diff --git a/pandas/tests/io/data/html/computer_sales_page.html b/pandas/tests/io/data/html/computer_sales_page.html deleted file mode 100644 index ff2b031b58d64..0000000000000 --- a/pandas/tests/io/data/html/computer_sales_page.html +++ /dev/null @@ -1,619 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 
 Three months ended
-April 30 		 Six months ended
-April 30 		 
 
 2013  2012  2013  2012  
 
 In millions
 

Net revenue:

             

Notebooks

 $3,718 $4,900 $7,846 $9,842 

Desktops

  3,103  3,827  6,424  7,033 

Workstations

  521  537  1,056  1,072 

Other

  242  206  462  415 
          

Personal Systems

  7,584  9,470  15,788  18,362 
          

Supplies

  4,122  4,060  8,015  8,139 

Commercial Hardware

  1,398  1,479  2,752  2,968 

Consumer Hardware

  561  593  1,240  1,283 
          

Printing

  6,081  6,132  12,007  12,390 
          

Printing and Personal Systems Group

  13,665  15,602  27,795  30,752 
          

Industry Standard Servers

  2,806  3,186  5,800  6,258 

Technology Services

  2,272  2,335  4,515  4,599 

Storage

  857  990  1,690  1,945 

Networking

  618  614  1,226  1,200 

Business Critical Systems

  266  421  572  826 
          

Enterprise Group

  6,819  7,546  13,803  14,828 
          

Infrastructure Technology Outsourcing

  3,721  3,954  7,457  7,934 

Application and Business Services

  2,278  2,535  4,461  4,926 
          

Enterprise Services

  5,999  6,489  11,918  12,860 
          

Software

  941  970  1,867  1,916 

HP Financial Services

  881  968  1,838  1,918 

Corporate Investments

  10  7  14  37 
          

Total segments

  28,315  31,582  57,235  62,311 
          

Eliminations of intersegment net revenue and other

  (733) (889) (1,294) (1,582)
          

Total HP consolidated net revenue

 $27,582 $30,693 $55,941 $60,729 
          
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Traffic Statistics - Passengers

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- Passengers Figure(2008-2013)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  201320122011201020092008
January - - 374,917 - - - 362,379 - - - 301,503 - - - 358,902 - - - 342,323 - - - 420,574 -
February - - 393,152 - - - 312,405 - - - 301,259 - - - 351,654 - - - 297,755 - - - 442,809 -
March - - 408,755 - - - 334,000 - - - 318,908 - - - 360,365 - - - 387,879 - - - 468,540 -
April - - 408,860 - - - 358,198 - - - 339,060 - - - 352,976 - - - 400,553 - - - 492,930 -
May - - 374,397 - - - 329,218 - - - 321,060 - - - 330,407 - - - 335,967 - - - 465,045 -
June - - 401,995 - - - 356,679 - - - 343,006 - - - 326,724 - - - 296,748 - - - 426,764 -
July - - - - - 423,081 - - - 378,993 - - - 356,580 - - - 351,110 - - - 439,425 -
August - - - - - 453,391 - - - 395,883 - - - 364,011 - - - 404,076 - - - 425,814 -
September - - - - - 384,887 - - - 325,124 - - - 308,940 - - - 317,226 - - - 379,898 -
October - - - - - 383,889 - - - 333,102 - - - 317,040 - - - 355,935 - - - 415,339 -
November - - - - - 379,065 - - - 327,803 - - - 303,186 - - - 372,104 - - - 366,411 -
December - - - - - 413,873 - - - 359,313 - - - 348,051 - - - 388,573 - - - 354,253 -
Total - - 2,362,076 - - - 4,491,065 - - - 4,045,014 - - - 4,078,836 - - - 4,250,249 - - - 5,097,802 -
- -


- Passengers Figure(2002-2007)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  200720062005200420032002
January - - 381,887 - - - 323,282 - - - 289,701 - - - 288,507 - - - 290,140 - - - 268,783 -
February - - 426,014 - - - 360,820 - - - 348,723 - - - 207,710 - - - 323,264 - - - 323,654 -
March - - 443,805 - - - 389,125 - - - 321,953 - - - 273,910 - - - 295,052 - - - 360,668 -
April - - 500,917 - - - 431,550 - - - 367,976 - - - 324,931 - - - 144,082 - - - 380,648 -
May - - 468,637 - - - 399,743 - - - 359,298 - - - 250,601 - - - 47,333 - - - 359,547 -
June - - 463,676 - - - 393,713 - - - 360,147 - - - 296,000 - - - 94,294 - - - 326,508 -
July - - 490,404 - - - 465,497 - - - 413,131 - - - 365,454 - - - 272,784 - - - 388,061 -
August - - 490,830 - - - 478,474 - - - 409,281 - - - 372,802 - - - 333,840 - - - 384,719 -
September - - 446,594 - - - 412,444 - - - 354,751 - - - 321,456 - - - 295,447 - - - 334,029 -
October - - 465,757 - - - 461,215 - - - 390,435 - - - 358,362 - - - 291,193 - - - 372,706 -
November - - 455,132 - - - 425,116 - - - 323,347 - - - 327,593 - - - 268,282 - - - 350,324 -
December - - 465,225 - - - 435,114 - - - 308,999 - - - 326,933 - - - 249,855 - - - 322,056 -
Total - - 5,498,878 - - - 4,976,093 - - - 4,247,742 - - - 3,714,259 - - - 2,905,566 - - - 4,171,703 -
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- Passengers Figure(1996-2001)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  200120001999199819971996
January - - 265,603 - - - 184,381 - - - 161,264 - - - 161,432 - - - 117,984 - - - -
February - - 249,259 - - - 264,066 - - - 209,569 - - - 168,777 - - - 150,772 - - - -
March - - 312,319 - - - 226,483 - - - 186,965 - - - 172,060 - - - 149,795 - - - -
April - - 351,793 - - - 296,541 - - - 237,449 - - - 180,241 - - - 179,049 - - - -
May - - 338,692 - - - 288,949 - - - 230,691 - - - 172,391 - - - 189,925 - - - -
June - - 332,630 - - - 271,181 - - - 231,328 - - - 157,519 - - - 175,402 - - - -
July - - 344,658 - - - 304,276 - - - 243,534 - - - 205,595 - - - 173,103 - - - -
August - - 360,899 - - - 300,418 - - - 257,616 - - - 241,140 - - - 178,118 - - - -
September - - 291,817 - - - 280,803 - - - 210,885 - - - 183,954 - - - 163,385 - - - -
October - - 327,232 - - - 298,873 - - - 231,251 - - - 205,726 - - - 176,879 - - - -
November - - 315,538 - - - 265,528 - - - 228,637 - - - 181,677 - - - 146,804 - - - -
December - - 314,866 - - - 257,929 - - - 210,922 - - - 183,975 - - - 151,362 - - - -
Total - - 3,805,306 - - - 3,239,428 - - - 2,640,111 - - - 2,214,487 - - - 1,952,578 - - - 0 -
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- Passengers Figure(1995-1995)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  1995
January - - -
February - - -
March - - -
April - - -
May - - -
June - - -
July - - -
August - - -
September - - -
October - - -
November - - 6,601 -
December - - 37,041 -
Total - - 43,642 -
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- Movement Statistics(2008-2013)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  201320122011201020092008
January - - 3,925 - - - 3,463 - - - 3,289 - - - 3,184 - - - 3,488 - - - 4,568 -
February - - 3,632 - - - 2,983 - - - 2,902 - - - 3,053 - - - 3,347 - - - 4,527 -
March - - 3,909 - - - 3,166 - - - 3,217 - - - 3,175 - - - 3,636 - - - 4,594 -
April - - 3,903 - - - 3,258 - - - 3,146 - - - 3,023 - - - 3,709 - - - 4,574 -
May - - 4,075 - - - 3,234 - - - 3,266 - - - 3,033 - - - 3,603 - - - 4,511 -
June - - 4,038 - - - 3,272 - - - 3,316 - - - 2,909 - - - 3,057 - - - 4,081 -
July - - - - - 3,661 - - - 3,359 - - - 3,062 - - - 3,354 - - - 4,215 -
August - - - - - 3,942 - - - 3,417 - - - 3,077 - - - 3,395 - - - 4,139 -
September - - - - - 3,703 - - - 3,169 - - - 3,095 - - - 3,100 - - - 3,752 -
October - - - - - 3,727 - - - 3,469 - - - 3,179 - - - 3,375 - - - 3,874 -
November - - - - - 3,722 - - - 3,145 - - - 3,159 - - - 3,213 - - - 3,567 -
December - - - - - 3,866 - - - 3,251 - - - 3,199 - - - 3,324 - - - 3,362 -
Total - - 23,482 - - - 41,997 - - - 38,946 - - - 37,148 - - - 40,601 - - - 49,764 -
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- Movement Statistics(2002-2007)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  200720062005200420032002
January - - 4,384 - - - 3,933 - - - 3,528 - - - 3,051 - - - 3,257 - - - 2,711 -
February - - 4,131 - - - 3,667 - - - 3,331 - - - 2,372 - - - 3,003 - - - 2,747 -
March - - 4,349 - - - 4,345 - - - 3,549 - - - 3,049 - - - 3,109 - - - 2,985 -
April - - 4,460 - - - 4,490 - - - 3,832 - - - 3,359 - - - 2,033 - - - 2,928 -
May - - 4,629 - - - 4,245 - - - 3,663 - - - 3,251 - - - 1,229 - - - 3,109 -
June - - 4,365 - - - 4,124 - - - 3,752 - - - 3,414 - - - 1,217 - - - 3,049 -
July - - 4,612 - - - 4,386 - - - 3,876 - - - 3,664 - - - 2,423 - - - 3,078 -
August - - 4,446 - - - 4,373 - - - 3,987 - - - 3,631 - - - 3,040 - - - 3,166 -
September - - 4,414 - - - 4,311 - - - 3,782 - - - 3,514 - - - 2,809 - - - 3,239 -
October - - 4,445 - - - 4,455 - - - 3,898 - - - 3,744 - - - 3,052 - - - 3,562 -
November - - 4,563 - - - 4,285 - - - 3,951 - - - 3,694 - - - 3,125 - - - 3,546 -
December - - 4,588 - - - 4,435 - - - 3,855 - - - 3,763 - - - 2,996 - - - 3,444 -
Total - - 53,386 - - - 51,049 - - - 45,004 - - - 40,506 - - - 31,293 - - - 37,564 -
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- Movement Statistics(1996-2001)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  200120001999199819971996
January - - 2,694 - - - 2,201 - - - 1,835 - - - 2,177 - - - 1,353 - - - 744 -
February - - 2,364 - - - 2,357 - - - 1,826 - - - 1,740 - - - 1,339 - - - 692 -
March - - 2,543 - - - 2,206 - - - 1,895 - - - 1,911 - - - 1,533 - - - 872 -
April - - 2,531 - - - 2,311 - - - 2,076 - - - 1,886 - - - 1,587 - - - 1,026 -
May - - 2,579 - - - 2,383 - - - 1,914 - - - 2,102 - - - 1,720 - - - 1,115 -
June - - 2,681 - - - 2,370 - - - 1,890 - - - 2,038 - - - 1,716 - - - 1,037 -
July - - 2,903 - - - 2,609 - - - 1,916 - - - 2,078 - - - 1,693 - - - 1,209 -
August - - 3,037 - - - 2,487 - - - 1,968 - - - 2,061 - - - 1,676 - - - 1,241 -
September - - 2,767 - - - 2,329 - - - 1,955 - - - 1,970 - - - 1,681 - - - 1,263 -
October - - 2,922 - - - 2,417 - - - 2,267 - - - 1,969 - - - 1,809 - - - 1,368 -
November - - 2,670 - - - 2,273 - - - 2,132 - - - 2,102 - - - 1,786 - - - 1,433 -
December - - 2,815 - - - 2,749 - - - 2,187 - - - 1,981 - - - 1,944 - - - 1,386 -
Total - - 32,506 - - - 28,692 - - - 23,861 - - - 24,015 - - - 19,837 - - - 13,386 -
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- Movement Statistics(1995-1995)

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  1995
January - - -
February - - -
March - - -
April - - -
May - - -
June - - -
July - - -
August - - -
September - - -
October - - -
November - - 126 -
December - - 536 -
Total - - 662 -
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 Issue(Roll over for charts and headlines) - VolumePriceChg% Chg
1 - J.C. Penney (JCP) - - 250,697,455$9.05-1.37-13.15
2 - Bank of America (BAC) - - 77,162,10313.90-0.18-1.28
3 - Rite Aid (RAD) - - 52,140,3824.70-0.08-1.67
4 - Ford Motor (F) - - 33,745,28717.05-0.22-1.27
5 - Pfizer (PFE) - - 27,801,85328.880.361.26
6 - Hertz Global Hldgs (HTZ) - - 25,821,26422.320.693.19
7 - General Electric (GE) - - 25,142,06424.05-0.20-0.82
8 - Elan ADS (ELN) - - 24,725,20915.590.080.52
9 - JPMorgan Chase (JPM) - - 22,402,75652.240.350.67
10 - Regions Financial (RF) - - 20,790,5329.300.121.31
11 - Violin Memory (VMEM) - - 20,669,8467.02-1.98-22.00
12 - Citigroup (C) - - 19,979,93248.89-0.04-0.08
13 - Nokia ADS (NOK) - - 19,585,0756.660.020.30
14 - Wells Fargo (WFC) - - 19,478,59041.59-0.02-0.05
15 - Vale ADS (VALE) - - 18,781,98715.60-0.52-3.23
16 - Delta Air Lines (DAL) - - 16,013,95623.57-0.44-1.83
17 - EMC (EMC) - - 15,771,25226.07-0.11-0.42
18 - Nike Cl B (NKE) - - 15,514,71773.643.304.69
19 - Alcoa (AA) - - 14,061,0738.20-0.07-0.85
20 - General Motors (GM) - - 13,984,00436.37-0.58-1.57
21 - Oracle (ORCL) - - 13,856,67133.78-0.03-0.09
22 - AT&T (T) - - 13,736,94833.98-0.25-0.73
23 - Trina Solar ADS (TSL) - - 13,284,20214.831.9915.50
24 - Yingli Green Energy Holding ADS (YGE) - - 12,978,3786.730.6310.33
25 - Petroleo Brasileiro ADS (PBR) - - 12,833,66015.40-0.21-1.35
26 - United Continental Holdings (UAL) - - 12,603,22530.91-3.16-9.28
27 - Coca-Cola (KO) - - 12,343,45238.40-0.34-0.88
28 - Arch Coal (ACI) - - 12,261,1384.25-0.28-6.18
29 - Morgan Stanley (MS) - - 11,956,34527.08-0.07-0.26
30 - Pandora Media (P) - - 11,829,96325.520.130.51
31 - Barrick Gold (ABX) - - 11,775,58518.530.000.00
32 - Abbott Laboratories (ABT) - - 11,755,71833.14-0.52-1.54
33 - Banco Santander Brasil ADS (BSBR) - - 11,587,3107.010.467.02
34 - Advanced Micro Devices (AMD) - - 11,337,6093.86-0.03-0.77
35 - Annaly Capital Management (NLY) - - 11,004,44011.63-0.07-0.60
36 - Alpha Natural Resources (ANR) - - 10,941,0746.08-0.19-3.03
37 - Exxon Mobil (XOM) - - 10,668,11586.90-0.17-0.20
38 - Itau Unibanco Holding ADS (ITUB) - - 10,638,80314.300.231.63
39 - Merck&Co (MRK) - - 10,388,15247.790.110.23
40 - Alcatel-Lucent ADS (ALU) - - 10,181,8333.650.010.27
41 - Verizon Communications (VZ) - - 10,139,32147.00-0.67-1.41
42 - Magnum Hunter Resources (MHR) - - 10,004,3036.330.467.84
43 - Hewlett-Packard (HPQ) - - 9,948,93521.17-0.13-0.61
44 - PulteGroup (PHM) - - 9,899,14116.57-0.41-2.41
45 - ReneSola ADS (SOL) - - 9,667,4384.840.398.76
46 - Corning (GLW) - - 9,547,26514.73-0.21-1.41
47 - Cole Real Estate Investments (COLE) - - 9,544,02112.210.010.08
48 - Dow Chemical (DOW) - - 9,150,47939.02-0.97-2.43
49 - International Game Technology (IGT) - - 9,129,12319.23-1.44-6.97
50 - Accenture Cl A (ACN) - - 8,773,26074.09-1.78-2.35
51 - KeyCorp (KEY) - - 8,599,33311.360.020.18
52 - Bristol-Myers Squibb (BMY) - - 8,440,70946.20-0.73-1.56
53 - Companhia Siderurgica Nacional ADS (SID) - - 8,437,6364.36-0.05-1.13
54 - H&R Block (HRB) - - 8,240,98426.360.311.19
55 - MGIC Investment (MTG) - - 8,135,0377.26-0.10-1.36
56 - RingCentral Cl A (RNG) - - 8,117,46918.205.2040.00
57 - United States Steel (X) - - 8,107,89920.44-0.66-3.13
58 - Cliffs Natural Resources (CLF) - - 8,041,57221.00-0.83-3.80
59 - Newmont Mining (NEM) - - 8,014,25027.98-0.19-0.67
60 - Altria Group (MO) - - 7,786,04834.71-0.29-0.83
61 - SandRidge Energy (SD) - - 7,782,7455.93-0.06-1.00
62 - Molycorp (MCP) - - 7,735,8316.73-0.45-6.27
63 - Halliburton (HAL) - - 7,728,73548.39-0.32-0.66
64 - Taiwan Semiconductor Manufacturing ADS (TSM) - - 7,661,39717.07-0.25-1.44
65 - Freeport-McMoRan Copper&Gold (FCX) - - 7,622,80333.42-0.45-1.33
66 - Kodiak Oil&Gas (KOG) - - 7,543,80611.940.161.36
67 - Xerox (XRX) - - 7,440,68910.37-0.01-0.10
68 - Sprint (S) - - 7,291,3516.16-0.14-2.22
69 - Two Harbors Investment (TWO) - - 7,153,8039.790.050.51
70 - Walter Energy (WLT) - - 7,152,19214.19-0.36-2.47
71 - International Paper (IP) - - 7,123,72245.44-1.85-3.91
72 - PPL (PPL) - - 7,026,29230.34-0.13-0.43
73 - Goldcorp (GG) - - 6,857,44725.760.080.31
74 - Time Warner (TWX) - - 6,807,23766.201.332.05
75 - Synovus Financial (SNV) - - 6,764,8053.290.020.61
76 - AK Steel Holding (AKS) - - 6,662,5993.83-0.11-2.79
77 - Boston Scientific (BSX) - - 6,629,08411.52-0.15-1.29
78 - Eldorado Gold (EGO) - - 6,596,9026.65-0.03-0.45
79 - Newpark Resources (NR) - - 6,552,45312.560.090.72
80 - AbbVie (ABBV) - - 6,525,52444.33-0.67-1.49
81 - MBIA (MBI) - - 6,416,58710.38-0.43-3.98
82 - SAIC (SAI) - - 6,404,58716.030.130.82
83 - Procter&Gamble (PG) - - 6,389,14377.21-0.84-1.08
84 - IAMGOLD (IAG) - - 6,293,0014.77-0.06-1.24
85 - Safeway (SWY) - - 6,268,18432.25-0.29-0.89
86 - Kinross Gold (KGC) - - 6,112,6584.99-0.03-0.60
87 - MGM Resorts International (MGM) - - 5,986,14320.22-0.05-0.25
88 - Cemex ADS (CX) - - 5,907,04011.27-0.06-0.53
89 - American International Group (AIG) - - 5,900,13349.15-0.30-0.61
90 - Chesapeake Energy (CHK) - - 5,848,01626.21-0.20-0.76
91 - RadioShack (RSH) - - 5,837,8333.44-0.43-11.11
92 - U.S. Bancorp (USB) - - 5,814,37336.50-0.04-0.11
93 - Eli Lilly (LLY) - - 5,776,99150.50-0.54-1.06
94 - MetLife (MET) - - 5,774,99647.21-0.37-0.78
95 - Yamana Gold (AUY) - - 5,742,42610.370.030.29
96 - CBS Cl B (CBS) - - 5,718,85855.50-0.06-0.11
97 - CSX (CSX) - - 5,710,06625.85-0.13-0.50
98 - Carnival (CCL) - - 5,661,32532.88-0.05-0.15
99 - Mosaic (MOS) - - 5,595,59243.43-0.76-1.72
100 - Walgreen (WAG) - - 5,568,31054.51-0.22-0.40
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diff --git a/pandas/tests/io/test_html.py b/pandas/tests/io/test_html.py index 7a814ce82fd73..b649e394c780b 100644 --- a/pandas/tests/io/test_html.py +++ b/pandas/tests/io/test_html.py @@ -14,7 +14,7 @@ from pandas.errors import ParserError import pandas.util._test_decorators as td -from pandas import DataFrame, Index, MultiIndex, Series, Timestamp, date_range, read_csv +from pandas import DataFrame, MultiIndex, Series, Timestamp, date_range, read_csv import pandas._testing as tm from pandas.io.common import file_path_to_url @@ -373,32 +373,6 @@ def test_python_docs_table(self): zz = [df.iloc[0, 0][0:4] for df in dfs] assert sorted(zz) == sorted(["Repo", "What"]) - @pytest.mark.slow - def test_thousands_macau_stats(self, datapath): - all_non_nan_table_index = -2 - macau_data = datapath("io", "data", "html", "macau.html") - dfs = self.read_html(macau_data, index_col=0, attrs={"class": "style1"}) - df = dfs[all_non_nan_table_index] - - assert not any(s.isna().any() for _, s in df.items()) - - @pytest.mark.slow - def test_thousands_macau_index_col(self, datapath, request): - # https://github.com/pandas-dev/pandas/issues/29622 - # This tests fails for bs4 >= 4.8.0 - so handle xfail accordingly - if self.read_html.keywords.get("flavor") == "bs4" and td.safe_import( - "bs4", "4.8.0" - ): - reason = "fails for bs4 version >= 4.8.0" - request.node.add_marker(pytest.mark.xfail(reason=reason)) - - all_non_nan_table_index = -2 - macau_data = datapath("io", "data", "html", "macau.html") - dfs = self.read_html(macau_data, index_col=0, header=0) - df = dfs[all_non_nan_table_index] - - assert not any(s.isna().any() for _, s in df.items()) - def test_empty_tables(self): """ Make sure that read_html ignores empty tables. @@ -571,23 +545,6 @@ def test_parse_header_of_non_string_column(self): tm.assert_frame_equal(result, expected) - def test_nyse_wsj_commas_table(self, datapath): - data = datapath("io", "data", "html", "nyse_wsj.html") - df = self.read_html(data, index_col=0, header=0, attrs={"class": "mdcTable"})[0] - - expected = Index( - [ - "Issue(Roll over for charts and headlines)", - "Volume", - "Price", - "Chg", - "% Chg", - ] - ) - nrows = 100 - assert df.shape[0] == nrows - tm.assert_index_equal(df.columns, expected) - @pytest.mark.slow def test_banklist_header(self, datapath): from pandas.io.html import _remove_whitespace @@ -894,24 +851,23 @@ def test_parse_dates_combine(self): newdf = DataFrame({"datetime": raw_dates}) tm.assert_frame_equal(newdf, res[0]) - def test_computer_sales_page(self, datapath): - data = datapath("io", "data", "html", "computer_sales_page.html") - msg = ( - r"Passed header=\[0,1\] are too many " - r"rows for this multi_index of columns" - ) - with pytest.raises(ParserError, match=msg): - self.read_html(data, header=[0, 1]) - - data = datapath("io", "data", "html", "computer_sales_page.html") - assert self.read_html(data, header=[1, 2]) - def test_wikipedia_states_table(self, datapath): data = datapath("io", "data", "html", "wikipedia_states.html") assert os.path.isfile(data), f"{repr(data)} is not a file" assert os.path.getsize(data), f"{repr(data)} is an empty file" result = self.read_html(data, "Arizona", header=1)[0] + assert result.shape == (60, 12) + assert "Unnamed" in result.columns[-1] assert result["sq mi"].dtype == np.dtype("float64") + assert np.allclose(result.loc[0, "sq mi"], 665384.04) + + def test_wikipedia_states_multiindex(self, datapath): + data = datapath("io", "data", "html", "wikipedia_states.html") + result = self.read_html(data, "Arizona", index_col=0)[0] + assert result.shape == (60, 11) + assert "Unnamed" in result.columns[-1][1] + assert result.columns.nlevels == 2 + assert np.allclose(result.loc["Alaska", ("Total area[2]", "sq mi")], 665384.04) def test_parser_error_on_empty_header_row(self): msg = (