Импортируйте CSV-файл в Jupyter Notebook с помощью панд - PullRequest
0 голосов
/ 04 сентября 2018

Мне нужна помощь со следующим:

Я пытался импортировать CSV-файл в свой блокнот Jupyter, но безрезультатно.

Код, который я использовал:

dfa = pd.read_csv ('Filename.csv')

И было выдано следующее сообщение об ошибке:

   ---------------------------------------------------------------------------
ParserError                               Traceback (most recent call last)
<ipython-input-3-164d461fc4d7> in <module>()
----> 1 dfa = pd.read_csv('Airpollution.csv')

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/io/parsers.py in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, doublequote, delim_whitespace, low_memory, memory_map, float_precision)
    676                     skip_blank_lines=skip_blank_lines)
    677 
--> 678         return _read(filepath_or_buffer, kwds)
    679 
    680     parser_f.__name__ = name

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds)
    444 
    445     try:
--> 446         data = parser.read(nrows)
    447     finally:
    448         parser.close()

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/io/parsers.py in read(self, nrows)
   1034                 raise ValueError('skipfooter not supported for iteration')
   1035 
-> 1036         ret = self._engine.read(nrows)
   1037 
   1038         # May alter columns / col_dict

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas/io/parsers.py in read(self, nrows)
   1846     def read(self, nrows=None):
   1847         try:
-> 1848             data = self._reader.read(nrows)
   1849         except StopIteration:
   1850             if self._first_chunk:

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader.read()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_low_memory()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._read_rows()

pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._tokenize_rows()

pandas/_libs/parsers.pyx in pandas._libs.parsers.raise_parser_error()

ParserError: Error tokenizing data. C error: Expected 1 fields in line 4, saw 11

Я проверил, что файлы открываются из одной и той же папки, и все они хранятся на моем рабочем столе.

У меня установлены панды, matplotlib и seaborn. Я перепробовал все способы (другие решения от Stackoverflow), но не смог понять, почему я не могу импортировать. Пожалуйста, просветите меня. Спасибо!

-

@ JPP: Другой CSV-файл смог работать это странно, так как я пытался использовать другой CSV-файл, и это сработало. я не могу загрузить эти файлы в.

я использую следующую информацию:

 Subject: Environment 
 Topic : Air Quality and Climate 
" Title  : M890641 - Air Pollution Levels, Annual "
, , , , , , , , , ,
 Variables , 2007 , 2008 , 2009 , 2010 , 2011 , 2012 , 2013 , 2014 , 2015 , 2016 ,
 Sulphur Dioxide (Annual Mean) (Microgram Per Cubic Metre) , 12 , 11 , 9 , 11 , 10 , 13 , 14 , 12 , 12 , 13 ,
 Sulphur Dioxide (Maximum 24-hour Mean) (Microgram Per Cubic Metre) , 84 , 80 , 93 , 104 , 80 , 98 , 75 , 83 , 75 , 61 ,
 Nitrogen Dioxide (Annual Mean) (Microgram Per Cubic Metre) , 22 , 22 , 22 , 23 , 25 , 25 , 25 , 24 , 22 , 26 ,
 Nitrogen Dioxide (Maximum 1-hour Mean) (Microgram Per Cubic Metre) , 177 , 126 , 147 , 153 , 189 , 154 , 132 , 121 , 99 , 123 ,
 Particulate Matter (PM10) (Annual Mean) (Microgram Per Cubic Metre) , 27 , 25 , 29 , 26 , 27 , 29 , 31 , 30 , 37 , 26 ,
 Particulate Matter (PM10) (99th Percentile 24-hour Mean) (Microgram Per Cubic Metre) , 53 , 49 , 59 , 76 , 55 , 57 , 215 , 75 , 186 , 61 ,
 Particulate Matter (PM2.5) (Annual Mean) (Microgram Per Cubic Metre) , 19 , 16 , 19 , 17 , 17 , 19 , 20 , 18 , 24 , 15 ,
 Particulate Matter (PM2.5) (99th Percentile 24-hour Mean) (Microgram Per Cubic Metre) , 37 , 32 , 44 , 56 , 41 , 42 , 176 , 51 , 145 , 40 ,
 Carbon Monoxide (Maximum 8-hour Mean) (Milligram Per Cubic Metre) , 1.7 , 1.6 , 1.9 , 2.4 , 2 , 1.9 , 5.5 , 1.8 , 3.3 , 2.2 ,
 Carbon Monoxide (Maximum 1-hour Mean) (Milligram Per Cubic Metre) , 2.5 , 2.3 , 3.9 , 2.8 , 2.6 , 2.4 , 7.5 , 2.7 , 3.5 , 2.7 ,
 Ozone (Maximum 8-hour Mean) (Microgram Per Cubic Metre) , 206 , 183 , 105 , 139 , 123 , 122 , 139 , 135 , 152 , 115 ,





SOURCE: NATIONAL ENVIRONMENT AGENCY




Generated by: SingStat Table Builder 
Date generated: 05/09/2018
Contact: info@singstat.gov.sg 

и это:

 Subject: Death and Life Expectancy 
 Topic : Death and Life Expectancy 
" Title  : M810131 - Deaths By Broad Groups Of Causes, Annual "
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,Number
 Variables , 1969 , 1970 , 1971 , 1972 , 1973 , 1974 , 1975 , 1976 , 1977 , 1978 , 1979 , 1980 , 1981 , 1982 , 1983 , 1984 , 1985 , 1986 , 1987 , 1988 , 1989 , 1990 , 1991 , 1992 , 1993 , 1994 , 1995 , 1996 , 1997 , 1998 , 1999 , 2000 , 2001 , 2002 , 2003 , 2004 , 2005 , 2006 , 2007 , 2008 , 2009 , 2010 , 2011 , 2012 , 2013 , 2014 , 2015 , 2016 , 2017 ,
 Total Deaths By Causes ," 10,224 "," 10,717 "," 11,329 "," 11,522 "," 11,920 "," 11,674 "," 11,447 "," 11,648 "," 11,955 "," 12,065 "," 12,468 "," 12,505 "," 12,863 "," 12,896 "," 13,321 "," 13,162 "," 13,348 "," 12,821 "," 13,173 "," 13,690 "," 14,069 "," 13,891 "," 13,876 "," 14,337 "," 14,461 "," 14,946 "," 15,569 "," 15,590 "," 15,305 "," 15,657 "," 15,516 "," 15,693 "," 15,367 "," 15,820 "," 16,036 "," 15,860 "," 16,215 "," 16,393 "," 17,140 "," 17,222 "," 17,101 "," 17,610 "," 18,027 "," 18,481 "," 18,938 "," 19,393 "," 19,862 "," 20,017 "," 20,905 ",
     Infective And Parasitic Diseases , 708 , 727 , 702 , 752 , 775 , 714 , 630 , 554 , 523 , 502 , 503 , 425 , 432 , 393 , 432 , 390 , 375 , 402 , 432 , 430 , 439 , 347 , 321 , 342 , 398 , 366 , 369 , 358 , 318 , 361 , 311 , 276 , 296 , 289 , 250 , 296 , 373 , 257 , 307 , 285 , 279 , 269 , 244 , 233 , 211 , 217 , 194 , 174 , 189 ,
         Tuberculosis , 419 , 458 , 439 , 489 , 450 , 472 , 420 , 358 , 340 , 318 , 331 , 240 , 221 , 207 , 224 , 163 , 177 , 177 , 186 , 168 , 132 , 113 , 104 , 101 , 115 , 101 , 118 , 132 , 115 , 128 , 107 , 101 , 104 , 92 , 79 , 79 , 67 , 66 , 85 , 83 , 75 , 77 , 68 , 65 , 51 , 60 , 41 , 41 , 32 ,
     Neoplasms ," 1,577 "," 1,633 "," 1,728 "," 1,821 "," 1,912 "," 2,002 "," 2,123 "," 2,278 "," 2,326 "," 2,415 "," 2,542 "," 2,623 "," 2,672 "," 2,729 "," 2,903 "," 2,817 "," 2,939 "," 2,921 "," 3,169 "," 3,233 "," 3,321 "," 3,314 "," 3,405 "," 3,497 "," 3,560 "," 3,785 "," 3,921 "," 4,034 "," 4,178 "," 4,091 "," 4,168 "," 4,278 "," 4,384 "," 4,465 "," 4,187 "," 4,353 "," 4,331 "," 4,722 "," 4,803 "," 5,081 "," 5,063 "," 5,078 "," 5,461 "," 5,651 "," 5,849 "," 5,790 "," 5,986 "," 5,993 "," 6,237 ",
         Malignant Neoplasms ," 1,533 "," 1,596 "," 1,688 "," 1,773 "," 1,863 "," 1,955 "," 2,083 "," 2,245 "," 2,286 "," 2,386 "," 2,488 "," 2,561 "," 2,616 "," 2,668 "," 2,858 "," 2,776 "," 2,893 "," 2,887 "," 3,131 "," 3,194 "," 3,283 "," 3,269 "," 3,361 "," 3,456 "," 3,531 "," 3,756 "," 3,898 "," 3,985 "," 4,128 "," 4,050 "," 4,134 "," 4,238 "," 4,339 "," 4,425 "," 4,146 "," 4,303 "," 4,289 "," 4,677 "," 4,745 "," 5,038 "," 5,010 "," 5,025 "," 5,411 "," 5,565 "," 5,775 "," 5,701 "," 5,903 "," 5,925 "," 6,077 ",
"     Endocrine, Nutritional And Metabolic Diseases ", 331 , 250 , 308 , 271 , 342 , 377 , 375 , 408 , 429 , 403 , 403 , 359 , 404 , 397 , 423 , 512 , 492 , 508 , 521 , 525 , 461 , 388 , 359 , 269 , 309 , 374 , 327 , 403 , 366 , 401 , 444 , 458 , 629 , 530 , 473 , 545 , 593 , 620 , 722 , 551 , 378 , 272 , 356 , 279 , 253 , 296 , 270 , 363 , 340 ,
         Diabetes , 184 , 134 , 212 , 207 , 247 , 257 , 259 , 334 , 377 , 334 , 347 , 319 , 368 , 361 , 373 , 469 , 464 , 479 , 492 , 501 , 419 , 332 , 320 , 238 , 264 , 334 , 271 , 320 , 282 , 308 , 350 , 355 , 512 , 425 , 373 , 474 , 510 , 536 , 609 , 463 , 290 , 182 , 299 , 268 , 247 , 277 , 250 , 343 , 321 ,
     Diseases Of The Blood And Blood-forming Organs , 71 , 51 , 60 , 50 , 61 , 60 , 52 , 32 , 50 , 45 , 41 , 31 , 42 , 33 , 33 , 28 , 29 , 30 , 35 , 35 , 48 , 50 , 40 , 33 , 34 , 24 , 37 , 37 , 44 , 35 , 50 , 54 , 52 , 44 , 39 , 33 , 40 , 36 , 31 , 46 , 30 , 41 , 41 , 20 , 14 , 23 , 10 , 14 , 17 ,
     Diseases Of The Nervous System And Sense Organs , 221 , 173 , 166 , 171 , 169 , 149 , 133 , 129 , 110 , 114 , 122 , 131 , 114 , 121 , 92 , 97 , 87 , 87 , 102 , 133 , 111 , 143 , 117 , 127 , 93 , 71 , 89 , 89 , 95 , 110 , 105 , 107 , 122 , 94 , 67 , 81 , 68 , 62 , 64 , 75 , 68 , 92 , 117 , 166 , 137 , 144 , 210 , 226 , 185 ,
     Diseases Of The Circulatory System ," 2,733 "," 2,899 "," 3,120 "," 2,999 "," 3,169 "," 3,295 "," 3,369 "," 3,798 "," 3,889 "," 3,983 "," 4,233 "," 4,305 "," 4,413 "," 4,430 "," 4,436 "," 4,637 "," 4,651 "," 4,482 "," 4,675 "," 4,847 "," 5,082 "," 5,152 "," 5,070 "," 5,270 "," 5,315 "," 5,460 "," 5,560 "," 5,896 "," 5,680 "," 5,711 "," 5,810 "," 5,749 "," 5,588 "," 5,401 "," 5,727 "," 5,423 "," 5,397 "," 5,441 "," 5,835 "," 5,794 "," 5,611 "," 5,807 "," 5,720 "," 5,747 "," 5,765 "," 5,987 "," 6,101 "," 6,107 "," 6,541 ",
         Heart And Hypertensive Diseases ," 1,761 "," 1,780 "," 1,925 "," 1,819 "," 1,967 "," 2,014 "," 2,000 "," 2,283 "," 2,426 "," 2,518 "," 2,752 "," 2,777 "," 2,892 "," 2,866 "," 2,911 "," 3,156 "," 3,129 "," 3,028 "," 3,251 "," 3,318 "," 3,416 "," 3,385 "," 3,234 "," 3,457 "," 3,552 "," 3,653 "," 3,742 "," 3,984 "," 3,943 "," 3,950 "," 4,061 "," 3,976 "," 4,075 "," 3,856 "," 4,067 "," 3,714 "," 3,656 "," 3,833 "," 4,197 "," 4,201 "," 4,081 "," 4,161 "," 3,920 "," 3,848 "," 3,914 "," 4,165 "," 4,534 "," 4,576 "," 4,970 ",
         Cerebrovascular Disease , 863 ," 1,038 "," 1,103 "," 1,080 "," 1,131 "," 1,213 "," 1,244 "," 1,427 "," 1,360 "," 1,382 "," 1,409 "," 1,447 "," 1,438 "," 1,469 "," 1,454 "," 1,413 "," 1,418 "," 1,355 "," 1,343 "," 1,414 "," 1,551 "," 1,666 "," 1,700 "," 1,697 "," 1,652 "," 1,692 "," 1,701 "," 1,805 "," 1,645 "," 1,633 "," 1,633 "," 1,625 "," 1,409 "," 1,393 "," 1,556 "," 1,562 "," 1,616 "," 1,462 "," 1,490 "," 1,435 "," 1,375 "," 1,472 "," 1,628 "," 1,714 "," 1,680 "," 1,620 "," 1,357 "," 1,317 "," 1,310 ",
     Diseases Of The Respiratory System ," 1,235 "," 1,473 "," 1,502 "," 1,653 "," 1,663 "," 1,631 "," 1,632 "," 1,651 "," 1,902 "," 1,724 "," 2,024 "," 1,965 "," 2,196 "," 2,257 "," 2,429 "," 2,096 "," 2,241 "," 1,974 "," 1,942 "," 2,110 "," 2,167 "," 2,112 "," 2,289 "," 2,522 "," 2,588 "," 2,564 "," 2,912 "," 2,534 "," 2,385 "," 2,579 "," 2,357 "," 2,505 "," 2,239 "," 2,763 "," 2,992 "," 2,851 "," 3,124 "," 2,913 "," 2,948 "," 2,989 "," 3,188 "," 3,434 "," 3,493 "," 3,708 "," 4,061 "," 4,232 "," 4,417 "," 4,440 "," 4,757 ",
         Pneumonia , 655 , 843 , 875 , 951 , 950 , 969 , 948 ," 1,010 "," 1,215 ", 942 ," 1,124 "," 1,129 "," 1,284 "," 1,375 "," 1,513 "," 1,204 "," 1,287 "," 1,082 ", 998 ," 1,039 "," 1,130 "," 1,191 "," 1,285 "," 1,420 "," 1,596 "," 1,670 "," 2,028 "," 1,693 "," 1,553 "," 1,780 "," 1,641 "," 1,794 "," 1,540 "," 2,079 "," 2,340 "," 2,232 "," 2,437 "," 2,244 "," 2,375 "," 2,387 "," 2,614 "," 2,766 "," 2,879 "," 3,096 "," 3,512 "," 3,680 "," 3,859 "," 3,855 "," 4,212 ",
     Diseases Of The Digestive System , 402 , 454 , 463 , 463 , 453 , 451 , 423 , 384 , 382 , 359 , 382 , 368 , 385 , 400 , 403 , 369 , 394 , 326 , 329 , 380 , 363 , 374 , 406 , 353 , 361 , 394 , 409 , 416 , 357 , 418 , 412 , 326 , 307 , 339 , 383 , 356 , 385 , 384 , 392 , 377 , 351 , 436 , 426 , 414 , 418 , 482 , 477 , 467 , 485 ,
     Diseases Of The Genito-urinary System , 234 , 239 , 252 , 279 , 275 , 320 , 311 , 281 , 324 , 381 , 349 , 366 , 366 , 319 , 375 , 405 , 319 , 343 , 393 , 380 , 370 , 346 , 369 , 362 , 371 , 444 , 483 , 444 , 399 , 494 , 470 , 486 , 487 , 594 , 587 , 641 , 634 , 637 , 739 , 753 , 861 , 893 , 918 , 934 , 967 , 951 , 928 , 913 , 925 ,
     Congenital Anomalies , 181 , 150 , 186 , 172 , 189 , 177 , 146 , 156 , 141 , 185 , 184 , 185 , 178 , 182 , 155 , 172 , 189 , 202 , 171 , 201 , 170 , 189 , 164 , 163 , 160 , 148 , 157 , 130 , 108 , 112 , 95 , 85 , 79 , 69 , 59 , 49 , 67 , 70 , 55 , 60 , 60 , 60 , 53 , 54 , 47 , 50 , 62 , 72 , 49 ,
         Congenital Anomalies Of Heart , 84 , 76 , 102 , 93 , 94 , 101 , 76 , 70 , 70 , 98 , 105 , 111 , 109 , 101 , 86 , 91 , 84 , 101 , 87 , 98 , 75 , 84 , 82 , 92 , 94 , 90 , 89 , 74 , 68 , 57 , 48 , 48 , 33 , 40 , 32 , 28 , 38 , 42 , 40 , 32 , 36 , 35 , 21 , 25 , 21 , 26 , 32 , 38 , 22 ,
     Certain Causes Of Perinatal Mortality , 460 , 463 , 455 , 502 , 477 , 322 , 254 , 221 , 247 , 239 , 261 , 227 , 208 , 215 , 149 , 151 , 147 , 128 , 128 , 127 , 135 , 123 , 89 , 82 , 76 , 68 , 51 , 64 , 61 , 62 , 52 , 48 , 24 , 52 , 41 , 22 , 39 , 43 , 32 , 39 , 49 , 34 , 49 , 44 , 43 , 42 , 30 , 36 , 39 ,
"     Accidents, Poisonings And Violence ", 811 , 836 , 968 , 982 , 995 , 894 , 887 , 890 , 914 ," 1,057 ", 876 , 899 , 938 , 966 ," 1,085 "," 1,095 "," 1,082 "," 1,025 ", 931 , 958 ," 1,042 "," 1,008 "," 1,074 "," 1,127 "," 1,066 "," 1,122 "," 1,113 "," 1,040 "," 1,187 "," 1,110 "," 1,066 "," 1,133 "," 1,036 "," 1,053 "," 1,062 "," 1,028 "," 1,017 "," 1,027 "," 1,036 "," 1,006 ", 978 , 973 , 989 ," 1,030 ", 933 , 909 , 895 , 890 , 840 ,
         Suicides , 188 , 185 , 230 , 235 , 240 , 229 , 252 , 257 , 224 , 266 , 249 , 271 , 191 , 239 , 267 , 211 , 327 , 329 , 302 , 367 , 395 , 354 , 319 , 298 , 296 , 347 , 401 , 271 , 346 , 371 , 309 , 348 , 357 , 361 , 346 , 381 , 405 , 419 , 374 , 364 , 401 , 353 , 361 , 467 , 422 , 415 , 409 , 429 , 361 ,
         Transport Accidents , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , na , 199 , 232 , 226 , 201 , 208 , 207 , 192 , 176 , 183 , 168 , 164 , 141 ,
     Other Diseases And Causes ," 1,260 "," 1,369 "," 1,419 "," 1,407 "," 1,440 "," 1,282 "," 1,112 ", 866 , 718 , 658 , 548 , 621 , 515 , 454 , 406 , 393 , 403 , 393 , 345 , 331 , 360 , 345 , 173 , 190 , 130 , 126 , 141 , 145 , 127 , 173 , 176 , 188 , 124 , 127 , 167 , 182 , 147 , 181 , 176 , 166 , 185 , 221 , 160 , 201 , 240 , 270 , 282 , 322 , 301 ,



"Deaths prior to 1979 are classified according to the eighth (1965) revision of the International Classification of Diseases.  Deaths from 1979 to 2011 are classified according to the ninth (1975) revision.  From 2012, deaths are classified according to the tenth revision."

SOURCE: REGISTRY OF BIRTHS AND DEATHS




Generated by: SingStat Table Builder 
Date generated: 05/09/2018
Contact: info@singstat.gov.sg 

Я не совсем уверен, имеет ли это какое-то отношение к файлу или настройкам на моем mac .. спасибо!

Ответы [ 2 ]

0 голосов
/ 04 сентября 2018

Вы можете пропустить плохие строки (несоответствующее количество полей):

dfa = pd.read_csv('Filename.csv',error_bad_lines=False) 
0 голосов
/ 04 сентября 2018

Вам следует рассмотреть возможность использования параметров, доступных для pd.read_csv. Например, вы можете указать разделители и пропустить строки. У вас есть пустой столбец в конце и мусор внизу, но это может быть обработано после чтения вашего файла.

Например:

df = pd.read_csv('file.csv', sep=' *, *', skiprows=4, engine='python')\
       .dropna(subset=['2007'])\
       .iloc[:, :-1]

print(df)

                                            Variables   2007   2008   2009  \
0   Sulphur Dioxide (Annual Mean) (Microgram Per C...   12.0   11.0    9.0   
1   Sulphur Dioxide (Maximum 24-hour Mean) (Microg...   84.0   80.0   93.0   
2   Nitrogen Dioxide (Annual Mean) (Microgram Per ...   22.0   22.0   22.0   
3   Nitrogen Dioxide (Maximum 1-hour Mean) (Microg...  177.0  126.0  147.0   
4   Particulate Matter (PM10) (Annual Mean) (Micro...   27.0   25.0   29.0   
5   Particulate Matter (PM10) (99th Percentile 24-...   53.0   49.0   59.0   
6   Particulate Matter (PM2.5) (Annual Mean) (Micr...   19.0   16.0   19.0   
7   Particulate Matter (PM2.5) (99th Percentile 24...   37.0   32.0   44.0   
8   Carbon Monoxide (Maximum 8-hour Mean) (Milligr...    1.7    1.6    1.9   
9   Carbon Monoxide (Maximum 1-hour Mean) (Milligr...    2.5    2.3    3.9   
10  Ozone (Maximum 8-hour Mean) (Microgram Per Cub...  206.0  183.0  105.0   

     2010   2011   2012   2013   2014   2015   2016  
0    11.0   10.0   13.0   14.0   12.0   12.0   13.0  
1   104.0   80.0   98.0   75.0   83.0   75.0   61.0  
2    23.0   25.0   25.0   25.0   24.0   22.0   26.0  
3   153.0  189.0  154.0  132.0  121.0   99.0  123.0  
4    26.0   27.0   29.0   31.0   30.0   37.0   26.0  
5    76.0   55.0   57.0  215.0   75.0  186.0   61.0  
6    17.0   17.0   19.0   20.0   18.0   24.0   15.0  
7    56.0   41.0   42.0  176.0   51.0  145.0   40.0  
8     2.4    2.0    1.9    5.5    1.8    3.3    2.2  
9     2.8    2.6    2.4    7.5    2.7    3.5    2.7  
10  139.0  123.0  122.0  139.0  135.0  152.0  115.0  
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