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66 | 66 | "name": "stderr",
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67 | 67 | "output_type": "stream",
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68 | 68 | "text": [
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69 |
| - "/usr/local/google/home/swast/src/bigframes-2/bigframes/core/global_session.py:113: DefaultLocationWarning: No explicit location is set, so using location US for the session.\n", |
70 |
| - " return func(get_global_session(), *args, **kwargs)\n" |
| 69 | + "/home/swast/src/github.com/googleapis/python-bigquery-dataframes/bigframes/core/global_session.py:103: DefaultLocationWarning: No explicit location is set, so using location US for the session.\n", |
| 70 | + " _global_session = bigframes.session.connect(\n" |
71 | 71 | ]
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| 72 | + }, |
| 73 | + { |
| 74 | + "data": { |
| 75 | + "text/html": [ |
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| 77 | + ], |
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| 80 | + ] |
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72 | 84 | }
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73 | 85 | ],
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74 | 86 | "source": [
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96 | 108 | },
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97 | 109 | {
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98 | 110 | "cell_type": "code",
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99 |
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| 111 | + "execution_count": 4, |
100 | 112 | "metadata": {},
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101 | 113 | "outputs": [
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102 | 114 | {
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103 | 115 | "data": {
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104 | 116 | "text/html": [
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105 |
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106 | 118 | ],
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107 | 119 | "text/plain": [
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108 | 120 | "<IPython.core.display.HTML object>"
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128 | 140 | },
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129 | 141 | {
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130 | 142 | "cell_type": "code",
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131 |
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132 | 144 | "metadata": {},
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133 | 145 | "outputs": [
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134 | 146 | {
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135 | 147 | "data": {
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136 | 148 | "text/html": [
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137 |
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138 | 150 | ],
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139 | 151 | "text/plain": [
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140 | 152 | "<IPython.core.display.HTML object>"
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146 | 158 | {
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147 | 159 | "data": {
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148 | 160 | "text/plain": [
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149 |
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150 | 162 | ]
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151 | 163 | },
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152 |
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| 164 | + "execution_count": 5, |
153 | 165 | "metadata": {},
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154 | 166 | "output_type": "execute_result"
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155 | 167 | }
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172 | 184 | },
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173 | 185 | {
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174 | 186 | "cell_type": "code",
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175 |
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| 187 | + "execution_count": 6, |
176 | 188 | "metadata": {},
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177 | 189 | "outputs": [
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178 | 190 | {
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179 | 191 | "data": {
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180 | 192 | "text/html": [
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181 |
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182 | 194 | ],
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183 | 195 | "text/plain": [
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184 | 196 | "<IPython.core.display.HTML object>"
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192 | 204 | "output_type": "stream",
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193 | 205 | "text": [
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194 | 206 | " index int_col float_col string_col\n",
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195 |
| - "0 3 4 -0.1250 d\n", |
196 |
| - "1 1 2 -0.5000 b\n", |
| 207 | + "0 1 2 -0.5000 b\n", |
| 208 | + "1 2 3 0.2500 c\n", |
197 | 209 | "2 0 1 1.0000 a\n",
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198 |
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199 |
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| 210 | + "3 3 4 -0.1250 d\n", |
| 211 | + "4 4 5 0.0625 e\n" |
200 | 212 | ]
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201 | 213 | }
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202 | 214 | ],
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238 | 250 | },
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239 | 251 | {
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240 | 252 | "cell_type": "code",
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241 |
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| 253 | + "execution_count": 7, |
242 | 254 | "metadata": {},
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243 | 255 | "outputs": [
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244 | 256 | {
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245 | 257 | "data": {
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246 | 258 | "text/html": [
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247 |
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| 259 | + "Query job b6f68a49-5129-448d-bca3-62a23dced10d is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:b6f68a49-5129-448d-bca3-62a23dced10d&page=queryresults\">Open Job</a>" |
248 | 260 | ],
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249 | 261 | "text/plain": [
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250 | 262 | "<IPython.core.display.HTML object>"
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258 | 270 | "output_type": "stream",
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259 | 271 | "text": [
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260 | 272 | " index int_col float_col string_col\n",
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261 |
| - "0 1 2 -0.5000 b\n", |
262 |
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263 |
| - "2 0 1 1.0000 a\n", |
264 |
| - "3 4 5 0.0625 e\n", |
265 |
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| 273 | + "0 3 4 -0.1250 d\n", |
| 274 | + "1 1 2 -0.5000 b\n", |
| 275 | + "2 4 5 0.0625 e\n", |
| 276 | + "3 2 3 0.2500 c\n", |
| 277 | + "4 0 1 1.0000 a\n" |
266 | 278 | ]
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267 | 279 | }
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268 | 280 | ],
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274 | 286 | " table_id = df.to_gbq()\n",
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275 | 287 | "\n",
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276 | 288 | " bqclient = df.bqclient\n",
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277 |
| - " token = bqclient._credentials.token\n", |
| 289 | + " token = bqclient._http.credentials.token\n", |
278 | 290 | " project_id = bqclient.project\n",
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279 | 291 | "\n",
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280 | 292 | " share_table_and_start_workload(table_id, token, project_id)\n",
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335 | 347 | },
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336 | 348 | {
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337 | 349 | "cell_type": "code",
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338 |
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| 350 | + "execution_count": 8, |
339 | 351 | "metadata": {},
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340 | 352 | "outputs": [
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341 | 353 | {
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342 | 354 | "data": {
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343 | 355 | "text/html": [
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344 |
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| 356 | + "Query job 0f205180-cf26-46e5-950d-109947b7f5a1 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:0f205180-cf26-46e5-950d-109947b7f5a1&page=queryresults\">Open Job</a>" |
345 | 357 | ],
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346 | 358 | "text/plain": [
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347 | 359 | "<IPython.core.display.HTML object>"
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353 | 365 | {
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354 | 366 | "data": {
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355 | 367 | "text/plain": [
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356 |
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357 | 369 | ]
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358 | 370 | },
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359 |
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| 371 | + "execution_count": 8, |
360 | 372 | "metadata": {},
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361 | 373 | "output_type": "execute_result"
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362 | 374 | }
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378 | 390 | },
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379 | 391 | {
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380 | 392 | "cell_type": "code",
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381 |
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| 393 | + "execution_count": 9, |
382 | 394 | "metadata": {},
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383 | 395 | "outputs": [
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384 | 396 | {
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385 | 397 | "data": {
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386 | 398 | "text/html": [
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387 |
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388 | 400 | ],
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389 | 401 | "text/plain": [
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390 | 402 | "<IPython.core.display.HTML object>"
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396 | 408 | {
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397 | 409 | "data": {
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398 | 410 | "text/plain": [
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399 |
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400 | 412 | ]
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401 | 413 | },
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402 |
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| 414 | + "execution_count": 9, |
403 | 415 | "metadata": {},
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404 | 416 | "output_type": "execute_result"
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405 | 417 | }
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427 | 439 | },
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428 | 440 | {
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429 | 441 | "cell_type": "code",
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430 |
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| 442 | + "execution_count": 10, |
431 | 443 | "metadata": {},
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432 | 444 | "outputs": [
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433 | 445 | {
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434 | 446 | "data": {
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435 | 447 | "text/plain": [
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436 |
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| 448 | + "Dataset(DatasetReference('bigframes-dev', 'my_dataset'))" |
437 | 449 | ]
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438 | 450 | },
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439 |
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| 451 | + "execution_count": 10, |
440 | 452 | "metadata": {},
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441 | 453 | "output_type": "execute_result"
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442 | 454 | }
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451 | 463 | },
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452 | 464 | {
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453 | 465 | "cell_type": "code",
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454 |
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| 466 | + "execution_count": 11, |
455 | 467 | "metadata": {},
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456 | 468 | "outputs": [
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457 |
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458 |
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459 |
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460 |
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461 |
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462 |
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463 |
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464 |
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465 |
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466 |
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467 |
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468 |
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469 |
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470 |
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471 |
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472 |
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473 |
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474 |
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475 |
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476 |
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477 |
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478 |
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479 |
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480 |
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481 | 469 | {
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482 | 470 | "data": {
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483 | 471 | "text/html": [
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593 | 581 | "[10 rows x 3 columns]"
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594 | 582 | ]
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595 | 583 | },
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596 |
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| 584 | + "execution_count": 11, |
597 | 585 | "metadata": {},
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598 | 586 | "output_type": "execute_result"
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599 | 587 | }
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683 | 671 | ],
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684 | 672 | "metadata": {
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685 | 673 | "kernelspec": {
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686 |
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| 674 | + "display_name": "venv", |
687 | 675 | "language": "python",
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688 | 676 | "name": "python3"
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689 | 677 | },
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697 | 685 | "name": "python",
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698 | 686 | "nbconvert_exporter": "python",
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699 | 687 | "pygments_lexer": "ipython3",
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700 |
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| 688 | + "version": "3.12.10" |
701 | 689 | }
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702 | 690 | },
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703 | 691 | "nbformat": 4,
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