mirror of
https://github.com/gsi-upm/sitc
synced 2024-12-22 03:38:13 +00:00
Updated with the new libraries
This commit is contained in:
cif2cif
parent
2ba0e2f3d9
commit
ae8d3d3ba2
@ -76,7 +76,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 33,
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"metadata": {},
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"outputs": [
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{
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@ -85,7 +85,7 @@
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"(2034, 2807)"
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]
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},
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"execution_count": 1,
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"execution_count": 33,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -126,12 +126,15 @@
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"source": [
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"Although scikit-learn provides an LDA implementation, it is more popular the package *gensim*, which also provides an LSI implementation, as well as other functionalities. Fortunately, scikit-learn sparse matrices can be used in Gensim using the function *matutils.Sparse2Corpus()*. Anyway, if you are using intensively LDA,it can be convenient to create the corpus with their functions.\n",
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"\n",
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"You should install first *gensim*. Run 'conda install -c anaconda gensim=0.12.4' in a terminal."
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"You should install first:\n",
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"\n",
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"* *gensim*. Run 'conda install gensim' in a terminal.\n",
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"* *python-Levenshtein*. Run 'conda install python-Levenshtein' in a terminal"
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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": 2,
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"execution_count": 34,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -159,7 +162,7 @@
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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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"execution_count": 60,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -173,23 +176,23 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 61,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[(0,\n",
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" '0.007*\"car\" + 0.006*\"increased\" + 0.006*\"closely\" + 0.006*\"groups\" + 0.006*\"center\" + 0.006*\"88\" + 0.006*\"offer\" + 0.005*\"archie\" + 0.005*\"beginning\" + 0.005*\"comets\"'),\n",
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" '0.011*\"baptist\" + 0.010*\"koresh\" + 0.009*\"bible\" + 0.006*\"reality\" + 0.006*\"virtual\" + 0.005*\"scarlet\" + 0.005*\"shag\" + 0.004*\"tootsie\" + 0.004*\"kinda\" + 0.004*\"captain\"'),\n",
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" (1,\n",
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" '0.005*\"allow\" + 0.005*\"discuss\" + 0.005*\"condition\" + 0.004*\"certain\" + 0.004*\"member\" + 0.004*\"manipulation\" + 0.004*\"little\" + 0.003*\"proposal\" + 0.003*\"heavily\" + 0.003*\"obvious\"'),\n",
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" '0.010*\"targa\" + 0.008*\"thanks\" + 0.008*\"moon\" + 0.007*\"craig\" + 0.007*\"zoroastrians\" + 0.006*\"yayayay\" + 0.005*\"unfortunately\" + 0.005*\"windows\" + 0.005*\"rayshade\" + 0.004*\"tdb\"'),\n",
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" (2,\n",
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" '0.002*\"led\" + 0.002*\"mechanism\" + 0.002*\"frank\" + 0.002*\"platform\" + 0.002*\"mormons\" + 0.002*\"concepts\" + 0.002*\"proton\" + 0.002*\"aeronautics\" + 0.002*\"header\" + 0.002*\"foreign\"'),\n",
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" '0.009*\"mary\" + 0.007*\"whatever\" + 0.006*\"god\" + 0.005*\"ns\" + 0.005*\"lucky\" + 0.005*\"joseph\" + 0.005*\"ssrt\" + 0.005*\"samaritan\" + 0.005*\"crusades\" + 0.004*\"phobos\"'),\n",
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" (3,\n",
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" '0.004*\"objects\" + 0.003*\"activity\" + 0.003*\"manhattan\" + 0.003*\"obtained\" + 0.003*\"eyes\" + 0.003*\"education\" + 0.003*\"netters\" + 0.003*\"complex\" + 0.003*\"europe\" + 0.002*\"missions\"')]"
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" '0.009*\"islam\" + 0.008*\"western\" + 0.008*\"plane\" + 0.008*\"jeff\" + 0.007*\"cheers\" + 0.007*\"kent\" + 0.007*\"joy\" + 0.007*\"khomeini\" + 0.007*\"davidian\" + 0.006*\"basically\"')]"
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]
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},
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"execution_count": 4,
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"execution_count": 61,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -208,7 +211,7 @@
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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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"execution_count": 62,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -240,7 +243,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 63,
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"metadata": {},
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"outputs": [
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{
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@ -253,14 +256,14 @@
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],
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"source": [
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"# You can save the dictionary\n",
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"dictionary.save('newsgroup.dict')\n",
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"dictionary.save('newsgroup.dict.texts')\n",
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"\n",
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"print(dictionary)"
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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": 7,
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"execution_count": 64,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -271,7 +274,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 65,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -283,28 +286,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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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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"WARNING:root:random_state not set so using default value\n",
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"WARNING:root:failed to load state from newsgroups.dict.state: [Errno 2] No such file or directory: 'newsgroups.dict.state'\n"
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]
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}
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],
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"source": [
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"# You can optionally save the dictionary \n",
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"\n",
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"dictionary.save('newsgroups.dict')\n",
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"lda = LdaModel.load('newsgroups.dict')"
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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": 16,
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"execution_count": 71,
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"metadata": {},
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"outputs": [
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{
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@ -323,7 +305,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": 72,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -333,7 +315,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 73,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -346,7 +328,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 74,
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"metadata": {},
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"outputs": [
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{
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@ -364,7 +346,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 75,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -377,23 +359,23 @@
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"execution_count": 76,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[(0,\n",
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" '0.011*\"thanks\" + 0.010*\"targa\" + 0.008*\"mary\" + 0.008*\"western\" + 0.007*\"craig\" + 0.007*\"jeff\" + 0.006*\"yayayay\" + 0.006*\"phobos\" + 0.005*\"unfortunately\" + 0.005*\"martian\"'),\n",
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" '0.009*\"whatever\" + 0.007*\"plane\" + 0.007*\"ns\" + 0.007*\"joy\" + 0.006*\"happy\" + 0.005*\"bob\" + 0.004*\"phil\" + 0.004*\"nasa\" + 0.003*\"purdue\" + 0.003*\"neie\"'),\n",
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" (1,\n",
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" '0.007*\"islam\" + 0.006*\"koresh\" + 0.006*\"moon\" + 0.006*\"bible\" + 0.006*\"plane\" + 0.006*\"ns\" + 0.005*\"zoroastrians\" + 0.005*\"joy\" + 0.005*\"lucky\" + 0.005*\"ssrt\"'),\n",
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" '0.009*\"god\" + 0.008*\"mary\" + 0.008*\"targa\" + 0.007*\"baptist\" + 0.007*\"thanks\" + 0.007*\"koresh\" + 0.006*\"really\" + 0.006*\"bible\" + 0.005*\"lot\" + 0.005*\"lucky\"'),\n",
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" (2,\n",
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" '0.009*\"whatever\" + 0.009*\"baptist\" + 0.007*\"cheers\" + 0.007*\"kent\" + 0.006*\"khomeini\" + 0.006*\"davidian\" + 0.005*\"gerald\" + 0.005*\"bull\" + 0.005*\"sorry\" + 0.005*\"jesus\"'),\n",
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" '0.010*\"moon\" + 0.007*\"phobos\" + 0.006*\"unfortunately\" + 0.006*\"martian\" + 0.006*\"russian\" + 0.005*\"rayshade\" + 0.005*\"anybody\" + 0.005*\"perturbations\" + 0.005*\"thanks\" + 0.004*\"apollo\"'),\n",
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" (3,\n",
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" '0.005*\"pd\" + 0.004*\"baltimore\" + 0.004*\"also\" + 0.003*\"ipx\" + 0.003*\"dam\" + 0.003*\"feiner\" + 0.003*\"foley\" + 0.003*\"ideally\" + 0.003*\"srgp\" + 0.003*\"thank\"')]"
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" '0.008*\"islam\" + 0.008*\"western\" + 0.007*\"jeff\" + 0.007*\"zoroastrians\" + 0.006*\"davidian\" + 0.006*\"basically\" + 0.005*\"bull\" + 0.005*\"gerald\" + 0.005*\"sorry\" + 0.004*\"kent\"')]"
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]
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},
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"execution_count": 21,
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"execution_count": 76,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -405,14 +387,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"execution_count": 77,
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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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"[(0, 0.09401487), (1, 0.08991001), (2, 0.08514047), (3, 0.7309346)]\n"
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"[(0, 0.7154438), (1, 0.10569019), (2, 0.09522807), (3, 0.08363795)]\n"
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]
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}
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],
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@ -424,7 +406,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"execution_count": 78,
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"metadata": {},
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"outputs": [
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{
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@ -445,14 +427,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"execution_count": 79,
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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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"[(0, 0.06678458), (1, 0.8006135), (2, 0.06974816), (3, 0.062853776)]\n"
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"[(0, 0.06320839), (1, 0.80878526), (2, 0.06274223), (3, 0.065264106)]\n"
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]
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}
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],
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@ -464,14 +446,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"execution_count": 80,
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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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"0.007*\"islam\" + 0.006*\"koresh\" + 0.006*\"moon\" + 0.006*\"bible\" + 0.006*\"plane\" + 0.006*\"ns\" + 0.005*\"zoroastrians\" + 0.005*\"joy\" + 0.005*\"lucky\" + 0.005*\"ssrt\"\n"
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"0.009*\"god\" + 0.008*\"mary\" + 0.008*\"targa\" + 0.007*\"baptist\" + 0.007*\"thanks\" + 0.007*\"koresh\" + 0.006*\"really\" + 0.006*\"bible\" + 0.005*\"lot\" + 0.005*\"lucky\"\n"
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]
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}
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],
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@ -482,15 +464,15 @@
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"execution_count": 81,
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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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"[(0, 0.110989906), (1, 0.670005), (2, 0.11422917), (3, 0.10477593)]\n",
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"0.007*\"islam\" + 0.006*\"koresh\" + 0.006*\"moon\" + 0.006*\"bible\" + 0.006*\"plane\" + 0.006*\"ns\" + 0.005*\"zoroastrians\" + 0.005*\"joy\" + 0.005*\"lucky\" + 0.005*\"ssrt\"\n"
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"[(0, 0.10564032), (1, 0.67894983), (2, 0.104482815), (3, 0.11092702)]\n",
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"0.009*\"god\" + 0.008*\"mary\" + 0.008*\"targa\" + 0.007*\"baptist\" + 0.007*\"thanks\" + 0.007*\"koresh\" + 0.006*\"really\" + 0.006*\"bible\" + 0.005*\"lot\" + 0.005*\"lucky\"\n"
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]
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}
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],
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@ -510,7 +492,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"execution_count": 82,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -526,23 +508,23 @@
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"execution_count": 83,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[(0,\n",
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" '0.769*\"god\" + 0.345*\"jesus\" + 0.235*\"bible\" + 0.203*\"christian\" + 0.149*\"christians\" + 0.108*\"christ\" + 0.089*\"well\" + 0.085*\"koresh\" + 0.081*\"kent\" + 0.080*\"christianity\"'),\n",
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" '0.769*\"god\" + 0.346*\"jesus\" + 0.235*\"bible\" + 0.204*\"christian\" + 0.148*\"christians\" + 0.107*\"christ\" + 0.090*\"well\" + 0.085*\"koresh\" + 0.081*\"kent\" + 0.080*\"christianity\"'),\n",
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" (1,\n",
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" '-0.863*\"thanks\" + -0.255*\"please\" + -0.160*\"hello\" + -0.153*\"hi\" + 0.123*\"god\" + -0.112*\"sorry\" + -0.088*\"could\" + -0.075*\"windows\" + -0.068*\"jpeg\" + -0.062*\"gif\"'),\n",
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" '-0.863*\"thanks\" + -0.255*\"please\" + -0.159*\"hello\" + -0.152*\"hi\" + 0.124*\"god\" + -0.111*\"sorry\" + -0.088*\"could\" + -0.074*\"windows\" + -0.067*\"jpeg\" + -0.063*\"gif\"'),\n",
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" (2,\n",
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" '-0.779*\"well\" + 0.229*\"god\" + -0.164*\"yes\" + 0.153*\"thanks\" + -0.135*\"ico\" + -0.135*\"tek\" + -0.132*\"beauchaine\" + -0.132*\"queens\" + -0.132*\"bronx\" + -0.131*\"manhattan\"'),\n",
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" '-0.780*\"well\" + 0.229*\"god\" + -0.165*\"yes\" + 0.154*\"thanks\" + -0.133*\"ico\" + -0.133*\"tek\" + -0.130*\"queens\" + -0.130*\"bronx\" + -0.130*\"beauchaine\" + -0.130*\"manhattan\"'),\n",
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" (3,\n",
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" '0.343*\"well\" + -0.335*\"ico\" + -0.334*\"tek\" + -0.328*\"bronx\" + -0.328*\"beauchaine\" + -0.328*\"queens\" + -0.325*\"manhattan\" + -0.305*\"com\" + -0.303*\"bob\" + -0.073*\"god\"')]"
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" '-0.338*\"well\" + 0.336*\"ico\" + 0.334*\"tek\" + 0.328*\"bronx\" + 0.328*\"beauchaine\" + 0.328*\"queens\" + 0.326*\"manhattan\" + 0.305*\"com\" + 0.305*\"bob\" + 0.072*\"god\"')]"
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]
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},
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"execution_count": 29,
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"execution_count": 83,
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"metadata": {},
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"output_type": "execute_result"
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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": 30,
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"execution_count": 84,
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"metadata": {},
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"outputs": [
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{
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@ -603,6 +585,15 @@
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}
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],
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"metadata": {
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"datacleaner": {
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"position": {
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"top": "50px"
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},
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"python": {
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"varRefreshCmd": "try:\n print(_datacleaner.dataframe_metadata())\nexcept:\n print([])"
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},
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"window_display": false
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},
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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@ -618,7 +609,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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"version": "3.8.8"
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},
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"latex_envs": {
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"LaTeX_envs_menu_present": true,
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