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jupyter notebook upload

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  1. Untitled.ipynb +415 -0
Untitled.ipynb ADDED
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1
+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import pandas as pd\n",
10
+ "import os\n",
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+ "import random\n",
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+ "from sklearn.model_selection import train_test_split\n",
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+ "from tqdm import tqdm"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 3,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "def get_text_lists(filenames):\n",
23
+ " text_list = []\n",
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+ " text_list_clean = []\n",
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+ " for filename in filenames:\n",
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+ " with open(filename,'r') as file:\n",
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+ " data = file.read()\n",
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+ " text_list = text_list + (data.split(\"<EOS>\"))\n",
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+ " \n",
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+ " for text in text_list:\n",
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+ " #remove trailing ugly things at end of strings\n",
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+ " text = text[0:text.find(\"EmbedShare\")]\n",
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+ " text_list_clean.append(text)\n",
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+ " return text_list_clean"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 5,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "ename": "FileNotFoundError",
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+ "evalue": "[Errno 2] No such file or directory: 'novireperi.txt'",
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+ "output_type": "error",
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+ "traceback": [
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+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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+ "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
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+ "\u001b[0;32m<ipython-input-5-974cc4a9f270>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m text_list = get_text_lists([\"Lilgpt.txt\", \"ye.txt\", \"zenske.txt\", \"flowmasteri.txt\",\n\u001b[0;32m----> 2\u001b[0;31m \"wutang.txt\", \"novireperi.txt\", \"novireperi2.txt\", \"novireperi3.txt\", \"OF.txt\"])\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
50
+ "\u001b[0;32m<ipython-input-3-81b6d230f518>\u001b[0m in \u001b[0;36mget_text_lists\u001b[0;34m(filenames)\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mtext_list_clean\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfilename\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfilenames\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'r'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mtext_list\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtext_list\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"<EOS>\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
51
+ "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'novireperi.txt'"
52
+ ]
53
+ }
54
+ ],
55
+ "source": [
56
+ "text_list = get_text_lists([\"Lilgpt.txt\", \"ye.txt\", \"zenske.txt\", \"flowmasteri.txt\",\n",
57
+ " \"wutang.txt\", \"novireperi.txt\", \"novireperi2.txt\", \"novireperi3.txt\", \"OF.txt\"])\n",
58
+ "print(len(text_list))"
59
+ ]
60
+ },
61
+ {
62
+ "cell_type": "code",
63
+ "execution_count": 4,
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+ "metadata": {
65
+ "scrolled": true
66
+ },
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+ "outputs": [
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+ {
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+ "name": "stdout",
70
+ "output_type": "stream",
71
+ "text": [
72
+ "<BOS>3 Headed Goat[Intro]\n",
73
+ "(Aviator)\n",
74
+ "[Chorus: Lil Baby]\n",
75
+ "These ain't no Guess jeans\n",
76
+ "I dropped out of school, I'm still good at math, but, nigga, don't test me\n",
77
+ "I played to the left, they went to the right, they tried to finesse me\n",
78
+ "Still riding 'round with that blicky, I hope they don't catch me\n",
79
+ "Police had raided our spot, so we went to the next street\n",
80
+ "Play like I'm dumb, as soon as it pop, I'm goin' retarded\n",
81
+ "He say I'm hard and he say I'm garbage, I'm rich regardless\n",
82
+ "We in Miami in the middle of the winter, and we on them jet skis\n",
83
+ "If we in Atlanta, I'm runnin' the 'Cat and I'm workin' the red key\n",
84
+ "[Verse 1: Lil Durk]\n",
85
+ "I cannot mention my homies inside of my song 'cause I know they be trappin' a lot\n",
86
+ "I can't keep takin' these pills, when I'm in the trenches, they say I be cappin' a lot\n",
87
+ "I know a nigga who say he got rich off the dope, but I know he be actin' a lot\n",
88
+ "I know some niggas who said that they took down the city, but niggas be lackin' a lot\n",
89
+ "Yeah\n",
90
+ "That shit was awful, nigga had that dog food\n",
91
+ "That day they shot you, I slid on a Mongoose\n",
92
+ "You cannot come back around me, you turned your back on me, I cannot forget\n",
93
+ "The police was lyin', they say that they caught you, but nigga, they made you admit\n",
94
+ "Your name was found, you put in that work, they took your stick, you a bitch\n",
95
+ "Fuck my opps, they be on my dick, they all be mad we rich (Turn up)\n",
96
+ "[Verse 2: Lil Baby]\n",
97
+ "Only twenty-five, livin' like a boss, ridin' 'round with a chauffeur\n",
98
+ "I don't sell drugs, still be paranoid, keep lookin' over my shoulder\n",
99
+ "Niggas lyin' like I'm stealin' swag, boy, that's my shit like I wrote it\n",
100
+ "[Verse 3: Polo G]\n",
101
+ "Uh\n",
102
+ "These rappers really nice as hell\n",
103
+ "I'm a different nigga when I'm pissed off\n",
104
+ "Man, he say he gon' press up on who?\n",
105
+ "I'ma get the steel like I'm Chris Paul\n",
106
+ "Back to back suburbans, I'm a big dawg\n",
107
+ "I was in the slums servin' Fentanyl\n",
108
+ "Zombieland, junkies havin' withdrawals\n",
109
+ "I been gettin' to it, lotta missed calls\n",
110
+ "Turn it off, what the fuck is he talking 'bout?\n",
111
+ "I should slap you for sayin' he hot as me\n",
112
+ "I don't know who could fuck with me honestly\n",
113
+ "They know I'm the man, so they watchin' me\n",
114
+ "Different color bands like Monopoly\n",
115
+ "Man, he must not be usin' his head\n",
116
+ "If he thinkin' I don't keep a Glock with me\n",
117
+ "That's like suicide if you play with us\n",
118
+ "Got a better chance at the lottery\n",
119
+ "Call an ambulance when that chopper sweep\n",
120
+ "Make the crowd dance, choreography\n",
121
+ "Once I got a plan, ain't no stoppin' me\n",
122
+ "Three-car garage, million-dollar crib\n",
123
+ "With a foreign bitch ridin' on top of me\n",
124
+ "Lot of people done said I wouldn't be shit\n",
125
+ "Well, I guess they owe me an apology\n",
126
+ "[Chorus: Lil Baby]\n",
127
+ "These ain't no Guess jeans\n",
128
+ "I dropped out of school, I'm still good at math, but, nigga, don't test me\n",
129
+ "I played to the left, they went to the right, they tried to finesse me\n",
130
+ "Still riding 'round with that blicky, I hope they don't catch me\n",
131
+ "Police had raided our spot, so we went to the next street\n",
132
+ "Play like I'm dumb, as soon as it pop, I'm goin' retarded\n",
133
+ "He say I'm hard and he say I'm garbage, I'm rich regardless\n",
134
+ "We in Miami in the middle of the winter, and we on them jet skis\n",
135
+ "If we in Atlanta, I'm runnin' the 'Cat and I'm workin' the red key35<EOS>\n"
136
+ ]
137
+ }
138
+ ],
139
+ "source": [
140
+ "new_list = []\n",
141
+ "for l in text_list:\n",
142
+ " n = l\n",
143
+ " n = n.replace(\"<BOS>\",\"\")\n",
144
+ " n = os.linesep.join([s for s in n.splitlines() if s])\n",
145
+ " n = \"<BOS>\"+ n + \"<EOS>\"\n",
146
+ " new_list.append(n)"
147
+ ]
148
+ },
149
+ {
150
+ "cell_type": "code",
151
+ "execution_count": 10,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "1287\n",
159
+ "11583\n"
160
+ ]
161
+ }
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+ ],
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+ "source": [
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+ "List_train, List_val = train_test_split(new_list, test_size = 0.1, random_state = 420)\n",
165
+ "print(len(List_val))\n",
166
+ "print(len(List_train))"
167
+ ]
168
+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 11,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "100%|█████████████████████████████████████| 1286/1286 [00:01<00:00, 1215.57it/s]\n"
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+ ]
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+ }
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+ ],
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+ "source": [
183
+ "val_set = List_val[0]\n",
184
+ "for i in tqdm(range(1,len(List_val))):\n",
185
+ " val_set = val_set+\"\\n\\n\"+ List_val[i]"
186
+ ]
187
+ },
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+ {
189
+ "cell_type": "code",
190
+ "execution_count": 12,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "100%|█████████████████████████████████████| 11582/11582 [05:06<00:00, 37.77it/s]\n"
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+ ]
199
+ }
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+ ],
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+ "source": [
202
+ "train_set = List_train[0]\n",
203
+ "for i in tqdm(range(1,len(List_train))):\n",
204
+ " train_set = train_set+\"\\n\\n\"+List_train[i]"
205
+ ]
206
+ },
207
+ {
208
+ "cell_type": "code",
209
+ "execution_count": 13,
210
+ "metadata": {},
211
+ "outputs": [],
212
+ "source": [
213
+ "file1 = open(\"train2.txt\",\"w+\")\n",
214
+ "file1.write(train_set)\n",
215
+ "file1.close()"
216
+ ]
217
+ },
218
+ {
219
+ "cell_type": "code",
220
+ "execution_count": 14,
221
+ "metadata": {},
222
+ "outputs": [],
223
+ "source": [
224
+ "file2 = open(\"val2.txt\",\"w+\")\n",
225
+ "file2.write(val_set)\n",
226
+ "file2.close()"
227
+ ]
228
+ },
229
+ {
230
+ "cell_type": "code",
231
+ "execution_count": 15,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/html": [
237
+ "<div>\n",
238
+ "<style scoped>\n",
239
+ " .dataframe tbody tr th:only-of-type {\n",
240
+ " vertical-align: middle;\n",
241
+ " }\n",
242
+ "\n",
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+ " .dataframe tbody tr th {\n",
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+ " vertical-align: top;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
249
+ " }\n",
250
+ "</style>\n",
251
+ "<table border=\"1\" class=\"dataframe\">\n",
252
+ " <thead>\n",
253
+ " <tr style=\"text-align: right;\">\n",
254
+ " <th></th>\n",
255
+ " <th>Songs</th>\n",
256
+ " </tr>\n",
257
+ " </thead>\n",
258
+ " <tbody>\n",
259
+ " <tr>\n",
260
+ " <th>0</th>\n",
261
+ " <td>&lt;BOS&gt;Night CourtBehind door one:\\nThere's thre...</td>\n",
262
+ " </tr>\n",
263
+ " <tr>\n",
264
+ " <th>1</th>\n",
265
+ " <td>&lt;BOS&gt;Golden ArmsYeah, yeah\\nYeah, yeah\\n[Verse...</td>\n",
266
+ " </tr>\n",
267
+ " <tr>\n",
268
+ " <th>2</th>\n",
269
+ " <td>&lt;BOS&gt;Flashing Lights (Clipse Remix)[Intro]\\nWe...</td>\n",
270
+ " </tr>\n",
271
+ " <tr>\n",
272
+ " <th>3</th>\n",
273
+ " <td>&lt;BOS&gt;Lights Camera Action[Intro]\\nThe lights, ...</td>\n",
274
+ " </tr>\n",
275
+ " <tr>\n",
276
+ " <th>4</th>\n",
277
+ " <td>&lt;BOS&gt;Thug Life [Souljah] (Original Version 1)[...</td>\n",
278
+ " </tr>\n",
279
+ " </tbody>\n",
280
+ "</table>\n",
281
+ "</div>"
282
+ ],
283
+ "text/plain": [
284
+ " Songs\n",
285
+ "0 <BOS>Night CourtBehind door one:\\nThere's thre...\n",
286
+ "1 <BOS>Golden ArmsYeah, yeah\\nYeah, yeah\\n[Verse...\n",
287
+ "2 <BOS>Flashing Lights (Clipse Remix)[Intro]\\nWe...\n",
288
+ "3 <BOS>Lights Camera Action[Intro]\\nThe lights, ...\n",
289
+ "4 <BOS>Thug Life [Souljah] (Original Version 1)[..."
290
+ ]
291
+ },
292
+ "execution_count": 15,
293
+ "metadata": {},
294
+ "output_type": "execute_result"
295
+ }
296
+ ],
297
+ "source": [
298
+ "df_train = pd.DataFrame(List_train,columns = [\"Songs\"])\n",
299
+ "df_train.head()"
300
+ ]
301
+ },
302
+ {
303
+ "cell_type": "code",
304
+ "execution_count": 16,
305
+ "metadata": {},
306
+ "outputs": [
307
+ {
308
+ "data": {
309
+ "text/html": [
310
+ "<div>\n",
311
+ "<style scoped>\n",
312
+ " .dataframe tbody tr th:only-of-type {\n",
313
+ " vertical-align: middle;\n",
314
+ " }\n",
315
+ "\n",
316
+ " .dataframe tbody tr th {\n",
317
+ " vertical-align: top;\n",
318
+ " }\n",
319
+ "\n",
320
+ " .dataframe thead th {\n",
321
+ " text-align: right;\n",
322
+ " }\n",
323
+ "</style>\n",
324
+ "<table border=\"1\" class=\"dataframe\">\n",
325
+ " <thead>\n",
326
+ " <tr style=\"text-align: right;\">\n",
327
+ " <th></th>\n",
328
+ " <th>Songs</th>\n",
329
+ " </tr>\n",
330
+ " </thead>\n",
331
+ " <tbody>\n",
332
+ " <tr>\n",
333
+ " <th>0</th>\n",
334
+ " <td>&lt;BOS&gt;Letter 2 My Unborn[Intro]\\nTo my unborn c...</td>\n",
335
+ " </tr>\n",
336
+ " <tr>\n",
337
+ " <th>1</th>\n",
338
+ " <td>&lt;BOS&gt;Trouble[Intro]\\nTrouble on last, oh well\\...</td>\n",
339
+ " </tr>\n",
340
+ " <tr>\n",
341
+ " <th>2</th>\n",
342
+ " <td>&lt;BOS&gt;SouthsideSu woo\\nBitch I'm from the south...</td>\n",
343
+ " </tr>\n",
344
+ " <tr>\n",
345
+ " <th>3</th>\n",
346
+ " <td>&lt;BOS&gt;Gangsta PartyFeat. Lil B\\n[Lil Wayne]\\nI ...</td>\n",
347
+ " </tr>\n",
348
+ " <tr>\n",
349
+ " <th>4</th>\n",
350
+ " <td>&lt;BOS&gt;Gangstaz Life[Verse 1: Snoop Dogg]\\n10-20...</td>\n",
351
+ " </tr>\n",
352
+ " </tbody>\n",
353
+ "</table>\n",
354
+ "</div>"
355
+ ],
356
+ "text/plain": [
357
+ " Songs\n",
358
+ "0 <BOS>Letter 2 My Unborn[Intro]\\nTo my unborn c...\n",
359
+ "1 <BOS>Trouble[Intro]\\nTrouble on last, oh well\\...\n",
360
+ "2 <BOS>SouthsideSu woo\\nBitch I'm from the south...\n",
361
+ "3 <BOS>Gangsta PartyFeat. Lil B\\n[Lil Wayne]\\nI ...\n",
362
+ "4 <BOS>Gangstaz Life[Verse 1: Snoop Dogg]\\n10-20..."
363
+ ]
364
+ },
365
+ "execution_count": 16,
366
+ "metadata": {},
367
+ "output_type": "execute_result"
368
+ }
369
+ ],
370
+ "source": [
371
+ "df_val = pd.DataFrame(List_val,columns = [\"Songs\"])\n",
372
+ "df_val.head()"
373
+ ]
374
+ },
375
+ {
376
+ "cell_type": "code",
377
+ "execution_count": 17,
378
+ "metadata": {},
379
+ "outputs": [],
380
+ "source": [
381
+ "df_train.to_csv(\"Train.tsv\",sep=\"\\t\",index = False)"
382
+ ]
383
+ },
384
+ {
385
+ "cell_type": "code",
386
+ "execution_count": 18,
387
+ "metadata": {},
388
+ "outputs": [],
389
+ "source": [
390
+ "df_val.to_csv(\"Val.tsv\",sep=\"\\t\",index = False)"
391
+ ]
392
+ }
393
+ ],
394
+ "metadata": {
395
+ "kernelspec": {
396
+ "display_name": "Python 3",
397
+ "language": "python",
398
+ "name": "python3"
399
+ },
400
+ "language_info": {
401
+ "codemirror_mode": {
402
+ "name": "ipython",
403
+ "version": 3
404
+ },
405
+ "file_extension": ".py",
406
+ "mimetype": "text/x-python",
407
+ "name": "python",
408
+ "nbconvert_exporter": "python",
409
+ "pygments_lexer": "ipython3",
410
+ "version": "3.6.9"
411
+ }
412
+ },
413
+ "nbformat": 4,
414
+ "nbformat_minor": 5
415
+ }