## [1] "D:/BINUS UNIVERSITY/SEMESTER 4/Data Mining"# import dataset ke chunk R
df <- read.csv("ds_salaries.csv")
#check header data (asumsi baris lembar pertama)
head(df, 500)## X work_year experience_level employment_type
## 1 0 2020 MI FT
## 2 1 2020 SE FT
## 3 2 2020 SE FT
## 4 3 2020 MI FT
## 5 4 2020 SE FT
## 6 5 2020 EN FT
## 7 6 2020 SE FT
## 8 7 2020 MI FT
## 9 8 2020 MI FT
## 10 9 2020 SE FT
## 11 10 2020 EN FT
## 12 11 2020 MI FT
## 13 12 2020 EN FT
## 14 13 2020 MI FT
## 15 14 2020 MI FT
## 16 15 2020 MI FT
## 17 16 2020 EN FT
## 18 17 2020 SE FT
## 19 18 2020 EN FT
## 20 19 2020 MI FT
## 21 20 2020 MI FT
## 22 21 2020 MI FT
## 23 22 2020 SE FT
## 24 23 2020 MI FT
## 25 24 2020 MI FT
## 26 25 2020 EX FT
## 27 26 2020 EN FT
## 28 27 2020 SE FT
## 29 28 2020 EN CT
## 30 29 2020 SE FT
## 31 30 2020 MI FT
## 32 31 2020 EN FT
## 33 32 2020 SE FT
## 34 33 2020 MI FT
## 35 34 2020 MI FT
## 36 35 2020 MI FT
## 37 36 2020 MI FT
## 38 37 2020 EN FT
## 39 38 2020 EN FT
## 40 39 2020 EN FT
## 41 40 2020 MI FT
## 42 41 2020 EX FT
## 43 42 2020 MI FT
## 44 43 2020 MI FT
## 45 44 2020 MI FT
## 46 45 2020 EN PT
## 47 46 2020 MI FT
## 48 47 2020 SE FT
## 49 48 2020 MI FT
## 50 49 2020 MI FT
## 51 50 2020 EN FT
## 52 51 2020 EN FT
## 53 52 2020 EN FT
## 54 53 2020 EN FT
## 55 54 2020 SE FL
## 56 55 2020 SE FT
## 57 56 2020 MI FT
## 58 57 2020 MI FT
## 59 58 2020 SE FT
## 60 59 2020 MI FT
## 61 60 2020 MI FT
## 62 61 2020 MI FT
## 63 62 2020 EN PT
## 64 63 2020 SE FT
## 65 64 2020 SE FT
## 66 65 2020 EN FT
## 67 66 2020 EN FT
## 68 67 2020 SE FT
## 69 68 2020 EN FT
## 70 69 2020 SE FT
## 71 70 2020 MI FT
## 72 71 2020 MI FT
## 73 72 2021 EN FT
## 74 73 2021 EX FT
## 75 74 2021 EX FT
## 76 75 2021 SE FT
## 77 76 2021 MI FT
## 78 77 2021 MI PT
## 79 78 2021 MI CT
## 80 79 2021 EN FT
## 81 80 2021 SE FT
## 82 81 2021 MI FT
## 83 82 2021 MI FT
## 84 83 2021 MI FT
## 85 84 2021 EX FT
## 86 85 2021 MI FT
## 87 86 2021 EN FT
## 88 87 2021 MI FT
## 89 88 2021 SE FT
## 90 89 2021 SE FT
## 91 90 2021 SE FT
## 92 91 2021 EN FT
## 93 92 2021 MI FT
## 94 93 2021 SE FT
## 95 94 2021 EN FT
## 96 95 2021 MI FT
## 97 96 2021 EN PT
## 98 97 2021 MI FT
## 99 98 2021 EN FT
## 100 99 2021 MI FT
## 101 100 2021 MI FT
## 102 101 2021 SE FT
## 103 102 2021 MI FT
## 104 103 2021 MI FT
## 105 104 2021 MI FT
## 106 105 2021 MI FT
## 107 106 2021 MI FT
## 108 107 2021 SE FT
## 109 108 2021 SE FT
## 110 109 2021 EN FT
## 111 110 2021 SE FT
## 112 111 2021 SE FT
## 113 112 2021 SE FT
## 114 113 2021 EN PT
## 115 114 2021 MI FT
## 116 115 2021 EN FT
## 117 116 2021 MI FT
## 118 117 2021 MI FT
## 119 118 2021 EN FT
## 120 119 2021 MI FT
## 121 120 2021 MI FT
## 122 121 2021 SE FT
## 123 122 2021 EN FT
## 124 123 2021 EN FT
## 125 124 2021 EN PT
## 126 125 2021 MI FT
## 127 126 2021 SE FT
## 128 127 2021 MI FT
## 129 128 2021 EN FT
## 130 129 2021 SE FT
## 131 130 2021 EN FT
## 132 131 2021 EN FT
## 133 132 2021 MI FT
## 134 133 2021 SE FT
## 135 134 2021 EN FT
## 136 135 2021 MI FT
## 137 136 2021 MI FT
## 138 137 2021 MI FT
## 139 138 2021 SE FT
## 140 139 2021 EN FT
## 141 140 2021 MI FT
## 142 141 2021 SE FT
## 143 142 2021 SE FT
## 144 143 2021 MI FT
## 145 144 2021 MI FT
## 146 145 2021 SE FT
## 147 146 2021 MI FT
## 148 147 2021 MI FT
## 149 148 2021 SE FT
## 150 149 2021 SE FT
## 151 150 2021 SE FT
## 152 151 2021 MI FT
## 153 152 2021 MI FT
## 154 153 2021 EN FT
## 155 154 2021 SE FT
## 156 155 2021 SE FT
## 157 156 2021 MI FT
## 158 157 2021 MI FT
## 159 158 2021 SE FT
## 160 159 2021 EN FT
## 161 160 2021 EX FT
## 162 161 2021 EX FT
## 163 162 2021 MI FT
## 164 163 2021 EN FT
## 165 164 2021 EX FT
## 166 165 2021 SE FT
## 167 166 2021 EN FT
## 168 167 2021 EX FT
## 169 168 2021 EN FT
## 170 169 2021 MI FT
## 171 170 2021 MI FT
## 172 171 2021 MI FT
## 173 172 2021 EN FT
## 174 173 2021 SE FT
## 175 174 2021 SE FT
## 176 175 2021 SE FT
## 177 176 2021 MI FT
## 178 177 2021 MI FT
## 179 178 2021 EN FT
## 180 179 2021 MI FT
## 181 180 2021 MI FT
## 182 181 2021 MI FT
## 183 182 2021 MI FT
## 184 183 2021 SE FT
## 185 184 2021 MI FL
## 186 185 2021 MI FT
## 187 186 2021 SE FT
## 188 187 2021 EX FT
## 189 188 2021 SE FT
## 190 189 2021 MI FT
## 191 190 2021 SE FT
## 192 191 2021 EN FT
## 193 192 2021 MI FT
## 194 193 2021 SE FT
## 195 194 2021 SE FT
## 196 195 2021 MI FT
## 197 196 2021 EN FT
## 198 197 2021 SE FT
## 199 198 2021 SE FT
## 200 199 2021 EN FT
## 201 200 2021 MI FT
## 202 201 2021 SE FT
## 203 202 2021 MI FT
## 204 203 2021 SE FT
## 205 204 2021 MI FT
## 206 205 2021 MI FT
## 207 206 2021 SE FT
## 208 207 2021 SE FT
## 209 208 2021 MI FL
## 210 209 2021 SE FT
## 211 210 2021 MI FT
## 212 211 2021 MI FT
## 213 212 2021 MI FT
## 214 213 2021 EN FT
## 215 214 2021 EN FT
## 216 215 2021 SE FT
## 217 216 2021 EN PT
## 218 217 2021 MI FT
## 219 218 2021 MI FT
## 220 219 2021 SE FT
## 221 220 2021 MI FT
## 222 221 2021 MI FT
## 223 222 2021 MI FT
## 224 223 2021 MI FT
## 225 224 2021 SE FT
## 226 225 2021 EX CT
## 227 226 2021 SE FT
## 228 227 2021 MI FT
## 229 228 2021 SE FT
## 230 229 2021 SE FT
## 231 230 2021 EN FT
## 232 231 2021 SE FT
## 233 232 2021 SE FT
## 234 233 2021 SE FT
## 235 234 2021 MI FT
## 236 235 2021 MI FT
## 237 236 2021 MI FT
## 238 237 2021 MI FT
## 239 238 2021 EN FT
## 240 239 2021 EN FT
## 241 240 2021 SE FT
## 242 241 2021 MI FT
## 243 242 2021 MI FT
## 244 243 2021 SE FT
## 245 244 2021 EN FT
## 246 245 2021 MI FT
## 247 246 2021 EN FT
## 248 247 2021 MI FT
## 249 248 2021 SE FT
## 250 249 2021 SE FT
## 251 250 2021 MI FT
## 252 251 2021 EN FT
## 253 252 2021 EX FT
## 254 253 2021 EN FT
## 255 254 2021 MI FT
## 256 255 2021 SE FT
## 257 256 2021 MI FT
## 258 257 2021 SE FT
## 259 258 2021 SE FT
## 260 259 2021 EX FT
## 261 260 2021 MI FT
## 262 261 2021 SE FT
## 263 262 2021 MI FT
## 264 263 2021 SE FT
## 265 264 2021 MI FT
## 266 265 2021 SE FT
## 267 266 2021 MI FT
## 268 267 2021 MI FT
## 269 268 2021 MI FT
## 270 269 2021 EN FT
## 271 270 2021 EN FT
## 272 271 2021 SE FT
## 273 272 2021 EN FT
## 274 273 2021 EN FT
## 275 274 2021 SE FT
## 276 275 2021 EN FT
## 277 276 2021 EN FT
## 278 277 2021 SE FT
## 279 278 2021 SE FT
## 280 279 2021 EN FT
## 281 280 2021 MI FT
## 282 281 2021 EN FT
## 283 282 2021 MI PT
## 284 283 2021 SE CT
## 285 284 2021 MI FT
## 286 285 2021 SE FT
## 287 286 2021 SE FT
## 288 287 2021 MI FT
## 289 288 2021 MI FT
## 290 289 2022 SE FT
## 291 290 2022 SE FT
## 292 291 2022 SE FT
## 293 292 2022 MI FT
## 294 293 2022 MI FT
## 295 294 2022 MI FT
## 296 295 2022 MI FT
## 297 296 2022 SE FT
## 298 297 2022 SE FT
## 299 298 2022 SE FT
## 300 299 2022 SE FT
## 301 300 2022 SE FT
## 302 301 2022 SE FT
## 303 302 2022 SE FT
## 304 303 2022 SE FT
## 305 304 2022 EN FT
## 306 305 2022 SE FT
## 307 306 2022 SE FT
## 308 307 2022 MI FT
## 309 308 2022 MI FT
## 310 309 2022 EX FT
## 311 310 2022 EX FT
## 312 311 2022 MI FT
## 313 312 2022 MI FT
## 314 313 2022 MI FT
## 315 314 2022 MI FT
## 316 315 2022 SE FT
## 317 316 2022 EN FT
## 318 317 2022 SE FT
## 319 318 2022 SE FT
## 320 319 2022 SE FT
## 321 320 2022 SE FT
## 322 321 2022 SE FT
## 323 322 2022 SE FT
## 324 323 2022 SE FT
## 325 324 2022 SE FT
## 326 325 2022 SE FT
## 327 326 2022 EX FT
## 328 327 2022 EX FT
## 329 328 2022 SE FT
## 330 329 2022 MI FT
## 331 330 2022 SE FT
## 332 331 2022 SE FT
## 333 332 2022 SE FT
## 334 333 2022 SE FT
## 335 334 2022 SE FT
## 336 335 2022 SE FT
## 337 336 2022 MI FT
## 338 337 2022 SE FT
## 339 338 2022 SE FT
## 340 339 2022 SE FT
## 341 340 2022 SE FT
## 342 341 2022 SE FT
## 343 342 2022 EX FT
## 344 343 2022 EX FT
## 345 344 2022 EX FT
## 346 345 2022 SE FT
## 347 346 2022 SE FT
## 348 347 2022 SE FT
## 349 348 2022 SE FT
## 350 349 2022 SE FT
## 351 350 2022 SE FT
## 352 351 2022 SE FT
## 353 352 2022 SE FT
## 354 353 2022 SE FT
## 355 354 2022 SE FT
## 356 355 2022 SE FT
## 357 356 2022 SE FT
## 358 357 2022 SE FT
## 359 358 2022 SE FT
## 360 359 2022 SE FT
## 361 360 2022 SE FT
## 362 361 2022 SE FT
## 363 362 2022 SE FT
## 364 363 2022 SE FT
## 365 364 2022 SE FT
## 366 365 2022 SE FT
## 367 366 2022 SE FT
## 368 367 2022 MI FT
## 369 368 2022 EX FT
## 370 369 2022 SE FT
## 371 370 2022 SE FT
## 372 371 2022 SE FT
## 373 372 2022 SE FT
## 374 373 2022 MI FT
## 375 374 2022 MI FT
## 376 375 2022 EX FT
## 377 376 2022 SE FT
## 378 377 2022 SE FT
## 379 378 2022 SE FT
## 380 379 2022 SE FT
## 381 380 2022 SE FT
## 382 381 2022 SE FT
## 383 382 2022 SE FT
## 384 383 2022 SE FT
## 385 384 2022 EX FT
## 386 385 2022 SE FT
## 387 386 2022 EN FT
## 388 387 2022 SE FT
## 389 388 2022 SE FT
## 390 389 2022 MI FT
## 391 390 2022 MI FT
## 392 391 2022 MI FT
## 393 392 2022 SE FT
## 394 393 2022 SE FT
## 395 394 2022 SE FT
## 396 395 2022 SE FT
## 397 396 2022 MI FT
## 398 397 2022 MI FT
## 399 398 2022 SE FT
## 400 399 2022 SE FT
## 401 400 2022 SE FT
## 402 401 2022 SE FT
## 403 402 2022 SE FT
## 404 403 2022 SE FT
## 405 404 2022 SE FT
## 406 405 2022 MI FT
## 407 406 2022 MI FT
## 408 407 2022 SE FT
## 409 408 2022 MI FT
## 410 409 2022 SE FT
## 411 410 2022 MI FT
## 412 411 2022 MI FT
## 413 412 2022 MI FT
## 414 413 2022 MI FT
## 415 414 2022 MI FT
## 416 415 2022 MI FT
## 417 416 2022 SE FT
## 418 417 2022 SE FT
## 419 418 2022 MI FT
## 420 419 2022 MI FT
## 421 420 2022 MI FT
## 422 421 2022 MI FT
## 423 422 2022 MI FT
## 424 423 2022 SE FT
## 425 424 2022 SE FT
## 426 425 2022 MI FT
## 427 426 2022 SE FT
## 428 427 2022 MI FT
## 429 428 2022 SE FT
## 430 429 2022 MI FT
## 431 430 2022 MI FT
## 432 431 2022 MI FT
## 433 432 2022 MI FT
## 434 433 2022 MI FT
## 435 434 2022 MI FT
## 436 435 2022 MI FT
## 437 436 2022 MI FT
## 438 437 2022 MI FT
## 439 438 2022 SE FT
## 440 439 2022 SE FT
## 441 440 2022 MI FT
## 442 441 2022 MI FT
## 443 442 2022 MI FT
## 444 443 2022 MI FT
## 445 444 2022 SE FT
## 446 445 2022 MI FT
## 447 446 2022 SE FT
## 448 447 2022 SE FT
## 449 448 2022 SE FT
## 450 449 2022 EN FT
## 451 450 2022 SE FT
## 452 451 2022 MI FT
## 453 452 2022 EX FT
## 454 453 2022 MI FT
## 455 454 2022 EN FT
## 456 455 2022 MI FT
## 457 456 2022 SE FT
## 458 457 2022 SE FT
## 459 458 2022 MI FT
## 460 459 2022 MI FT
## 461 460 2022 MI FT
## 462 461 2022 EN FT
## 463 462 2022 MI PT
## 464 463 2022 EN FT
## 465 464 2022 SE FT
## 466 465 2022 EN FT
## 467 466 2022 SE FT
## 468 467 2022 SE FT
## 469 468 2022 SE FT
## 470 469 2022 SE FT
## 471 470 2022 MI FT
## 472 471 2022 MI FT
## 473 472 2022 SE FT
## 474 473 2022 SE FT
## 475 474 2022 MI FT
## 476 475 2022 MI FT
## 477 476 2022 SE FT
## 478 477 2022 SE FT
## 479 478 2022 MI FT
## 480 479 2022 MI FT
## 481 480 2022 SE FT
## 482 481 2022 SE FT
## 483 482 2022 EX FT
## 484 483 2022 EX FT
## 485 484 2022 SE FT
## 486 485 2022 SE FT
## 487 486 2022 SE FT
## 488 487 2022 EN PT
## 489 488 2022 MI FL
## 490 489 2022 EN CT
## 491 490 2022 SE FT
## 492 491 2022 MI FT
## 493 492 2022 MI FT
## 494 493 2022 SE FT
## 495 494 2022 SE FT
## 496 495 2022 MI FT
## 497 496 2022 EN FT
## 498 497 2022 SE FT
## 499 498 2022 SE FT
## 500 499 2022 EN FT
## job_title salary salary_currency
## 1 Data Scientist 70000 EUR
## 2 Machine Learning Scientist 260000 USD
## 3 Big Data Engineer 85000 GBP
## 4 Product Data Analyst 20000 USD
## 5 Machine Learning Engineer 150000 USD
## 6 Data Analyst 72000 USD
## 7 Lead Data Scientist 190000 USD
## 8 Data Scientist 11000000 HUF
## 9 Business Data Analyst 135000 USD
## 10 Lead Data Engineer 125000 USD
## 11 Data Scientist 45000 EUR
## 12 Data Scientist 3000000 INR
## 13 Data Scientist 35000 EUR
## 14 Lead Data Analyst 87000 USD
## 15 Data Analyst 85000 USD
## 16 Data Analyst 8000 USD
## 17 Data Engineer 4450000 JPY
## 18 Big Data Engineer 100000 EUR
## 19 Data Science Consultant 423000 INR
## 20 Lead Data Engineer 56000 USD
## 21 Machine Learning Engineer 299000 CNY
## 22 Product Data Analyst 450000 INR
## 23 Data Engineer 42000 EUR
## 24 BI Data Analyst 98000 USD
## 25 Lead Data Scientist 115000 USD
## 26 Director of Data Science 325000 USD
## 27 Research Scientist 42000 USD
## 28 Data Engineer 720000 MXN
## 29 Business Data Analyst 100000 USD
## 30 Machine Learning Manager 157000 CAD
## 31 Data Engineering Manager 51999 EUR
## 32 Big Data Engineer 70000 USD
## 33 Data Scientist 60000 EUR
## 34 Research Scientist 450000 USD
## 35 Data Analyst 41000 EUR
## 36 Data Engineer 65000 EUR
## 37 Data Science Consultant 103000 USD
## 38 Machine Learning Engineer 250000 USD
## 39 Data Analyst 10000 USD
## 40 Machine Learning Engineer 138000 USD
## 41 Data Scientist 45760 USD
## 42 Data Engineering Manager 70000 EUR
## 43 Machine Learning Infrastructure Engineer 44000 EUR
## 44 Data Engineer 106000 USD
## 45 Data Engineer 88000 GBP
## 46 ML Engineer 14000 EUR
## 47 Data Scientist 60000 GBP
## 48 Data Engineer 188000 USD
## 49 Data Scientist 105000 USD
## 50 Data Engineer 61500 EUR
## 51 Data Analyst 450000 INR
## 52 Data Analyst 91000 USD
## 53 AI Scientist 300000 DKK
## 54 Data Engineer 48000 EUR
## 55 Computer Vision Engineer 60000 USD
## 56 Principal Data Scientist 130000 EUR
## 57 Data Scientist 34000 EUR
## 58 Data Scientist 118000 USD
## 59 Data Scientist 120000 USD
## 60 Data Scientist 138350 USD
## 61 Data Engineer 110000 USD
## 62 Data Engineer 130800 USD
## 63 Data Scientist 19000 EUR
## 64 Data Scientist 412000 USD
## 65 Machine Learning Engineer 40000 EUR
## 66 Data Scientist 55000 EUR
## 67 Data Scientist 43200 EUR
## 68 Data Science Manager 190200 USD
## 69 Data Scientist 105000 USD
## 70 Data Scientist 80000 EUR
## 71 Data Scientist 55000 EUR
## 72 Data Scientist 37000 EUR
## 73 Research Scientist 60000 GBP
## 74 BI Data Analyst 150000 USD
## 75 Head of Data 235000 USD
## 76 Data Scientist 45000 EUR
## 77 BI Data Analyst 100000 USD
## 78 3D Computer Vision Researcher 400000 INR
## 79 ML Engineer 270000 USD
## 80 Data Analyst 80000 USD
## 81 Data Analytics Engineer 67000 EUR
## 82 Data Engineer 140000 USD
## 83 Applied Data Scientist 68000 CAD
## 84 Machine Learning Engineer 40000 EUR
## 85 Director of Data Science 130000 EUR
## 86 Data Engineer 110000 PLN
## 87 Data Analyst 50000 EUR
## 88 Data Analytics Engineer 110000 USD
## 89 Lead Data Analyst 170000 USD
## 90 Data Analyst 80000 USD
## 91 Marketing Data Analyst 75000 EUR
## 92 Data Science Consultant 65000 EUR
## 93 Lead Data Analyst 1450000 INR
## 94 Lead Data Engineer 276000 USD
## 95 Data Scientist 2200000 INR
## 96 Cloud Data Engineer 120000 SGD
## 97 AI Scientist 12000 USD
## 98 Financial Data Analyst 450000 USD
## 99 Computer Vision Software Engineer 70000 USD
## 100 Computer Vision Software Engineer 81000 EUR
## 101 Data Analyst 75000 USD
## 102 Data Engineer 150000 USD
## 103 BI Data Analyst 11000000 HUF
## 104 Data Analyst 62000 USD
## 105 Data Scientist 73000 USD
## 106 Data Analyst 37456 GBP
## 107 Research Scientist 235000 CAD
## 108 Data Engineer 115000 USD
## 109 Data Engineer 150000 USD
## 110 Data Engineer 2250000 INR
## 111 Machine Learning Engineer 80000 EUR
## 112 Director of Data Engineering 82500 GBP
## 113 Lead Data Engineer 75000 GBP
## 114 AI Scientist 12000 USD
## 115 Data Engineer 38400 EUR
## 116 Machine Learning Scientist 225000 USD
## 117 Data Scientist 50000 USD
## 118 Data Science Engineer 34000 EUR
## 119 Data Analyst 90000 USD
## 120 Data Engineer 200000 USD
## 121 Big Data Engineer 60000 USD
## 122 Principal Data Engineer 200000 USD
## 123 Data Analyst 50000 USD
## 124 Applied Data Scientist 80000 GBP
## 125 Data Analyst 8760 EUR
## 126 Principal Data Scientist 151000 USD
## 127 Machine Learning Scientist 120000 USD
## 128 Data Scientist 700000 INR
## 129 Machine Learning Engineer 20000 USD
## 130 Lead Data Scientist 3000000 INR
## 131 Machine Learning Developer 100000 USD
## 132 Data Scientist 42000 EUR
## 133 Applied Machine Learning Scientist 38400 USD
## 134 Computer Vision Engineer 24000 USD
## 135 Data Scientist 100000 USD
## 136 Data Analyst 90000 USD
## 137 ML Engineer 7000000 JPY
## 138 ML Engineer 8500000 JPY
## 139 Principal Data Scientist 220000 USD
## 140 Data Scientist 80000 USD
## 141 Data Analyst 135000 USD
## 142 Data Science Manager 240000 USD
## 143 Data Engineering Manager 150000 USD
## 144 Data Scientist 82500 USD
## 145 Data Engineer 100000 USD
## 146 Machine Learning Engineer 70000 EUR
## 147 Research Scientist 53000 EUR
## 148 Data Engineer 90000 USD
## 149 Data Engineering Manager 153000 USD
## 150 Cloud Data Engineer 160000 USD
## 151 Director of Data Science 168000 USD
## 152 Data Scientist 150000 USD
## 153 Data Scientist 95000 CAD
## 154 Data Scientist 13400 USD
## 155 Data Science Manager 144000 USD
## 156 Data Science Engineer 159500 CAD
## 157 Data Scientist 160000 SGD
## 158 Applied Machine Learning Scientist 423000 USD
## 159 Data Analytics Manager 120000 USD
## 160 Machine Learning Engineer 125000 USD
## 161 Head of Data 230000 USD
## 162 Head of Data Science 85000 USD
## 163 Data Engineer 24000 EUR
## 164 Data Science Consultant 54000 EUR
## 165 Director of Data Science 110000 EUR
## 166 Data Specialist 165000 USD
## 167 Data Engineer 80000 USD
## 168 Director of Data Science 250000 USD
## 169 BI Data Analyst 55000 USD
## 170 Data Architect 150000 USD
## 171 Data Architect 170000 USD
## 172 Data Engineer 60000 GBP
## 173 Data Analyst 60000 USD
## 174 Principal Data Scientist 235000 USD
## 175 Research Scientist 51400 EUR
## 176 Data Engineering Manager 174000 USD
## 177 Data Scientist 58000 MXN
## 178 Data Scientist 30400000 CLP
## 179 Machine Learning Engineer 81000 USD
## 180 Data Scientist 420000 INR
## 181 Big Data Engineer 1672000 INR
## 182 Data Scientist 76760 EUR
## 183 Data Engineer 22000 EUR
## 184 Finance Data Analyst 45000 GBP
## 185 Machine Learning Scientist 12000 USD
## 186 Data Engineer 4000 USD
## 187 Data Analytics Engineer 50000 USD
## 188 Data Science Consultant 59000 EUR
## 189 Data Engineer 65000 EUR
## 190 Machine Learning Engineer 74000 USD
## 191 Data Science Manager 152000 USD
## 192 Machine Learning Engineer 21844 USD
## 193 Big Data Engineer 18000 USD
## 194 Data Science Manager 174000 USD
## 195 Research Scientist 120500 CAD
## 196 Data Scientist 147000 USD
## 197 BI Data Analyst 9272 USD
## 198 Machine Learning Engineer 1799997 INR
## 199 Data Science Manager 4000000 INR
## 200 Data Science Consultant 90000 USD
## 201 Data Scientist 52000 EUR
## 202 Machine Learning Infrastructure Engineer 195000 USD
## 203 Data Scientist 32000 EUR
## 204 Research Scientist 50000 USD
## 205 Data Scientist 160000 USD
## 206 Data Scientist 69600 BRL
## 207 Machine Learning Engineer 200000 USD
## 208 Data Engineer 165000 USD
## 209 Data Engineer 20000 USD
## 210 Data Analytics Manager 120000 USD
## 211 Machine Learning Engineer 21000 EUR
## 212 Research Scientist 48000 EUR
## 213 Data Engineer 48000 GBP
## 214 Big Data Engineer 435000 INR
## 215 Machine Learning Engineer 21000 EUR
## 216 Principal Data Engineer 185000 USD
## 217 Computer Vision Engineer 180000 DKK
## 218 Data Scientist 76760 EUR
## 219 Machine Learning Engineer 75000 EUR
## 220 Data Analytics Manager 140000 USD
## 221 Machine Learning Engineer 180000 PLN
## 222 Data Scientist 85000 GBP
## 223 Data Scientist 2500000 INR
## 224 Data Scientist 40900 GBP
## 225 Machine Learning Scientist 225000 USD
## 226 Principal Data Scientist 416000 USD
## 227 Data Scientist 110000 CAD
## 228 Data Scientist 75000 EUR
## 229 Data Scientist 135000 USD
## 230 Data Analyst 90000 CAD
## 231 Big Data Engineer 1200000 INR
## 232 ML Engineer 256000 USD
## 233 Director of Data Engineering 200000 USD
## 234 Data Analyst 200000 USD
## 235 Data Architect 180000 USD
## 236 Head of Data Science 110000 USD
## 237 Research Scientist 80000 CAD
## 238 Data Scientist 39600 EUR
## 239 Data Scientist 4000 USD
## 240 Data Engineer 1600000 INR
## 241 Data Scientist 130000 CAD
## 242 Data Analyst 80000 USD
## 243 Data Engineer 110000 USD
## 244 Data Scientist 165000 USD
## 245 AI Scientist 1335000 INR
## 246 Data Engineer 52500 GBP
## 247 Data Scientist 31000 EUR
## 248 Data Engineer 108000 TRY
## 249 Data Engineer 70000 GBP
## 250 Principal Data Analyst 170000 USD
## 251 Data Scientist 115000 USD
## 252 Data Scientist 90000 USD
## 253 Principal Data Engineer 600000 USD
## 254 Data Scientist 2100000 INR
## 255 Data Analyst 93000 USD
## 256 Big Data Architect 125000 CAD
## 257 Data Engineer 200000 USD
## 258 Principal Data Scientist 147000 EUR
## 259 Machine Learning Engineer 185000 USD
## 260 Director of Data Science 120000 EUR
## 261 Data Scientist 130000 USD
## 262 Data Analyst 54000 EUR
## 263 Data Scientist 1250000 INR
## 264 Machine Learning Engineer 4900000 INR
## 265 Data Scientist 21600 EUR
## 266 Lead Data Engineer 160000 USD
## 267 Data Engineer 93150 USD
## 268 Data Engineer 111775 USD
## 269 Data Engineer 250000 TRY
## 270 Data Engineer 55000 EUR
## 271 Data Engineer 72500 USD
## 272 Computer Vision Engineer 102000 BRL
## 273 Data Science Consultant 65000 EUR
## 274 Machine Learning Engineer 85000 USD
## 275 Data Scientist 65720 EUR
## 276 Data Scientist 100000 USD
## 277 Data Scientist 58000 USD
## 278 AI Scientist 55000 USD
## 279 Data Scientist 180000 TRY
## 280 Business Data Analyst 50000 EUR
## 281 Data Engineer 112000 USD
## 282 Research Scientist 100000 USD
## 283 Data Engineer 59000 EUR
## 284 Staff Data Scientist 105000 USD
## 285 Research Scientist 69999 USD
## 286 Data Science Manager 7000000 INR
## 287 Head of Data 87000 EUR
## 288 Data Scientist 109000 USD
## 289 Machine Learning Engineer 43200 EUR
## 290 Data Engineer 135000 USD
## 291 Data Analyst 155000 USD
## 292 Data Analyst 120600 USD
## 293 Data Scientist 130000 USD
## 294 Data Scientist 90000 USD
## 295 Data Engineer 170000 USD
## 296 Data Engineer 150000 USD
## 297 Data Analyst 102100 USD
## 298 Data Analyst 84900 USD
## 299 Data Scientist 136620 USD
## 300 Data Scientist 99360 USD
## 301 Data Scientist 90000 GBP
## 302 Data Scientist 80000 GBP
## 303 Data Scientist 146000 USD
## 304 Data Scientist 123000 USD
## 305 Data Engineer 40000 GBP
## 306 Data Analyst 99000 USD
## 307 Data Analyst 116000 USD
## 308 Data Analyst 106260 USD
## 309 Data Analyst 126500 USD
## 310 Data Engineer 242000 USD
## 311 Data Engineer 200000 USD
## 312 Data Scientist 50000 GBP
## 313 Data Scientist 30000 GBP
## 314 Data Engineer 60000 GBP
## 315 Data Engineer 40000 GBP
## 316 Data Scientist 165220 USD
## 317 Data Engineer 35000 GBP
## 318 Data Scientist 120160 USD
## 319 Data Analyst 90320 USD
## 320 Data Engineer 181940 USD
## 321 Data Engineer 132320 USD
## 322 Data Engineer 220110 USD
## 323 Data Engineer 160080 USD
## 324 Data Scientist 180000 USD
## 325 Data Scientist 120000 USD
## 326 Data Analyst 124190 USD
## 327 Data Analyst 130000 USD
## 328 Data Analyst 110000 USD
## 329 Data Analyst 170000 USD
## 330 Data Analyst 115500 USD
## 331 Data Analyst 112900 USD
## 332 Data Analyst 90320 USD
## 333 Data Analyst 112900 USD
## 334 Data Analyst 90320 USD
## 335 Data Engineer 165400 USD
## 336 Data Engineer 132320 USD
## 337 Data Analyst 167000 USD
## 338 Data Engineer 243900 USD
## 339 Data Analyst 136600 USD
## 340 Data Analyst 109280 USD
## 341 Data Engineer 128875 USD
## 342 Data Engineer 93700 USD
## 343 Head of Data Science 224000 USD
## 344 Head of Data Science 167875 USD
## 345 Analytics Engineer 175000 USD
## 346 Data Engineer 156600 USD
## 347 Data Engineer 108800 USD
## 348 Data Scientist 95550 USD
## 349 Data Engineer 113000 USD
## 350 Data Analyst 135000 USD
## 351 Data Science Manager 161342 USD
## 352 Data Science Manager 137141 USD
## 353 Data Scientist 167000 USD
## 354 Data Scientist 123000 USD
## 355 Data Engineer 60000 GBP
## 356 Data Engineer 50000 GBP
## 357 Data Scientist 150000 USD
## 358 Data Scientist 211500 USD
## 359 Data Architect 192400 USD
## 360 Data Architect 90700 USD
## 361 Data Analyst 130000 USD
## 362 Data Analyst 61300 USD
## 363 Data Analyst 130000 USD
## 364 Data Analyst 61300 USD
## 365 Data Engineer 160000 USD
## 366 Data Scientist 138600 USD
## 367 Data Engineer 136000 USD
## 368 Data Analyst 58000 USD
## 369 Analytics Engineer 135000 USD
## 370 Data Scientist 170000 USD
## 371 Data Scientist 123000 USD
## 372 Machine Learning Engineer 189650 USD
## 373 Machine Learning Engineer 164996 USD
## 374 ETL Developer 50000 EUR
## 375 ETL Developer 50000 EUR
## 376 Lead Data Engineer 150000 CAD
## 377 Data Analyst 132000 USD
## 378 Data Engineer 165400 USD
## 379 Data Architect 208775 USD
## 380 Data Architect 147800 USD
## 381 Data Engineer 136994 USD
## 382 Data Engineer 101570 USD
## 383 Data Analyst 128875 USD
## 384 Data Analyst 93700 USD
## 385 Head of Machine Learning 6000000 INR
## 386 Data Engineer 132320 USD
## 387 Machine Learning Engineer 28500 GBP
## 388 Data Analyst 164000 USD
## 389 Data Engineer 155000 USD
## 390 Machine Learning Engineer 95000 GBP
## 391 Machine Learning Engineer 75000 GBP
## 392 AI Scientist 120000 USD
## 393 Data Analyst 112900 USD
## 394 Data Analyst 90320 USD
## 395 Data Analytics Manager 145000 USD
## 396 Data Analytics Manager 105400 USD
## 397 Machine Learning Engineer 80000 EUR
## 398 Data Engineer 90000 GBP
## 399 Data Scientist 215300 USD
## 400 Data Scientist 158200 USD
## 401 Data Engineer 209100 USD
## 402 Data Engineer 154600 USD
## 403 Data Analyst 115934 USD
## 404 Data Analyst 81666 USD
## 405 Data Engineer 175000 USD
## 406 Data Engineer 75000 GBP
## 407 Data Analyst 58000 USD
## 408 Data Engineer 183600 USD
## 409 Data Analyst 40000 GBP
## 410 Data Scientist 180000 USD
## 411 Data Scientist 55000 GBP
## 412 Data Scientist 35000 GBP
## 413 Data Engineer 60000 EUR
## 414 Data Engineer 45000 EUR
## 415 Data Engineer 60000 GBP
## 416 Data Engineer 45000 GBP
## 417 Data Scientist 260000 USD
## 418 Data Science Engineer 60000 USD
## 419 Data Engineer 63900 USD
## 420 Machine Learning Scientist 160000 USD
## 421 Machine Learning Scientist 112300 USD
## 422 Data Science Manager 241000 USD
## 423 Data Science Manager 159000 USD
## 424 Data Scientist 180000 USD
## 425 Data Scientist 80000 USD
## 426 Data Engineer 82900 USD
## 427 Data Engineer 100800 USD
## 428 Data Engineer 45000 EUR
## 429 Data Scientist 140400 USD
## 430 Data Analyst 30000 GBP
## 431 Data Analyst 40000 EUR
## 432 Data Analyst 30000 EUR
## 433 Data Engineer 80000 EUR
## 434 Data Engineer 70000 EUR
## 435 Data Engineer 80000 GBP
## 436 Data Engineer 70000 GBP
## 437 Data Engineer 60000 EUR
## 438 Data Engineer 80000 EUR
## 439 Machine Learning Engineer 189650 USD
## 440 Machine Learning Engineer 164996 USD
## 441 Data Analyst 40000 EUR
## 442 Data Analyst 30000 EUR
## 443 Data Engineer 75000 GBP
## 444 Data Engineer 60000 GBP
## 445 Data Scientist 215300 USD
## 446 Data Engineer 70000 EUR
## 447 Data Engineer 209100 USD
## 448 Data Engineer 154600 USD
## 449 Data Engineer 180000 USD
## 450 ML Engineer 20000 EUR
## 451 Data Engineer 80000 USD
## 452 Machine Learning Developer 100000 CAD
## 453 Director of Data Science 250000 CAD
## 454 Machine Learning Engineer 120000 USD
## 455 Computer Vision Engineer 125000 USD
## 456 NLP Engineer 240000 CNY
## 457 Data Engineer 105000 USD
## 458 Lead Machine Learning Engineer 80000 EUR
## 459 Business Data Analyst 1400000 INR
## 460 Data Scientist 2400000 INR
## 461 Machine Learning Infrastructure Engineer 53000 EUR
## 462 Financial Data Analyst 100000 USD
## 463 Data Engineer 50000 EUR
## 464 Data Scientist 1400000 INR
## 465 Principal Data Scientist 148000 EUR
## 466 Data Engineer 120000 USD
## 467 Research Scientist 144000 USD
## 468 Data Scientist 104890 USD
## 469 Data Engineer 100000 USD
## 470 Data Scientist 140000 USD
## 471 Data Analyst 135000 USD
## 472 Data Analyst 50000 USD
## 473 Data Scientist 220000 USD
## 474 Data Scientist 140000 USD
## 475 Data Scientist 140000 GBP
## 476 Data Scientist 70000 GBP
## 477 Data Scientist 185100 USD
## 478 Machine Learning Engineer 220000 USD
## 479 Data Scientist 200000 USD
## 480 Data Scientist 120000 USD
## 481 Machine Learning Engineer 120000 USD
## 482 Machine Learning Engineer 65000 USD
## 483 Data Engineer 324000 USD
## 484 Data Engineer 216000 USD
## 485 Data Engineer 210000 USD
## 486 Machine Learning Engineer 120000 USD
## 487 Data Scientist 230000 USD
## 488 Data Scientist 100000 USD
## 489 Data Scientist 100000 USD
## 490 Applied Machine Learning Scientist 29000 EUR
## 491 Head of Data 200000 USD
## 492 Principal Data Analyst 75000 USD
## 493 Data Scientist 150000 PLN
## 494 Machine Learning Developer 100000 CAD
## 495 Data Scientist 100000 USD
## 496 Machine Learning Scientist 153000 USD
## 497 Data Engineer 52800 EUR
## 498 Data Scientist 165000 USD
## 499 Research Scientist 85000 EUR
## 500 Data Scientist 66500 CAD
## salary_in_usd employee_residence remote_ratio company_location company_size
## 1 79833 DE 0 DE L
## 2 260000 JP 0 JP S
## 3 109024 GB 50 GB M
## 4 20000 HN 0 HN S
## 5 150000 US 50 US L
## 6 72000 US 100 US L
## 7 190000 US 100 US S
## 8 35735 HU 50 HU L
## 9 135000 US 100 US L
## 10 125000 NZ 50 NZ S
## 11 51321 FR 0 FR S
## 12 40481 IN 0 IN L
## 13 39916 FR 0 FR M
## 14 87000 US 100 US L
## 15 85000 US 100 US L
## 16 8000 PK 50 PK L
## 17 41689 JP 100 JP S
## 18 114047 PL 100 GB S
## 19 5707 IN 50 IN M
## 20 56000 PT 100 US M
## 21 43331 CN 0 CN M
## 22 6072 IN 100 IN L
## 23 47899 GR 50 GR L
## 24 98000 US 0 US M
## 25 115000 AE 0 AE L
## 26 325000 US 100 US L
## 27 42000 NL 50 NL L
## 28 33511 MX 0 MX S
## 29 100000 US 100 US L
## 30 117104 CA 50 CA L
## 31 59303 DE 100 DE S
## 32 70000 US 100 US L
## 33 68428 GR 100 US L
## 34 450000 US 0 US M
## 35 46759 FR 50 FR L
## 36 74130 AT 50 AT L
## 37 103000 US 100 US L
## 38 250000 US 50 US L
## 39 10000 NG 100 NG S
## 40 138000 US 100 US S
## 41 45760 PH 100 US S
## 42 79833 ES 50 ES L
## 43 50180 PT 0 PT M
## 44 106000 US 100 US L
## 45 112872 GB 50 GB L
## 46 15966 DE 100 DE S
## 47 76958 GB 100 GB S
## 48 188000 US 100 US L
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## 50 70139 FR 50 FR L
## 51 6072 IN 0 IN S
## 52 91000 US 100 US L
## 53 45896 DK 50 DK S
## 54 54742 PK 100 DE L
## 55 60000 RU 100 US S
## 56 148261 DE 100 DE M
## 57 38776 ES 100 ES M
## 58 118000 US 100 US M
## 59 120000 US 50 US L
## 60 138350 US 100 US M
## 61 110000 US 100 US L
## 62 130800 ES 100 US M
## 63 21669 IT 50 IT S
## 64 412000 US 100 US L
## 65 45618 HR 100 HR S
## 66 62726 DE 50 DE S
## 67 49268 DE 0 DE S
## 68 190200 US 100 US M
## 69 105000 US 100 US S
## 70 91237 AT 0 AT S
## 71 62726 FR 50 LU S
## 72 42197 FR 50 FR S
## 73 82528 GB 50 GB L
## 74 150000 IN 100 US L
## 75 235000 US 100 US L
## 76 53192 FR 50 FR L
## 77 100000 US 100 US M
## 78 5409 IN 50 IN M
## 79 270000 US 100 US L
## 80 80000 US 100 US M
## 81 79197 DE 100 DE L
## 82 140000 US 100 US L
## 83 54238 GB 50 CA L
## 84 47282 ES 100 ES S
## 85 153667 IT 100 PL L
## 86 28476 PL 100 PL L
## 87 59102 FR 50 FR M
## 88 110000 US 100 US L
## 89 170000 US 100 US L
## 90 80000 BG 100 US S
## 91 88654 GR 100 DK L
## 92 76833 DE 100 DE S
## 93 19609 IN 100 IN L
## 94 276000 US 0 US L
## 95 29751 IN 50 IN L
## 96 89294 SG 50 SG L
## 97 12000 BR 100 US S
## 98 450000 US 100 US L
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## 100 95746 DE 100 US S
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## 106 51519 GB 50 GB L
## 107 187442 CA 100 CA L
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## 110 30428 IN 100 IN L
## 111 94564 DE 50 DE L
## 112 113476 GB 100 GB M
## 113 103160 GB 100 GB S
## 114 12000 PK 100 US M
## 115 45391 NL 100 NL L
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## 118 40189 GR 100 GR M
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## 120 200000 US 100 US L
## 121 60000 ES 50 RO M
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## 124 110037 GB 0 GB L
## 125 10354 ES 50 ES M
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## 163 28369 MT 50 MT L
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## 184 61896 GB 50 GB L
## 185 12000 PK 50 PK M
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## 187 50000 VN 100 GB M
## 188 69741 FR 100 ES S
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## 218 90734 DE 50 DE L
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## 221 46597 PL 100 PL L
## 222 116914 GB 50 GB L
## 223 33808 IN 0 IN M
## 224 56256 GB 50 GB L
## 225 225000 US 100 CA L
## 226 416000 US 100 US S
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## 245 18053 IN 100 AS S
## 246 72212 GB 50 GB L
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## 248 12103 TR 0 TR M
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## 250 170000 US 100 US M
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## 387 37300 GB 100 GB L
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## 415 78526 GB 100 GB M
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## 430 39263 GB 100 GB M
## 431 43966 ES 100 ES M
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## 435 104702 GB 100 GB M
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## 441 43966 GR 100 GR M
## 442 32974 GR 100 GR M
## 443 98158 GB 100 GB M
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## 461 58255 PT 50 PT L
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## 463 54957 DE 50 DE L
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## 474 140000 US 100 US M
## 475 183228 GB 0 GB M
## 476 91614 GB 0 GB M
## 477 185100 US 100 US M
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## 481 120000 AE 100 AE S
## 482 65000 AE 100 AE S
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## 486 120000 US 100 US M
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## 488 100000 DZ 50 DZ M
## 489 100000 CA 100 US M
## 490 31875 TN 100 CZ M
## 491 200000 MY 100 US M
## 492 75000 CA 100 CA S
## 493 35590 PL 100 PL L
## 494 78791 CA 100 CA M
## 495 100000 BR 100 US M
## 496 153000 US 50 US M
## 497 58035 PK 100 DE M
## 498 165000 US 100 US M
## 499 93427 FR 50 FR L
## 500 52396 CA 100 CA L#Dapatkan jumlah Kolom (feature) dan baris
n_col <- ncol(df)
n_row <- nrow(df)
cat("jumlah kolom : ", n_col, "\n")## jumlah kolom : 12cat("jumlah baris : ", n_row, "\n")## jumlah baris : 607colnames(df)## [1] "X" "work_year" "experience_level"
## [4] "employment_type" "job_title" "salary"
## [7] "salary_currency" "salary_in_usd" "employee_residence"
## [10] "remote_ratio" "company_location" "company_size"#pakai structure untuk report lbh detail
str(df)## 'data.frame': 607 obs. of 12 variables:
## $ X : int 0 1 2 3 4 5 6 7 8 9 ...
## $ work_year : int 2020 2020 2020 2020 2020 2020 2020 2020 2020 2020 ...
## $ experience_level : chr "MI" "SE" "SE" "MI" ...
## $ employment_type : chr "FT" "FT" "FT" "FT" ...
## $ job_title : chr "Data Scientist" "Machine Learning Scientist" "Big Data Engineer" "Product Data Analyst" ...
## $ salary : int 70000 260000 85000 20000 150000 72000 190000 11000000 135000 125000 ...
## $ salary_currency : chr "EUR" "USD" "GBP" "USD" ...
## $ salary_in_usd : int 79833 260000 109024 20000 150000 72000 190000 35735 135000 125000 ...
## $ employee_residence: chr "DE" "JP" "GB" "HN" ...
## $ remote_ratio : int 0 0 50 0 50 100 100 50 100 50 ...
## $ company_location : chr "DE" "JP" "GB" "HN" ...
## $ company_size : chr "L" "S" "M" "S" ...#check variabel numerical & variabel categorical
# oh ya pakai library physc untuk method str
library(psych)
numeric <- names(df)[sapply(df, is.numeric)]
categor <- names(df)[sapply(df, is.character)]
cat("numerical : ", numeric, "\n")## numerical : X work_year salary salary_in_usd remote_ratiocat("categorical : ", categor)## categorical : experience_level employment_type job_title salary_currency employee_residence company_location company_sizedescribe(df)## vars n mean sd median trimmed mad
## X 1 607 303.00 175.37 303 303.00 225.36
## work_year 2 607 2021.41 0.69 2022 2021.51 0.00
## experience_level* 3 607 3.13 1.03 3 3.28 1.48
## employment_type* 4 607 2.99 0.24 3 3.00 0.00
## job_title* 5 607 21.96 10.49 18 21.00 7.41
## salary 6 607 324000.06 1544357.49 115000 118919.11 68706.65
## salary_currency* 7 607 14.03 4.38 17 14.67 0.00
## salary_in_usd 8 607 112297.87 70957.26 101570 106157.63 62906.72
## employee_residence* 9 607 41.41 18.27 56 43.66 0.00
## remote_ratio 10 607 70.92 40.71 100 76.08 0.00
## company_location* 11 607 36.89 16.03 49 39.07 0.00
## company_size* 12 607 1.81 0.65 2 1.76 0.00
## min max range skew kurtosis se
## X 0 606 606 0.00 -1.21 7.12
## work_year 2020 2022 2 -0.73 -0.66 0.03
## experience_level* 1 4 3 -1.04 -0.10 0.04
## employment_type* 1 4 3 -4.14 45.81 0.01
## job_title* 1 50 49 0.88 0.40 0.43
## salary 4000 30400000 30396000 13.98 244.57 62683.54
## salary_currency* 1 17 16 -1.03 -0.38 0.18
## salary_in_usd 2859 600000 597141 1.66 6.26 2880.07
## employee_residence* 1 57 56 -0.67 -1.22 0.74
## remote_ratio 0 100 100 -0.90 -0.90 1.65
## company_location* 1 50 49 -0.77 -1.09 0.65
## company_size* 1 3 2 0.21 -0.73 0.03sum(is.na(df))## [1] 0n_na <- colSums(is.na(df))
n_na <- n_na/nrow(df) *100
cat(paste0(names(n_na), ":", round(n_na),"%\n"))## X:0%
## work_year:0%
## experience_level:0%
## employment_type:0%
## job_title:0%
## salary:0%
## salary_currency:0%
## salary_in_usd:0%
## employee_residence:0%
## remote_ratio:0%
## company_location:0%
## company_size:0%unique(df$experience_level)## [1] "MI" "SE" "EN" "EX"cat("\n")unique(df$employment_type)## [1] "FT" "CT" "PT" "FL"cat("\n")unique(df$job_title)## [1] "Data Scientist"
## [2] "Machine Learning Scientist"
## [3] "Big Data Engineer"
## [4] "Product Data Analyst"
## [5] "Machine Learning Engineer"
## [6] "Data Analyst"
## [7] "Lead Data Scientist"
## [8] "Business Data Analyst"
## [9] "Lead Data Engineer"
## [10] "Lead Data Analyst"
## [11] "Data Engineer"
## [12] "Data Science Consultant"
## [13] "BI Data Analyst"
## [14] "Director of Data Science"
## [15] "Research Scientist"
## [16] "Machine Learning Manager"
## [17] "Data Engineering Manager"
## [18] "Machine Learning Infrastructure Engineer"
## [19] "ML Engineer"
## [20] "AI Scientist"
## [21] "Computer Vision Engineer"
## [22] "Principal Data Scientist"
## [23] "Data Science Manager"
## [24] "Head of Data"
## [25] "3D Computer Vision Researcher"
## [26] "Data Analytics Engineer"
## [27] "Applied Data Scientist"
## [28] "Marketing Data Analyst"
## [29] "Cloud Data Engineer"
## [30] "Financial Data Analyst"
## [31] "Computer Vision Software Engineer"
## [32] "Director of Data Engineering"
## [33] "Data Science Engineer"
## [34] "Principal Data Engineer"
## [35] "Machine Learning Developer"
## [36] "Applied Machine Learning Scientist"
## [37] "Data Analytics Manager"
## [38] "Head of Data Science"
## [39] "Data Specialist"
## [40] "Data Architect"
## [41] "Finance Data Analyst"
## [42] "Principal Data Analyst"
## [43] "Big Data Architect"
## [44] "Staff Data Scientist"
## [45] "Analytics Engineer"
## [46] "ETL Developer"
## [47] "Head of Machine Learning"
## [48] "NLP Engineer"
## [49] "Lead Machine Learning Engineer"
## [50] "Data Analytics Lead"cat("\n")unique(df$salary_currency)## [1] "EUR" "USD" "GBP" "HUF" "INR" "JPY" "CNY" "MXN" "CAD" "DKK" "PLN" "SGD"
## [13] "CLP" "BRL" "TRY" "AUD" "CHF"cat("\n")unique(df$employee_residence)## [1] "DE" "JP" "GB" "HN" "US" "HU" "NZ" "FR" "IN" "PK" "PL" "PT" "CN" "GR" "AE"
## [16] "NL" "MX" "CA" "AT" "NG" "PH" "ES" "DK" "RU" "IT" "HR" "BG" "SG" "BR" "IQ"
## [31] "VN" "BE" "UA" "MT" "CL" "RO" "IR" "CO" "MD" "KE" "SI" "HK" "TR" "RS" "PR"
## [46] "LU" "JE" "CZ" "AR" "DZ" "TN" "MY" "EE" "AU" "BO" "IE" "CH"cat("\n")unique(df$company_location)## [1] "DE" "JP" "GB" "HN" "US" "HU" "NZ" "FR" "IN" "PK" "CN" "GR" "AE" "NL" "MX"
## [16] "CA" "AT" "NG" "ES" "PT" "DK" "IT" "HR" "LU" "PL" "SG" "RO" "IQ" "BR" "BE"
## [31] "UA" "IL" "RU" "MT" "CL" "IR" "CO" "MD" "KE" "SI" "CH" "VN" "AS" "TR" "CZ"
## [46] "DZ" "EE" "MY" "AU" "IE"cat("\n")unique(df$company_size)## [1] "L" "S" "M"cat("\n")// Tidak ada masalah dalam konsistensi penamaan data
# untuk menghitung jumlah data terduplikasi
sum(duplicated(df))## [1] 0# asumsi jika ada
new_df <- df[!duplicated(df), ]# checking symbol secara general
check1 <- sapply(df, function(x) grepl("[[:punct:]]", x))
sum(check1)## [1] 0cat("\n")# checking symbol secara khusus
check <- sum(grepl("#", df))
check## [1] 0# asumsi jika ada
df <- as.data.frame(lapply(df, function(x) gsub("[[:punct:]]","",x)))
head(df, 500)## X work_year experience_level employment_type
## 1 0 2020 MI FT
## 2 1 2020 SE FT
## 3 2 2020 SE FT
## 4 3 2020 MI FT
## 5 4 2020 SE FT
## 6 5 2020 EN FT
## 7 6 2020 SE FT
## 8 7 2020 MI FT
## 9 8 2020 MI FT
## 10 9 2020 SE FT
## 11 10 2020 EN FT
## 12 11 2020 MI FT
## 13 12 2020 EN FT
## 14 13 2020 MI FT
## 15 14 2020 MI FT
## 16 15 2020 MI FT
## 17 16 2020 EN FT
## 18 17 2020 SE FT
## 19 18 2020 EN FT
## 20 19 2020 MI FT
## 21 20 2020 MI FT
## 22 21 2020 MI FT
## 23 22 2020 SE FT
## 24 23 2020 MI FT
## 25 24 2020 MI FT
## 26 25 2020 EX FT
## 27 26 2020 EN FT
## 28 27 2020 SE FT
## 29 28 2020 EN CT
## 30 29 2020 SE FT
## 31 30 2020 MI FT
## 32 31 2020 EN FT
## 33 32 2020 SE FT
## 34 33 2020 MI FT
## 35 34 2020 MI FT
## 36 35 2020 MI FT
## 37 36 2020 MI FT
## 38 37 2020 EN FT
## 39 38 2020 EN FT
## 40 39 2020 EN FT
## 41 40 2020 MI FT
## 42 41 2020 EX FT
## 43 42 2020 MI FT
## 44 43 2020 MI FT
## 45 44 2020 MI FT
## 46 45 2020 EN PT
## 47 46 2020 MI FT
## 48 47 2020 SE FT
## 49 48 2020 MI FT
## 50 49 2020 MI FT
## 51 50 2020 EN FT
## 52 51 2020 EN FT
## 53 52 2020 EN FT
## 54 53 2020 EN FT
## 55 54 2020 SE FL
## 56 55 2020 SE FT
## 57 56 2020 MI FT
## 58 57 2020 MI FT
## 59 58 2020 SE FT
## 60 59 2020 MI FT
## 61 60 2020 MI FT
## 62 61 2020 MI FT
## 63 62 2020 EN PT
## 64 63 2020 SE FT
## 65 64 2020 SE FT
## 66 65 2020 EN FT
## 67 66 2020 EN FT
## 68 67 2020 SE FT
## 69 68 2020 EN FT
## 70 69 2020 SE FT
## 71 70 2020 MI FT
## 72 71 2020 MI FT
## 73 72 2021 EN FT
## 74 73 2021 EX FT
## 75 74 2021 EX FT
## 76 75 2021 SE FT
## 77 76 2021 MI FT
## 78 77 2021 MI PT
## 79 78 2021 MI CT
## 80 79 2021 EN FT
## 81 80 2021 SE FT
## 82 81 2021 MI FT
## 83 82 2021 MI FT
## 84 83 2021 MI FT
## 85 84 2021 EX FT
## 86 85 2021 MI FT
## 87 86 2021 EN FT
## 88 87 2021 MI FT
## 89 88 2021 SE FT
## 90 89 2021 SE FT
## 91 90 2021 SE FT
## 92 91 2021 EN FT
## 93 92 2021 MI FT
## 94 93 2021 SE FT
## 95 94 2021 EN FT
## 96 95 2021 MI FT
## 97 96 2021 EN PT
## 98 97 2021 MI FT
## 99 98 2021 EN FT
## 100 99 2021 MI FT
## 101 100 2021 MI FT
## 102 101 2021 SE FT
## 103 102 2021 MI FT
## 104 103 2021 MI FT
## 105 104 2021 MI FT
## 106 105 2021 MI FT
## 107 106 2021 MI FT
## 108 107 2021 SE FT
## 109 108 2021 SE FT
## 110 109 2021 EN FT
## 111 110 2021 SE FT
## 112 111 2021 SE FT
## 113 112 2021 SE FT
## 114 113 2021 EN PT
## 115 114 2021 MI FT
## 116 115 2021 EN FT
## 117 116 2021 MI FT
## 118 117 2021 MI FT
## 119 118 2021 EN FT
## 120 119 2021 MI FT
## 121 120 2021 MI FT
## 122 121 2021 SE FT
## 123 122 2021 EN FT
## 124 123 2021 EN FT
## 125 124 2021 EN PT
## 126 125 2021 MI FT
## 127 126 2021 SE FT
## 128 127 2021 MI FT
## 129 128 2021 EN FT
## 130 129 2021 SE FT
## 131 130 2021 EN FT
## 132 131 2021 EN FT
## 133 132 2021 MI FT
## 134 133 2021 SE FT
## 135 134 2021 EN FT
## 136 135 2021 MI FT
## 137 136 2021 MI FT
## 138 137 2021 MI FT
## 139 138 2021 SE FT
## 140 139 2021 EN FT
## 141 140 2021 MI FT
## 142 141 2021 SE FT
## 143 142 2021 SE FT
## 144 143 2021 MI FT
## 145 144 2021 MI FT
## 146 145 2021 SE FT
## 147 146 2021 MI FT
## 148 147 2021 MI FT
## 149 148 2021 SE FT
## 150 149 2021 SE FT
## 151 150 2021 SE FT
## 152 151 2021 MI FT
## 153 152 2021 MI FT
## 154 153 2021 EN FT
## 155 154 2021 SE FT
## 156 155 2021 SE FT
## 157 156 2021 MI FT
## 158 157 2021 MI FT
## 159 158 2021 SE FT
## 160 159 2021 EN FT
## 161 160 2021 EX FT
## 162 161 2021 EX FT
## 163 162 2021 MI FT
## 164 163 2021 EN FT
## 165 164 2021 EX FT
## 166 165 2021 SE FT
## 167 166 2021 EN FT
## 168 167 2021 EX FT
## 169 168 2021 EN FT
## 170 169 2021 MI FT
## 171 170 2021 MI FT
## 172 171 2021 MI FT
## 173 172 2021 EN FT
## 174 173 2021 SE FT
## 175 174 2021 SE FT
## 176 175 2021 SE FT
## 177 176 2021 MI FT
## 178 177 2021 MI FT
## 179 178 2021 EN FT
## 180 179 2021 MI FT
## 181 180 2021 MI FT
## 182 181 2021 MI FT
## 183 182 2021 MI FT
## 184 183 2021 SE FT
## 185 184 2021 MI FL
## 186 185 2021 MI FT
## 187 186 2021 SE FT
## 188 187 2021 EX FT
## 189 188 2021 SE FT
## 190 189 2021 MI FT
## 191 190 2021 SE FT
## 192 191 2021 EN FT
## 193 192 2021 MI FT
## 194 193 2021 SE FT
## 195 194 2021 SE FT
## 196 195 2021 MI FT
## 197 196 2021 EN FT
## 198 197 2021 SE FT
## 199 198 2021 SE FT
## 200 199 2021 EN FT
## 201 200 2021 MI FT
## 202 201 2021 SE FT
## 203 202 2021 MI FT
## 204 203 2021 SE FT
## 205 204 2021 MI FT
## 206 205 2021 MI FT
## 207 206 2021 SE FT
## 208 207 2021 SE FT
## 209 208 2021 MI FL
## 210 209 2021 SE FT
## 211 210 2021 MI FT
## 212 211 2021 MI FT
## 213 212 2021 MI FT
## 214 213 2021 EN FT
## 215 214 2021 EN FT
## 216 215 2021 SE FT
## 217 216 2021 EN PT
## 218 217 2021 MI FT
## 219 218 2021 MI FT
## 220 219 2021 SE FT
## 221 220 2021 MI FT
## 222 221 2021 MI FT
## 223 222 2021 MI FT
## 224 223 2021 MI FT
## 225 224 2021 SE FT
## 226 225 2021 EX CT
## 227 226 2021 SE FT
## 228 227 2021 MI FT
## 229 228 2021 SE FT
## 230 229 2021 SE FT
## 231 230 2021 EN FT
## 232 231 2021 SE FT
## 233 232 2021 SE FT
## 234 233 2021 SE FT
## 235 234 2021 MI FT
## 236 235 2021 MI FT
## 237 236 2021 MI FT
## 238 237 2021 MI FT
## 239 238 2021 EN FT
## 240 239 2021 EN FT
## 241 240 2021 SE FT
## 242 241 2021 MI FT
## 243 242 2021 MI FT
## 244 243 2021 SE FT
## 245 244 2021 EN FT
## 246 245 2021 MI FT
## 247 246 2021 EN FT
## 248 247 2021 MI FT
## 249 248 2021 SE FT
## 250 249 2021 SE FT
## 251 250 2021 MI FT
## 252 251 2021 EN FT
## 253 252 2021 EX FT
## 254 253 2021 EN FT
## 255 254 2021 MI FT
## 256 255 2021 SE FT
## 257 256 2021 MI FT
## 258 257 2021 SE FT
## 259 258 2021 SE FT
## 260 259 2021 EX FT
## 261 260 2021 MI FT
## 262 261 2021 SE FT
## 263 262 2021 MI FT
## 264 263 2021 SE FT
## 265 264 2021 MI FT
## 266 265 2021 SE FT
## 267 266 2021 MI FT
## 268 267 2021 MI FT
## 269 268 2021 MI FT
## 270 269 2021 EN FT
## 271 270 2021 EN FT
## 272 271 2021 SE FT
## 273 272 2021 EN FT
## 274 273 2021 EN FT
## 275 274 2021 SE FT
## 276 275 2021 EN FT
## 277 276 2021 EN FT
## 278 277 2021 SE FT
## 279 278 2021 SE FT
## 280 279 2021 EN FT
## 281 280 2021 MI FT
## 282 281 2021 EN FT
## 283 282 2021 MI PT
## 284 283 2021 SE CT
## 285 284 2021 MI FT
## 286 285 2021 SE FT
## 287 286 2021 SE FT
## 288 287 2021 MI FT
## 289 288 2021 MI FT
## 290 289 2022 SE FT
## 291 290 2022 SE FT
## 292 291 2022 SE FT
## 293 292 2022 MI FT
## 294 293 2022 MI FT
## 295 294 2022 MI FT
## 296 295 2022 MI FT
## 297 296 2022 SE FT
## 298 297 2022 SE FT
## 299 298 2022 SE FT
## 300 299 2022 SE FT
## 301 300 2022 SE FT
## 302 301 2022 SE FT
## 303 302 2022 SE FT
## 304 303 2022 SE FT
## 305 304 2022 EN FT
## 306 305 2022 SE FT
## 307 306 2022 SE FT
## 308 307 2022 MI FT
## 309 308 2022 MI FT
## 310 309 2022 EX FT
## 311 310 2022 EX FT
## 312 311 2022 MI FT
## 313 312 2022 MI FT
## 314 313 2022 MI FT
## 315 314 2022 MI FT
## 316 315 2022 SE FT
## 317 316 2022 EN FT
## 318 317 2022 SE FT
## 319 318 2022 SE FT
## 320 319 2022 SE FT
## 321 320 2022 SE FT
## 322 321 2022 SE FT
## 323 322 2022 SE FT
## 324 323 2022 SE FT
## 325 324 2022 SE FT
## 326 325 2022 SE FT
## 327 326 2022 EX FT
## 328 327 2022 EX FT
## 329 328 2022 SE FT
## 330 329 2022 MI FT
## 331 330 2022 SE FT
## 332 331 2022 SE FT
## 333 332 2022 SE FT
## 334 333 2022 SE FT
## 335 334 2022 SE FT
## 336 335 2022 SE FT
## 337 336 2022 MI FT
## 338 337 2022 SE FT
## 339 338 2022 SE FT
## 340 339 2022 SE FT
## 341 340 2022 SE FT
## 342 341 2022 SE FT
## 343 342 2022 EX FT
## 344 343 2022 EX FT
## 345 344 2022 EX FT
## 346 345 2022 SE FT
## 347 346 2022 SE FT
## 348 347 2022 SE FT
## 349 348 2022 SE FT
## 350 349 2022 SE FT
## 351 350 2022 SE FT
## 352 351 2022 SE FT
## 353 352 2022 SE FT
## 354 353 2022 SE FT
## 355 354 2022 SE FT
## 356 355 2022 SE FT
## 357 356 2022 SE FT
## 358 357 2022 SE FT
## 359 358 2022 SE FT
## 360 359 2022 SE FT
## 361 360 2022 SE FT
## 362 361 2022 SE FT
## 363 362 2022 SE FT
## 364 363 2022 SE FT
## 365 364 2022 SE FT
## 366 365 2022 SE FT
## 367 366 2022 SE FT
## 368 367 2022 MI FT
## 369 368 2022 EX FT
## 370 369 2022 SE FT
## 371 370 2022 SE FT
## 372 371 2022 SE FT
## 373 372 2022 SE FT
## 374 373 2022 MI FT
## 375 374 2022 MI FT
## 376 375 2022 EX FT
## 377 376 2022 SE FT
## 378 377 2022 SE FT
## 379 378 2022 SE FT
## 380 379 2022 SE FT
## 381 380 2022 SE FT
## 382 381 2022 SE FT
## 383 382 2022 SE FT
## 384 383 2022 SE FT
## 385 384 2022 EX FT
## 386 385 2022 SE FT
## 387 386 2022 EN FT
## 388 387 2022 SE FT
## 389 388 2022 SE FT
## 390 389 2022 MI FT
## 391 390 2022 MI FT
## 392 391 2022 MI FT
## 393 392 2022 SE FT
## 394 393 2022 SE FT
## 395 394 2022 SE FT
## 396 395 2022 SE FT
## 397 396 2022 MI FT
## 398 397 2022 MI FT
## 399 398 2022 SE FT
## 400 399 2022 SE FT
## 401 400 2022 SE FT
## 402 401 2022 SE FT
## 403 402 2022 SE FT
## 404 403 2022 SE FT
## 405 404 2022 SE FT
## 406 405 2022 MI FT
## 407 406 2022 MI FT
## 408 407 2022 SE FT
## 409 408 2022 MI FT
## 410 409 2022 SE FT
## 411 410 2022 MI FT
## 412 411 2022 MI FT
## 413 412 2022 MI FT
## 414 413 2022 MI FT
## 415 414 2022 MI FT
## 416 415 2022 MI FT
## 417 416 2022 SE FT
## 418 417 2022 SE FT
## 419 418 2022 MI FT
## 420 419 2022 MI FT
## 421 420 2022 MI FT
## 422 421 2022 MI FT
## 423 422 2022 MI FT
## 424 423 2022 SE FT
## 425 424 2022 SE FT
## 426 425 2022 MI FT
## 427 426 2022 SE FT
## 428 427 2022 MI FT
## 429 428 2022 SE FT
## 430 429 2022 MI FT
## 431 430 2022 MI FT
## 432 431 2022 MI FT
## 433 432 2022 MI FT
## 434 433 2022 MI FT
## 435 434 2022 MI FT
## 436 435 2022 MI FT
## 437 436 2022 MI FT
## 438 437 2022 MI FT
## 439 438 2022 SE FT
## 440 439 2022 SE FT
## 441 440 2022 MI FT
## 442 441 2022 MI FT
## 443 442 2022 MI FT
## 444 443 2022 MI FT
## 445 444 2022 SE FT
## 446 445 2022 MI FT
## 447 446 2022 SE FT
## 448 447 2022 SE FT
## 449 448 2022 SE FT
## 450 449 2022 EN FT
## 451 450 2022 SE FT
## 452 451 2022 MI FT
## 453 452 2022 EX FT
## 454 453 2022 MI FT
## 455 454 2022 EN FT
## 456 455 2022 MI FT
## 457 456 2022 SE FT
## 458 457 2022 SE FT
## 459 458 2022 MI FT
## 460 459 2022 MI FT
## 461 460 2022 MI FT
## 462 461 2022 EN FT
## 463 462 2022 MI PT
## 464 463 2022 EN FT
## 465 464 2022 SE FT
## 466 465 2022 EN FT
## 467 466 2022 SE FT
## 468 467 2022 SE FT
## 469 468 2022 SE FT
## 470 469 2022 SE FT
## 471 470 2022 MI FT
## 472 471 2022 MI FT
## 473 472 2022 SE FT
## 474 473 2022 SE FT
## 475 474 2022 MI FT
## 476 475 2022 MI FT
## 477 476 2022 SE FT
## 478 477 2022 SE FT
## 479 478 2022 MI FT
## 480 479 2022 MI FT
## 481 480 2022 SE FT
## 482 481 2022 SE FT
## 483 482 2022 EX FT
## 484 483 2022 EX FT
## 485 484 2022 SE FT
## 486 485 2022 SE FT
## 487 486 2022 SE FT
## 488 487 2022 EN PT
## 489 488 2022 MI FL
## 490 489 2022 EN CT
## 491 490 2022 SE FT
## 492 491 2022 MI FT
## 493 492 2022 MI FT
## 494 493 2022 SE FT
## 495 494 2022 SE FT
## 496 495 2022 MI FT
## 497 496 2022 EN FT
## 498 497 2022 SE FT
## 499 498 2022 SE FT
## 500 499 2022 EN FT
## job_title salary salary_currency
## 1 Data Scientist 70000 EUR
## 2 Machine Learning Scientist 260000 USD
## 3 Big Data Engineer 85000 GBP
## 4 Product Data Analyst 20000 USD
## 5 Machine Learning Engineer 150000 USD
## 6 Data Analyst 72000 USD
## 7 Lead Data Scientist 190000 USD
## 8 Data Scientist 11000000 HUF
## 9 Business Data Analyst 135000 USD
## 10 Lead Data Engineer 125000 USD
## 11 Data Scientist 45000 EUR
## 12 Data Scientist 3000000 INR
## 13 Data Scientist 35000 EUR
## 14 Lead Data Analyst 87000 USD
## 15 Data Analyst 85000 USD
## 16 Data Analyst 8000 USD
## 17 Data Engineer 4450000 JPY
## 18 Big Data Engineer 100000 EUR
## 19 Data Science Consultant 423000 INR
## 20 Lead Data Engineer 56000 USD
## 21 Machine Learning Engineer 299000 CNY
## 22 Product Data Analyst 450000 INR
## 23 Data Engineer 42000 EUR
## 24 BI Data Analyst 98000 USD
## 25 Lead Data Scientist 115000 USD
## 26 Director of Data Science 325000 USD
## 27 Research Scientist 42000 USD
## 28 Data Engineer 720000 MXN
## 29 Business Data Analyst 100000 USD
## 30 Machine Learning Manager 157000 CAD
## 31 Data Engineering Manager 51999 EUR
## 32 Big Data Engineer 70000 USD
## 33 Data Scientist 60000 EUR
## 34 Research Scientist 450000 USD
## 35 Data Analyst 41000 EUR
## 36 Data Engineer 65000 EUR
## 37 Data Science Consultant 103000 USD
## 38 Machine Learning Engineer 250000 USD
## 39 Data Analyst 10000 USD
## 40 Machine Learning Engineer 138000 USD
## 41 Data Scientist 45760 USD
## 42 Data Engineering Manager 70000 EUR
## 43 Machine Learning Infrastructure Engineer 44000 EUR
## 44 Data Engineer 106000 USD
## 45 Data Engineer 88000 GBP
## 46 ML Engineer 14000 EUR
## 47 Data Scientist 60000 GBP
## 48 Data Engineer 188000 USD
## 49 Data Scientist 105000 USD
## 50 Data Engineer 61500 EUR
## 51 Data Analyst 450000 INR
## 52 Data Analyst 91000 USD
## 53 AI Scientist 300000 DKK
## 54 Data Engineer 48000 EUR
## 55 Computer Vision Engineer 60000 USD
## 56 Principal Data Scientist 130000 EUR
## 57 Data Scientist 34000 EUR
## 58 Data Scientist 118000 USD
## 59 Data Scientist 120000 USD
## 60 Data Scientist 138350 USD
## 61 Data Engineer 110000 USD
## 62 Data Engineer 130800 USD
## 63 Data Scientist 19000 EUR
## 64 Data Scientist 412000 USD
## 65 Machine Learning Engineer 40000 EUR
## 66 Data Scientist 55000 EUR
## 67 Data Scientist 43200 EUR
## 68 Data Science Manager 190200 USD
## 69 Data Scientist 105000 USD
## 70 Data Scientist 80000 EUR
## 71 Data Scientist 55000 EUR
## 72 Data Scientist 37000 EUR
## 73 Research Scientist 60000 GBP
## 74 BI Data Analyst 150000 USD
## 75 Head of Data 235000 USD
## 76 Data Scientist 45000 EUR
## 77 BI Data Analyst 100000 USD
## 78 3D Computer Vision Researcher 400000 INR
## 79 ML Engineer 270000 USD
## 80 Data Analyst 80000 USD
## 81 Data Analytics Engineer 67000 EUR
## 82 Data Engineer 140000 USD
## 83 Applied Data Scientist 68000 CAD
## 84 Machine Learning Engineer 40000 EUR
## 85 Director of Data Science 130000 EUR
## 86 Data Engineer 110000 PLN
## 87 Data Analyst 50000 EUR
## 88 Data Analytics Engineer 110000 USD
## 89 Lead Data Analyst 170000 USD
## 90 Data Analyst 80000 USD
## 91 Marketing Data Analyst 75000 EUR
## 92 Data Science Consultant 65000 EUR
## 93 Lead Data Analyst 1450000 INR
## 94 Lead Data Engineer 276000 USD
## 95 Data Scientist 2200000 INR
## 96 Cloud Data Engineer 120000 SGD
## 97 AI Scientist 12000 USD
## 98 Financial Data Analyst 450000 USD
## 99 Computer Vision Software Engineer 70000 USD
## 100 Computer Vision Software Engineer 81000 EUR
## 101 Data Analyst 75000 USD
## 102 Data Engineer 150000 USD
## 103 BI Data Analyst 11000000 HUF
## 104 Data Analyst 62000 USD
## 105 Data Scientist 73000 USD
## 106 Data Analyst 37456 GBP
## 107 Research Scientist 235000 CAD
## 108 Data Engineer 115000 USD
## 109 Data Engineer 150000 USD
## 110 Data Engineer 2250000 INR
## 111 Machine Learning Engineer 80000 EUR
## 112 Director of Data Engineering 82500 GBP
## 113 Lead Data Engineer 75000 GBP
## 114 AI Scientist 12000 USD
## 115 Data Engineer 38400 EUR
## 116 Machine Learning Scientist 225000 USD
## 117 Data Scientist 50000 USD
## 118 Data Science Engineer 34000 EUR
## 119 Data Analyst 90000 USD
## 120 Data Engineer 200000 USD
## 121 Big Data Engineer 60000 USD
## 122 Principal Data Engineer 200000 USD
## 123 Data Analyst 50000 USD
## 124 Applied Data Scientist 80000 GBP
## 125 Data Analyst 8760 EUR
## 126 Principal Data Scientist 151000 USD
## 127 Machine Learning Scientist 120000 USD
## 128 Data Scientist 700000 INR
## 129 Machine Learning Engineer 20000 USD
## 130 Lead Data Scientist 3000000 INR
## 131 Machine Learning Developer 100000 USD
## 132 Data Scientist 42000 EUR
## 133 Applied Machine Learning Scientist 38400 USD
## 134 Computer Vision Engineer 24000 USD
## 135 Data Scientist 100000 USD
## 136 Data Analyst 90000 USD
## 137 ML Engineer 7000000 JPY
## 138 ML Engineer 8500000 JPY
## 139 Principal Data Scientist 220000 USD
## 140 Data Scientist 80000 USD
## 141 Data Analyst 135000 USD
## 142 Data Science Manager 240000 USD
## 143 Data Engineering Manager 150000 USD
## 144 Data Scientist 82500 USD
## 145 Data Engineer 100000 USD
## 146 Machine Learning Engineer 70000 EUR
## 147 Research Scientist 53000 EUR
## 148 Data Engineer 90000 USD
## 149 Data Engineering Manager 153000 USD
## 150 Cloud Data Engineer 160000 USD
## 151 Director of Data Science 168000 USD
## 152 Data Scientist 150000 USD
## 153 Data Scientist 95000 CAD
## 154 Data Scientist 13400 USD
## 155 Data Science Manager 144000 USD
## 156 Data Science Engineer 159500 CAD
## 157 Data Scientist 160000 SGD
## 158 Applied Machine Learning Scientist 423000 USD
## 159 Data Analytics Manager 120000 USD
## 160 Machine Learning Engineer 125000 USD
## 161 Head of Data 230000 USD
## 162 Head of Data Science 85000 USD
## 163 Data Engineer 24000 EUR
## 164 Data Science Consultant 54000 EUR
## 165 Director of Data Science 110000 EUR
## 166 Data Specialist 165000 USD
## 167 Data Engineer 80000 USD
## 168 Director of Data Science 250000 USD
## 169 BI Data Analyst 55000 USD
## 170 Data Architect 150000 USD
## 171 Data Architect 170000 USD
## 172 Data Engineer 60000 GBP
## 173 Data Analyst 60000 USD
## 174 Principal Data Scientist 235000 USD
## 175 Research Scientist 51400 EUR
## 176 Data Engineering Manager 174000 USD
## 177 Data Scientist 58000 MXN
## 178 Data Scientist 30400000 CLP
## 179 Machine Learning Engineer 81000 USD
## 180 Data Scientist 420000 INR
## 181 Big Data Engineer 1672000 INR
## 182 Data Scientist 76760 EUR
## 183 Data Engineer 22000 EUR
## 184 Finance Data Analyst 45000 GBP
## 185 Machine Learning Scientist 12000 USD
## 186 Data Engineer 4000 USD
## 187 Data Analytics Engineer 50000 USD
## 188 Data Science Consultant 59000 EUR
## 189 Data Engineer 65000 EUR
## 190 Machine Learning Engineer 74000 USD
## 191 Data Science Manager 152000 USD
## 192 Machine Learning Engineer 21844 USD
## 193 Big Data Engineer 18000 USD
## 194 Data Science Manager 174000 USD
## 195 Research Scientist 120500 CAD
## 196 Data Scientist 147000 USD
## 197 BI Data Analyst 9272 USD
## 198 Machine Learning Engineer 1799997 INR
## 199 Data Science Manager 4000000 INR
## 200 Data Science Consultant 90000 USD
## 201 Data Scientist 52000 EUR
## 202 Machine Learning Infrastructure Engineer 195000 USD
## 203 Data Scientist 32000 EUR
## 204 Research Scientist 50000 USD
## 205 Data Scientist 160000 USD
## 206 Data Scientist 69600 BRL
## 207 Machine Learning Engineer 200000 USD
## 208 Data Engineer 165000 USD
## 209 Data Engineer 20000 USD
## 210 Data Analytics Manager 120000 USD
## 211 Machine Learning Engineer 21000 EUR
## 212 Research Scientist 48000 EUR
## 213 Data Engineer 48000 GBP
## 214 Big Data Engineer 435000 INR
## 215 Machine Learning Engineer 21000 EUR
## 216 Principal Data Engineer 185000 USD
## 217 Computer Vision Engineer 180000 DKK
## 218 Data Scientist 76760 EUR
## 219 Machine Learning Engineer 75000 EUR
## 220 Data Analytics Manager 140000 USD
## 221 Machine Learning Engineer 180000 PLN
## 222 Data Scientist 85000 GBP
## 223 Data Scientist 2500000 INR
## 224 Data Scientist 40900 GBP
## 225 Machine Learning Scientist 225000 USD
## 226 Principal Data Scientist 416000 USD
## 227 Data Scientist 110000 CAD
## 228 Data Scientist 75000 EUR
## 229 Data Scientist 135000 USD
## 230 Data Analyst 90000 CAD
## 231 Big Data Engineer 1200000 INR
## 232 ML Engineer 256000 USD
## 233 Director of Data Engineering 200000 USD
## 234 Data Analyst 200000 USD
## 235 Data Architect 180000 USD
## 236 Head of Data Science 110000 USD
## 237 Research Scientist 80000 CAD
## 238 Data Scientist 39600 EUR
## 239 Data Scientist 4000 USD
## 240 Data Engineer 1600000 INR
## 241 Data Scientist 130000 CAD
## 242 Data Analyst 80000 USD
## 243 Data Engineer 110000 USD
## 244 Data Scientist 165000 USD
## 245 AI Scientist 1335000 INR
## 246 Data Engineer 52500 GBP
## 247 Data Scientist 31000 EUR
## 248 Data Engineer 108000 TRY
## 249 Data Engineer 70000 GBP
## 250 Principal Data Analyst 170000 USD
## 251 Data Scientist 115000 USD
## 252 Data Scientist 90000 USD
## 253 Principal Data Engineer 600000 USD
## 254 Data Scientist 2100000 INR
## 255 Data Analyst 93000 USD
## 256 Big Data Architect 125000 CAD
## 257 Data Engineer 200000 USD
## 258 Principal Data Scientist 147000 EUR
## 259 Machine Learning Engineer 185000 USD
## 260 Director of Data Science 120000 EUR
## 261 Data Scientist 130000 USD
## 262 Data Analyst 54000 EUR
## 263 Data Scientist 1250000 INR
## 264 Machine Learning Engineer 4900000 INR
## 265 Data Scientist 21600 EUR
## 266 Lead Data Engineer 160000 USD
## 267 Data Engineer 93150 USD
## 268 Data Engineer 111775 USD
## 269 Data Engineer 250000 TRY
## 270 Data Engineer 55000 EUR
## 271 Data Engineer 72500 USD
## 272 Computer Vision Engineer 102000 BRL
## 273 Data Science Consultant 65000 EUR
## 274 Machine Learning Engineer 85000 USD
## 275 Data Scientist 65720 EUR
## 276 Data Scientist 100000 USD
## 277 Data Scientist 58000 USD
## 278 AI Scientist 55000 USD
## 279 Data Scientist 180000 TRY
## 280 Business Data Analyst 50000 EUR
## 281 Data Engineer 112000 USD
## 282 Research Scientist 100000 USD
## 283 Data Engineer 59000 EUR
## 284 Staff Data Scientist 105000 USD
## 285 Research Scientist 69999 USD
## 286 Data Science Manager 7000000 INR
## 287 Head of Data 87000 EUR
## 288 Data Scientist 109000 USD
## 289 Machine Learning Engineer 43200 EUR
## 290 Data Engineer 135000 USD
## 291 Data Analyst 155000 USD
## 292 Data Analyst 120600 USD
## 293 Data Scientist 130000 USD
## 294 Data Scientist 90000 USD
## 295 Data Engineer 170000 USD
## 296 Data Engineer 150000 USD
## 297 Data Analyst 102100 USD
## 298 Data Analyst 84900 USD
## 299 Data Scientist 136620 USD
## 300 Data Scientist 99360 USD
## 301 Data Scientist 90000 GBP
## 302 Data Scientist 80000 GBP
## 303 Data Scientist 146000 USD
## 304 Data Scientist 123000 USD
## 305 Data Engineer 40000 GBP
## 306 Data Analyst 99000 USD
## 307 Data Analyst 116000 USD
## 308 Data Analyst 106260 USD
## 309 Data Analyst 126500 USD
## 310 Data Engineer 242000 USD
## 311 Data Engineer 200000 USD
## 312 Data Scientist 50000 GBP
## 313 Data Scientist 30000 GBP
## 314 Data Engineer 60000 GBP
## 315 Data Engineer 40000 GBP
## 316 Data Scientist 165220 USD
## 317 Data Engineer 35000 GBP
## 318 Data Scientist 120160 USD
## 319 Data Analyst 90320 USD
## 320 Data Engineer 181940 USD
## 321 Data Engineer 132320 USD
## 322 Data Engineer 220110 USD
## 323 Data Engineer 160080 USD
## 324 Data Scientist 180000 USD
## 325 Data Scientist 120000 USD
## 326 Data Analyst 124190 USD
## 327 Data Analyst 130000 USD
## 328 Data Analyst 110000 USD
## 329 Data Analyst 170000 USD
## 330 Data Analyst 115500 USD
## 331 Data Analyst 112900 USD
## 332 Data Analyst 90320 USD
## 333 Data Analyst 112900 USD
## 334 Data Analyst 90320 USD
## 335 Data Engineer 165400 USD
## 336 Data Engineer 132320 USD
## 337 Data Analyst 167000 USD
## 338 Data Engineer 243900 USD
## 339 Data Analyst 136600 USD
## 340 Data Analyst 109280 USD
## 341 Data Engineer 128875 USD
## 342 Data Engineer 93700 USD
## 343 Head of Data Science 224000 USD
## 344 Head of Data Science 167875 USD
## 345 Analytics Engineer 175000 USD
## 346 Data Engineer 156600 USD
## 347 Data Engineer 108800 USD
## 348 Data Scientist 95550 USD
## 349 Data Engineer 113000 USD
## 350 Data Analyst 135000 USD
## 351 Data Science Manager 161342 USD
## 352 Data Science Manager 137141 USD
## 353 Data Scientist 167000 USD
## 354 Data Scientist 123000 USD
## 355 Data Engineer 60000 GBP
## 356 Data Engineer 50000 GBP
## 357 Data Scientist 150000 USD
## 358 Data Scientist 211500 USD
## 359 Data Architect 192400 USD
## 360 Data Architect 90700 USD
## 361 Data Analyst 130000 USD
## 362 Data Analyst 61300 USD
## 363 Data Analyst 130000 USD
## 364 Data Analyst 61300 USD
## 365 Data Engineer 160000 USD
## 366 Data Scientist 138600 USD
## 367 Data Engineer 136000 USD
## 368 Data Analyst 58000 USD
## 369 Analytics Engineer 135000 USD
## 370 Data Scientist 170000 USD
## 371 Data Scientist 123000 USD
## 372 Machine Learning Engineer 189650 USD
## 373 Machine Learning Engineer 164996 USD
## 374 ETL Developer 50000 EUR
## 375 ETL Developer 50000 EUR
## 376 Lead Data Engineer 150000 CAD
## 377 Data Analyst 132000 USD
## 378 Data Engineer 165400 USD
## 379 Data Architect 208775 USD
## 380 Data Architect 147800 USD
## 381 Data Engineer 136994 USD
## 382 Data Engineer 101570 USD
## 383 Data Analyst 128875 USD
## 384 Data Analyst 93700 USD
## 385 Head of Machine Learning 6000000 INR
## 386 Data Engineer 132320 USD
## 387 Machine Learning Engineer 28500 GBP
## 388 Data Analyst 164000 USD
## 389 Data Engineer 155000 USD
## 390 Machine Learning Engineer 95000 GBP
## 391 Machine Learning Engineer 75000 GBP
## 392 AI Scientist 120000 USD
## 393 Data Analyst 112900 USD
## 394 Data Analyst 90320 USD
## 395 Data Analytics Manager 145000 USD
## 396 Data Analytics Manager 105400 USD
## 397 Machine Learning Engineer 80000 EUR
## 398 Data Engineer 90000 GBP
## 399 Data Scientist 215300 USD
## 400 Data Scientist 158200 USD
## 401 Data Engineer 209100 USD
## 402 Data Engineer 154600 USD
## 403 Data Analyst 115934 USD
## 404 Data Analyst 81666 USD
## 405 Data Engineer 175000 USD
## 406 Data Engineer 75000 GBP
## 407 Data Analyst 58000 USD
## 408 Data Engineer 183600 USD
## 409 Data Analyst 40000 GBP
## 410 Data Scientist 180000 USD
## 411 Data Scientist 55000 GBP
## 412 Data Scientist 35000 GBP
## 413 Data Engineer 60000 EUR
## 414 Data Engineer 45000 EUR
## 415 Data Engineer 60000 GBP
## 416 Data Engineer 45000 GBP
## 417 Data Scientist 260000 USD
## 418 Data Science Engineer 60000 USD
## 419 Data Engineer 63900 USD
## 420 Machine Learning Scientist 160000 USD
## 421 Machine Learning Scientist 112300 USD
## 422 Data Science Manager 241000 USD
## 423 Data Science Manager 159000 USD
## 424 Data Scientist 180000 USD
## 425 Data Scientist 80000 USD
## 426 Data Engineer 82900 USD
## 427 Data Engineer 100800 USD
## 428 Data Engineer 45000 EUR
## 429 Data Scientist 140400 USD
## 430 Data Analyst 30000 GBP
## 431 Data Analyst 40000 EUR
## 432 Data Analyst 30000 EUR
## 433 Data Engineer 80000 EUR
## 434 Data Engineer 70000 EUR
## 435 Data Engineer 80000 GBP
## 436 Data Engineer 70000 GBP
## 437 Data Engineer 60000 EUR
## 438 Data Engineer 80000 EUR
## 439 Machine Learning Engineer 189650 USD
## 440 Machine Learning Engineer 164996 USD
## 441 Data Analyst 40000 EUR
## 442 Data Analyst 30000 EUR
## 443 Data Engineer 75000 GBP
## 444 Data Engineer 60000 GBP
## 445 Data Scientist 215300 USD
## 446 Data Engineer 70000 EUR
## 447 Data Engineer 209100 USD
## 448 Data Engineer 154600 USD
## 449 Data Engineer 180000 USD
## 450 ML Engineer 20000 EUR
## 451 Data Engineer 80000 USD
## 452 Machine Learning Developer 100000 CAD
## 453 Director of Data Science 250000 CAD
## 454 Machine Learning Engineer 120000 USD
## 455 Computer Vision Engineer 125000 USD
## 456 NLP Engineer 240000 CNY
## 457 Data Engineer 105000 USD
## 458 Lead Machine Learning Engineer 80000 EUR
## 459 Business Data Analyst 1400000 INR
## 460 Data Scientist 2400000 INR
## 461 Machine Learning Infrastructure Engineer 53000 EUR
## 462 Financial Data Analyst 100000 USD
## 463 Data Engineer 50000 EUR
## 464 Data Scientist 1400000 INR
## 465 Principal Data Scientist 148000 EUR
## 466 Data Engineer 120000 USD
## 467 Research Scientist 144000 USD
## 468 Data Scientist 104890 USD
## 469 Data Engineer 100000 USD
## 470 Data Scientist 140000 USD
## 471 Data Analyst 135000 USD
## 472 Data Analyst 50000 USD
## 473 Data Scientist 220000 USD
## 474 Data Scientist 140000 USD
## 475 Data Scientist 140000 GBP
## 476 Data Scientist 70000 GBP
## 477 Data Scientist 185100 USD
## 478 Machine Learning Engineer 220000 USD
## 479 Data Scientist 200000 USD
## 480 Data Scientist 120000 USD
## 481 Machine Learning Engineer 120000 USD
## 482 Machine Learning Engineer 65000 USD
## 483 Data Engineer 324000 USD
## 484 Data Engineer 216000 USD
## 485 Data Engineer 210000 USD
## 486 Machine Learning Engineer 120000 USD
## 487 Data Scientist 230000 USD
## 488 Data Scientist 100000 USD
## 489 Data Scientist 100000 USD
## 490 Applied Machine Learning Scientist 29000 EUR
## 491 Head of Data 200000 USD
## 492 Principal Data Analyst 75000 USD
## 493 Data Scientist 150000 PLN
## 494 Machine Learning Developer 100000 CAD
## 495 Data Scientist 100000 USD
## 496 Machine Learning Scientist 153000 USD
## 497 Data Engineer 52800 EUR
## 498 Data Scientist 165000 USD
## 499 Research Scientist 85000 EUR
## 500 Data Scientist 66500 CAD
## salary_in_usd employee_residence remote_ratio company_location company_size
## 1 79833 DE 0 DE L
## 2 260000 JP 0 JP S
## 3 109024 GB 50 GB M
## 4 20000 HN 0 HN S
## 5 150000 US 50 US L
## 6 72000 US 100 US L
## 7 190000 US 100 US S
## 8 35735 HU 50 HU L
## 9 135000 US 100 US L
## 10 125000 NZ 50 NZ S
## 11 51321 FR 0 FR S
## 12 40481 IN 0 IN L
## 13 39916 FR 0 FR M
## 14 87000 US 100 US L
## 15 85000 US 100 US L
## 16 8000 PK 50 PK L
## 17 41689 JP 100 JP S
## 18 114047 PL 100 GB S
## 19 5707 IN 50 IN M
## 20 56000 PT 100 US M
## 21 43331 CN 0 CN M
## 22 6072 IN 100 IN L
## 23 47899 GR 50 GR L
## 24 98000 US 0 US M
## 25 115000 AE 0 AE L
## 26 325000 US 100 US L
## 27 42000 NL 50 NL L
## 28 33511 MX 0 MX S
## 29 100000 US 100 US L
## 30 117104 CA 50 CA L
## 31 59303 DE 100 DE S
## 32 70000 US 100 US L
## 33 68428 GR 100 US L
## 34 450000 US 0 US M
## 35 46759 FR 50 FR L
## 36 74130 AT 50 AT L
## 37 103000 US 100 US L
## 38 250000 US 50 US L
## 39 10000 NG 100 NG S
## 40 138000 US 100 US S
## 41 45760 PH 100 US S
## 42 79833 ES 50 ES L
## 43 50180 PT 0 PT M
## 44 106000 US 100 US L
## 45 112872 GB 50 GB L
## 46 15966 DE 100 DE S
## 47 76958 GB 100 GB S
## 48 188000 US 100 US L
## 49 105000 US 100 US L
## 50 70139 FR 50 FR L
## 51 6072 IN 0 IN S
## 52 91000 US 100 US L
## 53 45896 DK 50 DK S
## 54 54742 PK 100 DE L
## 55 60000 RU 100 US S
## 56 148261 DE 100 DE M
## 57 38776 ES 100 ES M
## 58 118000 US 100 US M
## 59 120000 US 50 US L
## 60 138350 US 100 US M
## 61 110000 US 100 US L
## 62 130800 ES 100 US M
## 63 21669 IT 50 IT S
## 64 412000 US 100 US L
## 65 45618 HR 100 HR S
## 66 62726 DE 50 DE S
## 67 49268 DE 0 DE S
## 68 190200 US 100 US M
## 69 105000 US 100 US S
## 70 91237 AT 0 AT S
## 71 62726 FR 50 LU S
## 72 42197 FR 50 FR S
## 73 82528 GB 50 GB L
## 74 150000 IN 100 US L
## 75 235000 US 100 US L
## 76 53192 FR 50 FR L
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## 79 270000 US 100 US L
## 80 80000 US 100 US M
## 81 79197 DE 100 DE L
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## 83 54238 GB 50 CA L
## 84 47282 ES 100 ES S
## 85 153667 IT 100 PL L
## 86 28476 PL 100 PL L
## 87 59102 FR 50 FR M
## 88 110000 US 100 US L
## 89 170000 US 100 US L
## 90 80000 BG 100 US S
## 91 88654 GR 100 DK L
## 92 76833 DE 100 DE S
## 93 19609 IN 100 IN L
## 94 276000 US 0 US L
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## 96 89294 SG 50 SG L
## 97 12000 BR 100 US S
## 98 450000 US 100 US L
## 99 70000 US 100 US M
## 100 95746 DE 100 US S
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## 106 51519 GB 50 GB L
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## 110 30428 IN 100 IN L
## 111 94564 DE 50 DE L
## 112 113476 GB 100 GB M
## 113 103160 GB 100 GB S
## 114 12000 PK 100 US M
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## 117 50000 NG 100 NG L
## 118 40189 GR 100 GR M
## 119 90000 US 100 US S
## 120 200000 US 100 US L
## 121 60000 ES 50 RO M
## 122 200000 US 100 US M
## 123 50000 US 100 US M
## 124 110037 GB 0 GB L
## 125 10354 ES 50 ES M
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## 130 40570 IN 50 IN L
## 131 100000 IQ 50 IQ S
## 132 49646 FR 50 FR M
## 133 38400 VN 100 US M
## 134 24000 BR 100 BR M
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## 136 90000 US 100 US M
## 137 63711 JP 50 JP S
## 138 77364 JP 50 JP S
## 139 220000 US 0 US L
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## 141 135000 US 100 US L
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## 146 82744 BE 50 BE M
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## 151 168000 JP 0 JP S
## 152 150000 US 100 US M
## 153 75774 CA 100 CA L
## 154 13400 UA 100 UA L
## 155 144000 US 100 US L
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## 157 119059 SG 100 IL M
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## 160 125000 US 100 US S
## 161 230000 RU 50 RU L
## 162 85000 RU 0 RU M
## 163 28369 MT 50 MT L
## 164 63831 DE 50 DE L
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## 166 165000 US 100 US L
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## 171 170000 US 100 US L
## 172 82528 GB 100 GB L
## 173 60000 US 100 US S
## 174 235000 US 100 US L
## 175 60757 PT 50 PT L
## 176 174000 US 100 US L
## 177 2859 MX 0 MX S
## 178 40038 CL 100 CL L
## 179 81000 US 50 US S
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## 181 22611 IN 0 IN L
## 182 90734 DE 50 DE L
## 183 26005 RO 0 US L
## 184 61896 GB 50 GB L
## 185 12000 PK 50 PK M
## 186 4000 IR 100 IR M
## 187 50000 VN 100 GB M
## 188 69741 FR 100 ES S
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## 192 21844 CO 50 CO M
## 193 18000 MD 0 MD S
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## 198 24342 IN 100 IN L
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## 207 200000 US 100 US L
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## 213 66022 HK 50 GB S
## 214 5882 IN 0 CH L
## 215 24823 DE 50 DE M
## 216 185000 US 100 US L
## 217 28609 DK 50 DK S
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## 220 140000 US 100 US L
## 221 46597 PL 100 PL L
## 222 116914 GB 50 GB L
## 223 33808 IN 0 IN M
## 224 56256 GB 50 GB L
## 225 225000 US 100 CA L
## 226 416000 US 100 US S
## 227 87738 CA 100 CA S
## 228 88654 DE 50 DE L
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## 231 16228 IN 100 IN L
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## 239 4000 VN 0 VN M
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## 244 165000 US 100 US L
## 245 18053 IN 100 AS S
## 246 72212 GB 50 GB L
## 247 36643 FR 50 FR L
## 248 12103 TR 0 TR M
## 249 96282 GB 50 GB L
## 250 170000 US 100 US M
## 251 115000 US 50 US L
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## 253 600000 US 100 US L
## 254 28399 IN 100 IN M
## 255 93000 US 100 US L
## 256 99703 CA 50 CA M
## 257 200000 US 100 US L
## 258 173762 DE 100 DE M
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## 260 141846 DE 0 DE L
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## 262 63831 DE 50 DE L
## 263 16904 IN 100 IN S
## 264 66265 IN 0 IN L
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## 267 93150 US 0 US M
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## 270 65013 DE 50 DE M
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## 272 18907 BR 0 BR M
## 273 76833 DE 0 DE L
## 274 85000 NL 100 DE S
## 275 77684 FR 50 FR M
## 276 100000 US 100 US M
## 277 58000 US 50 US L
## 278 55000 ES 100 ES L
## 279 20171 TR 50 TR L
## 280 59102 LU 100 LU L
## 281 112000 US 100 US L
## 282 100000 JE 0 CN L
## 283 69741 NL 100 NL L
## 284 105000 US 100 US M
## 285 69999 CZ 50 CZ L
## 286 94665 IN 50 IN L
## 287 102839 SI 100 SI L
## 288 109000 US 50 US L
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## 290 135000 US 100 US M
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## 301 117789 GB 0 GB M
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## 305 52351 GB 100 GB M
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## 312 65438 GB 0 GB M
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## 315 52351 GB 0 GB M
## 316 165220 US 100 US M
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## 318 120160 US 100 US M
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## 430 39263 GB 100 GB M
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## 475 183228 GB 0 GB M
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## 482 65000 AE 100 AE S
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## 488 100000 DZ 50 DZ M
## 489 100000 CA 100 US M
## 490 31875 TN 100 CZ M
## 491 200000 MY 100 US M
## 492 75000 CA 100 CA S
## 493 35590 PL 100 PL L
## 494 78791 CA 100 CA M
## 495 100000 BR 100 US M
## 496 153000 US 50 US M
## 497 58035 PK 100 DE M
## 498 165000 US 100 US M
## 499 93427 FR 50 FR L
## 500 52396 CA 100 CA Lstr(df$salary)## chr [1:607] "70000" "260000" "85000" "20000" "150000" "72000" "190000" ...data ternyata dalam tipe character
# ubah tipe data
df$salary <- as.numeric(df$salary)
str(df$salary)## num [1:607] 70000 260000 85000 20000 150000 72000 190000 11000000 135000 125000 ...library(plotly)
density_salary <- density(df$salary)
plot_ly(
data = df,
x = ~salary,
type = "histogram"
)dens_salary <- density(log(df$salary))
plot_ly(
data = df,
x = ~log(salary),
type="histogram"
)describe(log(df$salary))## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 607 11.65 1.01 11.65 11.6 0.63 8.29 17.23 8.94 1.34 5.75 0.04# histogram dengan trace_line
plot_ly(
data = df,
x = ~log(salary),
type = "histogram",
name ="histogram"
)%>%add_lines(
x = dens_salary$x,
y = dens_salary$y * length(log(df$salary)),
name = "density line"
)# memasukan log ke df sebagai feature baru (asumsi saja jika permintaan kebutuhan data harus normal tidak homoskedastisitas, )
df$log_salary <- log(df$salary)
head(df)## X work_year experience_level employment_type job_title
## 1 0 2020 MI FT Data Scientist
## 2 1 2020 SE FT Machine Learning Scientist
## 3 2 2020 SE FT Big Data Engineer
## 4 3 2020 MI FT Product Data Analyst
## 5 4 2020 SE FT Machine Learning Engineer
## 6 5 2020 EN FT Data Analyst
## salary salary_currency salary_in_usd employee_residence remote_ratio
## 1 70000 EUR 79833 DE 0
## 2 260000 USD 260000 JP 0
## 3 85000 GBP 109024 GB 50
## 4 20000 USD 20000 HN 0
## 5 150000 USD 150000 US 50
## 6 72000 USD 72000 US 100
## company_location company_size log_salary
## 1 DE L 11.156251
## 2 JP S 12.468437
## 3 GB M 11.350407
## 4 HN S 9.903488
## 5 US L 11.918391
## 6 US L 11.184421Asumsi perbandingan salary berdasarkan job title
plot_ly(
data = df,
x = ~job_title,
y = ~salary,
type="bar"
)avg_salary <- df %>% group_by(job_title) %>% summarise(
salary_avg = mean(salary)
)
plot_ly(
data = avg_salary,
x = ~job_title,
y = ~salary_avg,
type = "bar",
marker = list(color=ifelse(avg_salary$job_title=="Head of Machine Learning","red","grey"))
)head(avg_salary,70)## # A tibble: 50 × 2
## job_title salary_avg
## <chr> <dbl>
## 1 3D Computer Vision Researcher 400000
## 2 AI Scientist 290571.
## 3 Analytics Engineer 175000
## 4 Applied Data Scientist 172400
## 5 Applied Machine Learning Scientist 141350
## 6 BI Data Analyst 1902045.
## 7 Big Data Architect 125000
## 8 Big Data Engineer 455000
## 9 Business Data Analyst 355000
## 10 Cloud Data Engineer 140000
## # ℹ 40 more rowsjob_filter <- df %>% filter(job_title %in% c("Head of Machine Learning", "Lead Data Scientist")) %>% group_by(job_title) %>%summarise(
salary_avgg = mean(salary),
salary_in_usd
)
plot_ly(
data = job_filter,
x = ~job_title,
y = ~salary_avgg,
marker = list(color="brown"),
type = "bar",
name = "salary avg"
)%>%add_trace(
x = ~job_title,
y = ~salary_in_usd,
marker = list(color="blue"),
name = "salary avg in USD"
)#plot_ly(
# data = df,
# x = ~salary,
# y = ~log_salary,
# type ="scatter",
# mode ="line"
#)#cor(df %>% select(salary, salary_in_usd, log_salary, remote_ratio), use="complete.obs")plot_ly(
data = df,
x = ~salary,
y = ~salary_in_usd,
type ="scatter"
)## No scatter mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plotly.com/r/reference/#scatter-modeplot_ly(
data = df,
x = ~job_title,
y = ~salary_in_usd,
type ="box"
#boxmean = TRUE
)#bisa dilihat ada oulier dan ……………….