:00:00,0.09450994365782422,0.22158155212170066,7995.0,6748.56,7264.47,6745.83,2640.49,18620560.8,7183.99
|
||||
2018-07-17 19:00:00,0.08938425271174931,0.23788686788771235,10452.0,7186.99,7468.31,7171.33,2600.32,19126407.89,7346.91
|
||||
2018-07-17 20:00:00,0.08826820193223688,0.22801567852606316,7354.0,7348.42,7375.65,7295.13,874.26,6408774.66,7295.13
|
||||
2018-07-17 21:00:00,0.08757832718459499,0.2214965284757346,6001.0,7295.13,7332.21,7295.13,582.84,4263944.05,7317.11
|
||||
2018-07-17 22:00:00,0.10081845661400027,0.22948639301796517,5717.0,7317.11,7388.38,7312.89,378.16,2781076.34,7360.6
|
||||
2018-07-17 23:00:00,0.08739853380203005,0.20683654015580452,5405.0,7360.6,7379.0,7269.84,474.87,3475255.97,7310.56
|
||||
2018-07-18 00:00:00,0.10458653605004535,0.22565920099699327,4989.0,7315.57,7338.55,7296.6,270.47,1979623.49,7310.71
|
||||
2018-07-18 01:00:00,0.10426692766856487,0.2150542494067622,4636.0,7310.71,7369.52,7310.71,245.16,1799395.28,7341.22
|
||||
2018-07-18 02:00:00,0.09539051572444865,0.19786297896745184,4829.0,7342.1,7352.41,7315.01,125.74,922275.1,7336.99
|
||||
2018-07-18 03:00:00,0.10018737266442283,0.22056466916427314,4799.0,7335.94,7449.68,7328.49,511.71,3775483.69,7401.0
|
||||
2018-07-18 04:00:00,0.10003658691113283,0.21010508601828456,5090.0,7401.0,7546.68,7401.0,1576.15,11798048.6,7458.54
|
||||
2018-07-18 05:00:00,0.09632101300041417,0.19897012116782847,4972.0,7459.92,7471.41,7400.0,351.11,2608164.78,7433.0
|
||||
2018-07-18 06:00:00,0.10810567198577267,0.20782090857300461,4653.0,7433.0,7481.07,7416.27,281.91,2097039.92,7459.23
|
||||
2018-07-18 07:00:00,0.09837631003006138,0.19710796290408308,5090.0,7459.23,7477.57,7449.25,304.67,2272795.48,7464.86
|
||||
2018-07-18 08:00:00,0.10286441641920244,0.20909074678772308,6332.0,7464.36,7466.0,7403.8,665.62,4944348.99,7433.46
|
||||
2018-07-18 09:00:00,0.10236345987876981,0.1995544952702377,5765.0,7436.58,7437.98,7317.83,773.15,5691054.24,7362.08
|
||||
2018-07-18 10:00:00,0.09893850443227278,0.2046419638769042,5694.0,7362.98,7395.63,7361.96,338.75,2499982.03,7395.63
|
||||
2018-07-18 11:00:00,0.08721378948642718,0.20327885161459489,5534.0,7392.63,7424.42,7362.19,269.83,1996662.83,7397.61
|
||||
2018-07-18 12:00:00,0.08452868963858916,0.19673796033717042,6844.0,7397.61,7434.45,7380.97,386.63,2866370.21,7410.65
|
||||
2018-07-18 13:00:00,0.08691865918191342,0.20876507790721302,7171.0,7415.62,7468.31,7407.48,462.37,3441667.99,7430.0
|
||||
2018-07-18 14:00:00,0.09715237581185075,0.2151440570451033,7209.0,7433.99,7461.62,7385.98,383.98,2851271.78,7449.43
|
||||
2018-07-18 15:00:00,0.09719707503910022,0.2140918216301937,7222.0,7445.35,7525.17,7425.76,630.39,4706264.24,7446.3
|
||||
2018-07-18 16:00:00,0.09856703142075066,0.22027114066808534,6733.0,7442.35,7442.35,7378.0,817.06,6055122.46,7422.88
|
||||
2018-07-18 17:00:00,0.10700218237766784,0.23218631464650394,6493.0,7417.81,7451.99,7410.89,221.67,1647469.3,7431.18
|
||||
2018-07-18 18:00:00,0.11935964400029529,0.24128665869962426,5765.0,7433.67,7513.38,7428.63,1103.91,8247570.88,7500.86
|
||||
2018-07-18 19:00:00,0.11004891527390581,0.23781049893042644,6211.0,7498.5,7599.98,7376.0,1490.02,11172723.69,7428.05
|
||||
2018-07-18 20:00:00,0.10739199869227331,0.24353434180133784,5597.0,7422.02,7442.4,7339.12,649.21,4794432.56,7400.0
|
||||
2018-07-18 21:00:00,0.10121197130126297,0.24342249598605217,5381.0,7393.77,7393.77,7239.15,949.03,6922391.06,7336.18
|
||||
2018-07-18 22:00:00,0.10244741599158645,0.23728994500190434,4597.0,7337.99,7357.26,7299.92,177.31,1300009.44,7332.6
|
||||
2018-07-18 23:00:00,0.09582295967638106,0.22565433501245782,4333.0,7325.66,7388.99,7278.88,324.78,2380734.14,7359.68
|
||||
2018-07-19 00:00:00,0.07359266204853114,0.21975802525110122,4225.0,7362.54,7394.09,7340.71,307.69,2268343.66,7374.88
|
||||
2018-07-19 01:00:00,0.09088181849508321,0.20757276547809825,4603.0,7384.92,7384.92,7305.0,201.54,1479387.55,7340.77
|
||||
2018-07-19 02:00:00,0.10544487159119742,0.21616249279499702,4281.0,7342.6,7342.6,7278.84,286.2,2091067.8,7298.95
|
||||
2018-07-19 03:00:00,0.12028376135888774,0.22015166158516353,4346.0,7301.74,7342.45,7280.92,322.28,2354462.88,7323.19
|
||||
2018-07-19 04:00:00,0.10575343210474486,0.20353374171222816,4618.0,7320.75,7357.26,7316.87,131.57,965522.38,7316.87
|
||||
2018-07-19 05:00:00,0.11944988528427804,0.22145330825652093,4482.0,7319.58,7347.16,7305.67,203.41,1490708.7,7315.98
|
||||
2018-07-19 06:00:00,0.11394853026434082,0.21496222114861888,4422.0,7312.37,7336.99,7300.33,185.65,1359245.16,7329.47
|
||||
2018-07-19 07:00:00,0.11660140494214971,0.22604099746407488,4810.0,7329.47,7362.09,7326.23,262.75,1929530.25,7332.58
|
||||
2018-07-19 08:00:00,0.10234580298997183,0.2079983409586107,6110.0,7331.58,7345.39,7293.59,202.74,1484532.8,7310.83
|
||||
2018-07-19 09:00:00,0.10890424448438812,0.2110123359473201,5441.0,7310.83,7338.41,7298.38,358.44,2622125.54,7324.03
|
||||
2018-07-19 10:00:00,0.10259191610439748,0.19155543801644864,5681.0,7323.44,7420.0,7321.97,532.98,3927556.9,7408.79
|
||||
2018-07-19 11:00:00,0.09756634607806124,0.2002868882588213,5861.0,7407.76,7420.71,7370.46,218.13,1611513.72,7374.87
|
||||
2018-07-19 12:00:00,0.10470509818970977,0.22154672720611843,6197.0,7374.83,7434.34,7359.94,624.64,4622003.24,7416.99
|
||||
2018-07-19 13:00:00,0.10366334418573576,0.21574768659840218,6151.0,7417.6,7452.0,7406.78,334.26,2482521.47,7423.27
|
||||
2018-07-19 14:00:00,0.10688106583353042,0.22254927883140213,6584.0,7423.27,7513.0,7414.05,703.35,5248927.21,7486.65
|
||||
2018-07-19 15:00:00,0.11044259314994757,0.2338962169074704,6786.0,7484.21,7484.21,7431.1,485.06,3616235.46,7448.6
|
||||
2018-07-19 16:00:00,0.11669284158808829,0.2348234412544244,6886.0,7454.44,7483.29,7363.63,735.65,5462758.12,7391.83
|
||||
2018-07-19 17:00:00,0.09872221884419828,0.21150099988977572,6205.0,7391.83,7419.99,7348.27,609.23,4499487.53,7371.86
|
||||
2018-07-19 18:00:00,0.10839835323482973,0.23050014608126324,5922.0,7363.07,7431.1,7358.62,353.88,2620114.63,7422.04
|
||||
2018-07-19 19:00:00,0.1210115284698595,0.2446549891303321,5516.0,7421.89,7450.0,7406.46,248.57,1847374.31,7420.81
|
||||
2018-07-19 20:00:00,0.12769561242543415,0.2620480951938342,5346.0,7424.43,7488.0,7415.0,335.15,2499285.31,7448.08
|
||||
2018-07-19 21:00:00,0.11627265435113132,0.24421462507996972,4842.0,7448.08,7481.02,7414.66,341.19,2541848.79,7416.59
|
||||
2018-07-19 22:00:00,0.12117015923875779,0.23701036943748027,4596.0,7421.22,7460.2,7420.22,45.09,335446.22,7436.93
|
||||
2018-07-19 23:00:00,0.0787649784566368,0.23165228792384185,4187.0,7436.93,7570.9,7433.99,793.46,5947075.84,7479.61
|
||||
2018-07-20 00:00:00,0.08728006645427411,0.2209028353939531,4039.0,7485.18,7510.43,7431.1,288.01,2150833.25,7471.42
|
||||
2018-07-20 01:00:00,0.11516674961173322,0.2221229195530492,4113.0,7474.35,7475.99,7367.09,395.84,2932585.49,7409.27
|
||||
2018-07-20 02:00:00,0.10425012582819412,0.2272496181537681,3795.0,7409.62,7456.04,7389.34,193.28,1435525.58,7454.99
|
||||
2018-07-20 03:00:00,0.07460754622046298,0.21440884171861302,4032.0,7455.67,7471.23,7440.71,165.44,1233432.4,7453.99
|
||||
2018-07-20 04:00:00,0.1037929786100678,0.20109405904353525,3820.0,7455.15,7467.35,7428.37,188.45,1404045.57,7464.99
|
||||
2018-07-20 05:00:00,0.10570982080896332,0.22670832913753183,4181.0,7464.99,7466.48,7433.89,133.83,996276.67,7446.46
|
||||
2018-07-20 06:00:00,0.10053325863541185,0.21788108532109776,3782.0,7446.46,7454.99,7398.94,279.81,2077634.57,7409.78
|
||||
2018-07-20 07:00:00,0.08414827709682643,0.21499163800879564,4313.0,7409.78,7429.36,7338.91,630.88,4659133.12,7368.86
|
||||
2018-07-20 08:00:00,0.09010914398328636,0.20536192724458174,5755.0,7366.46,7446.8,7340.56,659.84,4872673.97,7439.8
|
||||
2018-07-20 09:00:00,0.09879370523308237,0.22031407763039842,5104.0,7438.04,7503.81,7433.81,548.73,4094985.82,7462.19
|
||||
2018-07-20 10:00:00,0.08814294560410647,0.18488960368603197,5180.0,7462.76,7479.99,7425.0,331.32,2468681.38,7441.72
|
||||
2018-07-20 11:00:00,0.10208339855904663,0.21178035276313925,5272.0,7439.52,7471.0,7437.96,234.2,1747024.94,7464.71
|
||||
2018-07-20 12:00:00,0.09804571430916943,0.20979500104083415,5459.0,7465.73,7514.47,7458.15,366.74,2744311.79,7494.0
|
||||
2018-07-20 13:00:00,0.09371463122741983,0.2187961052503923,5598.0,7494.0,7506.96,7437.47,245.64,1833699.6,7465.04
|
||||
2018-07-20 14:00:00,0.1171893448208811,0.2260779619183398,6369.0,7465.33,7478.73,7440.09,135.4,1010243.63,7466.15
|
||||
2018-07-20 15:00:00,0.10416287280578328,0.22643467088380403,6399.0,7466.15,7497.58,7431.1,318.68,2380183.59,7475.51
|
||||
2018-07-20 16:00:00,0.10553985034667926,0.21745263970717474,6361.0,7475.51,7517.84,7447.21,290.96,2174703.55,7471.67
|
||||
2018-07-20 17:00:00,0.09850890569577489,0.21561035761872477,6394.0,7471.46,7696.88,7463.39,1510.0,11439228.05,7463.39
|
||||
2018-07-20 18:00:00,0.10134484567020713,0.23067609815253698,6217.0,7461.0,7492.15,7290.01,1046.06,7723792.29,7330.39
|
||||
2018-07-20 19:00:00,0.09659720598948149,0.226286999012059,5433.0,7332.45,7388.0,7265.0,479.71,3516136.44,7357.98
|
||||
2018-07-20 20:00:00,0.10229267973913325,0.2380914675633593,4785.0,7354.54,7380.99,7290.0,289.33,2122913.02,7344.97
|
||||
2018-07-20 21:00:00,0.10900678497248634,0.23506402045291955,4398.0,7344.99,7375.0,7321.77,147.05,1080813.42,7349.99
|
||||
2018-07-20 22:00:00,0.10832154132262885,0.24604585086842823,3684.0,7350.28,7370.77,7284.48,130.47,957538.97,7300.22
|
||||
2018-07-20 23:00:00,0.09528614152701649,0.23572697984581573,3691.0,7300.22,7372.2,7276.43,221.74,1624157.14,7359.41
|
||||
2018-07-21 00:00:00,0.0933235286912038,0.20864850497750845,3541.0,7359.41,7359.41,7305.51,435.78,3191418.87,7330.84
|
||||
2018-07-21 01:00:00,0.11307970936560656,0.22957918763657537,3973.0,7330.84,7330.84,7212.0,870.94,6330338.54,7237.33
|
||||
2018-07-21 02:00:00,0.09658274372458275,0.2004882477405005,4107.0,7237.52,7272.82,7222.04,148.68,1077986.74,7260.82
|
||||
2018-07-21 03:00:00,0.1128373221892612,0.2257256708766154,3546.0,7260.81,7301.55,7255.36,232.07,1691227.04,7276.99
|
||||
2018-07-21 04:00:00,0.10440665521966554,0.20534172494766,3429.0,7276.99,7292.98,7256.7,99.61,724964.94,7276.7
|
||||
2018-07-21 05:00:00,0.1217976329133393,0.22545816021356463,3608.0,7276.7,7301.71,7252.01,66.48,483680.98,7301.65
|
||||
2018-07-21 06:00:00,0.10741531073319543,0.20666120511628086,3556.0,7301.74,7334.74,7286.9,150.87,1102500.41,7322.46
|
||||
2018-07-21 07:00:00,0.10464420305147851,0.2204195054748561,3672.0,7328.24,7352.42,7305.07,202.44,1483369.93,7343.78
|
||||
2018-07-21 08:00:00,0.10354493260245629,0.22569615022402867,4264.0,7343.27,7344.99,7311.6,199.19,1459975.45,7322.97
|
||||
2018-07-21 09:00:00,0.1098208735910409,0.21986457019400601,3827.0,7321.09,7328.12,7297.74,90.87,664644.84,7312.98
|
||||
2018-07-21 10:00:00,0.11901263145477894,0.21877047037671676,4266.0,7312.99,7339.49,7307.06,70.72,518060.6,7323.96
|
||||
2018-07-21 11:00:00,0.10593457957705563,0.21222636737527462,3937.0,7320.01,7333.74,7281.42,358.36,2614648.61,7286.96
|
||||
2018-07-21 12:00:00,0.09928269927455888,0.19453921211553568,4589.0,7286.95,7321.05,7281.55,126.68,923983.24,7313.47
|
||||
2018-07-21 13:00:00,0.11923258790066131,0.21638568264272276,4439.0,7307.09,7357.25,7293.04,156.19,1145572.08,7340.29
|
||||
2018-07-21 14:00:00,0.10098612445382547,0.2016477467970073,4529.0,7340.99,7370.0,7340.0,250.54,1843444.5,7356.01
|
||||
2018-07-21 15:00:00,0.10157389389702721,0.202950967384158,4902.0,7352.0,7380.66,7345.26,182.97,1347541.91,7350.68
|
||||
2018-07-21 16:00:00,0.09641253371676677,0.21278828120634385,4833.0,7350.68,7413.2,7336.59,196.62,1453185.74,7390.67
|
||||
2018-07-21 17:00:00,0.0995958974354282,0.20680878531929076,4700.0,7389.98,7429.79,7382.99,156.83,1161130.54,7399.97
|
||||
2018-07-21 18:00:00,0.10905814218071068,0.22951690316149903,4210.0,7397.18,7428.78,7371.93,170.1,1258317.25,7410.33
|
||||
2018-07-21 19:00:00,0.07858763234272367,0.2569517234589236,4097.0,7405.12,7443.33,7405.11,87.93,653121.75,7432.99
|
||||
2018-07-21 20:00:00,0.1113174433622039,0.2267321518306913,3831.0,7433.99,7449.66,7393.01,80.07,594254.35,7424.99
|
||||
2018-07-21 21:00:00,0.11224272657066275,0.23438750080921497,3591.0,7418.61,7458.0,7409.56,69.65,517298.07,7414.2
|
||||
2018-07-21 22:00:00,0.09651080685798608,0.21117207476044,3859.0,7414.2,7430.16,7395.22,26.6,197235.09,7412.56
|
||||
2018-07-21 23:00:00,0.10581036678100333,0.20383254887140026,4054.0,7412.56,7425.0,7396.83,29.27,216812.48,7415.57
|
||||
2018-07-22 00:00:00,0.10194283543860032,0.21383450044430183,4367.0,7424.99,7425.0,7400.8,26.13,193732.87,7409.92
|
||||
2018-07-22 01:00:00,0.1040755127249144,0.21786207321381515,3273.0,7398.16,7449.67,7336.15,268.23,1981138.35,7446.98
|
||||
2018-07-22 02:00:00,0.1152619306152038,0.2088211541143237,3301.0,7446.45,7478.0,7422.96,110.05,820165.37,7472.39
|
||||
2018-07-22 03:00:00,0.1194643276315172,0.2178897738159717,3235.0,7476.54,7486.04,7418.44,182.77,1363437.32,7433.53
|
||||
2018-07-22 04:00:00,0.12050623290831733,0.22002535380158078,3241.0,7425.0,7430.16,7398.44,140.51,1041527.4,7408.48
|
||||
2018-07-22 05:00:00,0.1350877194600542,0.23946630493812396,3096.0,7415.96,7415.96,7358.61,249.65,1843379.84,7394.89
|
||||
2018-07-22 06:00:00,0.1262987140367526,0.245820422036782,3177.0,7389.1,7405.99,7365.0,117.91,870528.63,7404.89
|
||||
2018-07-22 07:00:00,0.11411391234579984,0.2309179823335156,3383.0,7398.32,7405.55,7365.02,36.81,271870.33,7385.51
|
||||
2018-07-22 08:00:00,0.11418540423608992,0.2216572789009823,3891.0,7393.17,7404.43,7380.5,90.13,666107.38,7388.59
|
||||
2018-07-22 09:00:00,0.12278375136149591,0.2023395371945722,3863.0,7395.69,7462.42,7388.63,175.52,1304602.31,7442.52
|
||||
2018-07-22 10:00:00,0.11977810676752554,0.21598897881516124,4253.0,7440.53,7455.01,7428.55,73.56,547357.24,7442.6
|
||||
2018-07-22 11:00:00,0.10547037658357916,0.2006770907117357,4474.0,7434.3,7460.0,7426.63,102.93,766518.15,7447.7
|
||||
2018-07-22 12:00:00,0.12202057407182905,0.20553985614888104,5258.0,7456.45,7468.31,7442.69,63.61,474263.13,7450.98
|
||||
2018-07-22 13:00:00,0.09292394764555745,0.20145485862793946,4573.0,7450.88,7457.59,7427.11,84.88,631847.95,7429.06
|
||||
2018-07-22 14:00:00,0.08671733818551153,0.18255175859268646,4850.0,7427.3,7486.98,7427.3,145.01,1081758.53,7459.55
|
||||
2018-07-22 15:00:00,0.08965528482891023,0.183903537238312,4655.0,7459.56,7515.0,7449.75,288.01,2155953.39,7481.92
|
||||
2018-07-22 16:00:00,0.10648621710232598,0.20488575993511304,5139.0,7481.92,7551.94,7481.92,687.13,5175198.38,7526.63
|
||||
2018-07-22 17:00:00,0.10659364491955034,0.206219169508721,4769.0,7526.64,7544.93,7479.0,179.9,1352034.77,7517.17
|
||||
2018-07-22 18:00:00,0.08911612480432447,0.20697637765328827,4332.0,7517.26,7523.37,7481.54,66.57,499181.8,7497.72
|
||||
2018-07-22 19:00:00,0.08788718672766556,0.1950247629306966,4146.0,7493.03,7533.41,7493.03,75.79,569715.5,7508.51
|
||||
2018-07-22 20:00:00,0.09081366743628874,0.20768423288149673,3764.0,7508.57,7535.0,7501.19,237.26,1784881.96,7520.01
|
||||
2018-07-22 21:00:00,0.10586384162224395,0.21782724942968124,4331.0,7523.21,7546.99,7515.97,230.22,1734329.47,7520.0
|
||||
2018-07-22 22:00:00,0.11126556695736717,0.2349190790601346,4033.0,7522.36,7581.03,7338.91,968.69,7187218.03,7365.92
|
||||
2018-07-22 23:00:00,0.10922222548953939,0.2087997272094735,3853.0,7375.99,7423.2,7340.23,308.61,2278158.96,7406.09
|
||||
2018-07-23 00:00:00,0.10475577050207723,0.1975975491182442,3461.0,7402.32,7413.97,7376.32,224.23,1658642.03,7396.6
|
||||
2018-07-23 01:00:00,0.11149394600059791,0.212647853168363,3535.0,7393.5,7474.01,7369.86,609.63,4524224.24,7465.43
|
||||
2018-07-23 02:00:00,0.11047602335988127,0.22075716985714774,3452.0,7465.68,7520.0,7448.82,217.97,1631448.96,7518.64
|
||||
2018-07-23 03:00:00,0.09511737513819504,0.20342365895426537,3986.0,7518.64,7673.0,7511.86,1669.28,12700066.1,7637.22
|
||||
2018-07-23 04:00:00,0.09786054067564111,0.1928907161786437,4245.0,7637.22,7648.99,7606.21,210.54,1605740.75,7629.49
|
||||
2018-07-23 05:00:00,0.11115644692094986,0.19892366004931056,4420.0,7626.27,7707.68,7623.62,691.15,5300988.05,7679.95
|
||||
2018-07-23 06:00:00,0.0930190659985257,0.1914312574946213,3764.0,7675.71,7678.69,7628.58,221.08,1691646.71,7649.09
|
||||
2018-07-23 07:00:00,0.09844149580000178,0.2127421874307118,4030.0,7649.99,7703.83,7644.1,456.85,3505971.91,7680.0
|
||||
2018-07-23 08:00:00,0.1032116792203447,0.20561868482535076,5550.0,7679.99,7786.92,7647.99,1135.38,8779071.84,7749.51
|
||||
2018-07-23 09:00:00,0.08239309692567295,0.20248244219901074,5773.0,7749.51,7761.93,7678.7,494.54,3814472.79,7710.6
|
||||
2018-07-23 10:00:00,0.0935212329017346,0.18504442677479818,5171.0,7711.42,7721.77,7666.59,385.52,2967772.35,7711.08
|
||||
2018-07-23 11:00:00,0.10625135285351818,0.1971017527934391,5196.0,7716.81,7717.2,7670.0,269.5,2072539.69,7692.32
|
||||
2018-07-23 12:00:00,0.113248706472941,0.227611147137981,5627.0,7692.46,7711.99,7644.14,373.01,2865394.65,7683.28
|
||||
2018-07-23 13:00:00,0.09681735481146139,0.20133591857355834,5724.0,7683.28,7716.81,7660.0,223.22,1715839.95,7699.99
|
||||
2018-07-23 14:00:00,0.08262967845476092,0.21096312091455532,6166.0,7699.99,7728.86,7695.74,438.37,3380900.33,7716.09
|
||||
2018-07-23 15:00:00,0.09774247097918552,0.2200634400549309,5847.0,7716.09,7721.77,7680.51,442.38,3409098.97,7694.43
|
||||
2018-07-23 16:00:00,0.09576028411968329,0.21172021045644548,5821.0,7694.56,7740.0,7687.49,828.8,6400465.69,7716.45
|
||||
2018-07-23 17:00:00,0.09950865597332739,0.23053129702339756,5665.0,7719.99,7740.0,7701.99,592.3,4577037.35,7733.59
|
||||
2018-07-23 18:00:00,0.0932363588627437,0.2090972509522472,5399.0,7733.59,7749.0,7707.39,324.45,2505429.39,7728.37
|
||||
2018-07-23 19:00:00,0.09243442142842846,0.2301853582351032,5606.0,7727.4,7800.0,7638.03,1396.32,10800309.53,7735.53
|
||||
2018-07-23 20:00:00,0.08816379064295315,0.22017791032853326,5420.0,7736.08,7800.0,7724.5,514.3,3993228.42,7744.19
|
||||
2018-07-23 21:00:00,0.10728226544791052,0.23563579471332594,5164.0,7746.99,7763.59,7690.16,237.63,1836633.86,7706.0
|
||||
2018-07-23 22:00:00,0.09449302248273747,0.271796113269155,4646.0,7699.13,7759.99,7690.5,63.31,489000.25,7750.09
|
||||
2018-07-23 23:00:00,0.0742455916391433,0.2316396917419365,4455.0,7754.57,7777.0,7715.45,280.46,2173424.81,7722.32
|
||||
2018-07-24 00:00:00,0.08086966898267806,0.2193670741288557,3862.0,7722.95,7730.61,7690.17,496.48,3830571.66,7719.62
|
||||
2018-07-24 01:00:00,0.09071721460745699,0.2126255809666524,4620.0,7712.46,7727.7,7691.14,163.99,1264085.79,7723.22
|
||||
|
+3169
File diff suppressed because it is too large.
Load diff
+342
@@ -0,0 +1,342 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"import pandas as pd\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"import seaborn as sns\n",
|
||||
"sns.set()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"['../dataset/AMD.csv',\n",
|
||||
" '../dataset/FB.csv',\n",
|
||||
" '../dataset/FSV.csv',\n",
|
||||
" '../dataset/INFY.csv',\n",
|
||||
" '../dataset/KNX.csv',\n",
|
||||
" '../dataset/MONDY.csv',\n",
|
||||
" '../dataset/MTDR.csv',\n",
|
||||
" '../dataset/SINA.csv',\n",
|
||||
" '../dataset/TMUS.csv',\n",
|
||||
" '../dataset/TSLA.csv',\n",
|
||||
" '../dataset/TWTR.csv']"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"directory = '../dataset/'\n",
|
||||
"ori_name = ['AMD.csv', 'FB.csv', 'FSV.csv', 'INFY.csv', 'KNX.csv',\n",
|
||||
" 'MONDY.csv', 'MTDR.csv', 'SINA.csv', 'TMUS.csv', 'TSLA.csv', 'TWTR.csv']\n",
|
||||
"stocks = [directory + s for s in ori_name]\n",
|
||||
"stocks"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"dfs = [pd.read_csv(s)[['Date', 'Close']] for s in stocks]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"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>Close_x</th>\n",
|
||||
" <th>Close_y</th>\n",
|
||||
" <th>Close_x</th>\n",
|
||||
" <th>Close_y</th>\n",
|
||||
" <th>Close_x</th>\n",
|
||||
" <th>Close_y</th>\n",
|
||||
" <th>Close_x</th>\n",
|
||||
" <th>Close_y</th>\n",
|
||||
" <th>Close_x</th>\n",
|
||||
" <th>Close_y</th>\n",
|
||||
" <th>Close</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>16.270000</td>\n",
|
||||
" <td>207.320007</td>\n",
|
||||
" <td>78.820000</td>\n",
|
||||
" <td>9.710</td>\n",
|
||||
" <td>37.910000</td>\n",
|
||||
" <td>56.889999</td>\n",
|
||||
" <td>31.809999</td>\n",
|
||||
" <td>84.070000</td>\n",
|
||||
" <td>61.680000</td>\n",
|
||||
" <td>318.869995</td>\n",
|
||||
" <td>44.490002</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>16.580000</td>\n",
|
||||
" <td>207.229996</td>\n",
|
||||
" <td>78.250000</td>\n",
|
||||
" <td>9.800</td>\n",
|
||||
" <td>36.360001</td>\n",
|
||||
" <td>56.639999</td>\n",
|
||||
" <td>31.670000</td>\n",
|
||||
" <td>83.949997</td>\n",
|
||||
" <td>61.630001</td>\n",
|
||||
" <td>310.100006</td>\n",
|
||||
" <td>44.259998</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>16.870001</td>\n",
|
||||
" <td>209.990005</td>\n",
|
||||
" <td>77.940002</td>\n",
|
||||
" <td>9.950</td>\n",
|
||||
" <td>36.279999</td>\n",
|
||||
" <td>57.730000</td>\n",
|
||||
" <td>32.020000</td>\n",
|
||||
" <td>84.870003</td>\n",
|
||||
" <td>61.209999</td>\n",
|
||||
" <td>322.690002</td>\n",
|
||||
" <td>44.709999</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>16.850000</td>\n",
|
||||
" <td>209.360001</td>\n",
|
||||
" <td>77.940002</td>\n",
|
||||
" <td>9.840</td>\n",
|
||||
" <td>37.500000</td>\n",
|
||||
" <td>57.810001</td>\n",
|
||||
" <td>31.740000</td>\n",
|
||||
" <td>83.989998</td>\n",
|
||||
" <td>60.520000</td>\n",
|
||||
" <td>323.850006</td>\n",
|
||||
" <td>43.340000</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>16.709999</td>\n",
|
||||
" <td>208.089996</td>\n",
|
||||
" <td>78.055000</td>\n",
|
||||
" <td>9.855</td>\n",
|
||||
" <td>37.990002</td>\n",
|
||||
" <td>52.380001</td>\n",
|
||||
" <td>32.330002</td>\n",
|
||||
" <td>82.940002</td>\n",
|
||||
" <td>59.410000</td>\n",
|
||||
" <td>320.230011</td>\n",
|
||||
" <td>43.439999</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" Close_x Close_y Close_x Close_y Close_x Close_y Close_x \\\n",
|
||||
"0 16.270000 207.320007 78.820000 9.710 37.910000 56.889999 31.809999 \n",
|
||||
"1 16.580000 207.229996 78.250000 9.800 36.360001 56.639999 31.670000 \n",
|
||||
"2 16.870001 209.990005 77.940002 9.950 36.279999 57.730000 32.020000 \n",
|
||||
"3 16.850000 209.360001 77.940002 9.840 37.500000 57.810001 31.740000 \n",
|
||||
"4 16.709999 208.089996 78.055000 9.855 37.990002 52.380001 32.330002 \n",
|
||||
"\n",
|
||||
" Close_y Close_x Close_y Close \n",
|
||||
"0 84.070000 61.680000 318.869995 44.490002 \n",
|
||||
"1 83.949997 61.630001 310.100006 44.259998 \n",
|
||||
"2 84.870003 61.209999 322.690002 44.709999 \n",
|
||||
"3 83.989998 60.520000 323.850006 43.340000 \n",
|
||||
"4 82.940002 59.410000 320.230011 43.439999 "
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from functools import reduce\n",
|
||||
"data = reduce(lambda left,right: pd.merge(left,right,on='Date'), dfs).iloc[:, 1:]\n",
|
||||
"data.head()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"returns = data.pct_change()\n",
|
||||
"mean_daily_returns = returns.mean()\n",
|
||||
"volatilities = returns.std()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Close_x 0.995185\n",
|
||||
"Close_y -0.247949\n",
|
||||
"Close_x 0.119677\n",
|
||||
"Close_y 0.190845\n",
|
||||
"Close_x -0.175416\n",
|
||||
"Close_y -0.170502\n",
|
||||
"Close_x -0.626256\n",
|
||||
"Close_y -0.450914\n",
|
||||
"Close_x 0.252493\n",
|
||||
"Close_y -0.069273\n",
|
||||
"Close -0.273753\n",
|
||||
"dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"mean_daily_returns * 252"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"Close_x 12.196632\n",
|
||||
"Close_y 6.637175\n",
|
||||
"Close_x 3.677834\n",
|
||||
"Close_y 3.572859\n",
|
||||
"Close_x 7.104904\n",
|
||||
"Close_y 7.909165\n",
|
||||
"Close_x 8.121732\n",
|
||||
"Close_y 6.948244\n",
|
||||
"Close_x 3.863498\n",
|
||||
"Close_y 10.213733\n",
|
||||
"Close 8.873234\n",
|
||||
"dtype: float64"
|
||||
]
|
||||
},
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"volatilities * 252"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"combine = pd.DataFrame({'returns': mean_daily_returns * 252,\n",
|
||||
" 'volatility': volatilities * 252})"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 504x504 with 3 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {
|
||||
"needs_background": "light"
|
||||
},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"g = sns.jointplot(\"volatility\", \"returns\", data=combine, kind=\"reg\",height=7)\n",
|
||||
"\n",
|
||||
"for i in range(combine.shape[0]):\n",
|
||||
" plt.annotate(ori_name[i].replace('.csv',''), (combine.iloc[i, 1], combine.iloc[i, 0]))\n",
|
||||
" \n",
|
||||
"plt.text(0, -1.5, 'SELL', fontsize=25)\n",
|
||||
"plt.text(0, 1.0, 'BUY', fontsize=25)\n",
|
||||
" \n",
|
||||
"plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"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": "3.6.8"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
BIN
Binary file not shown.
|
After Width: | Height: | Size: 30 KiB |
Reference in new issue
Block a user