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  1. symbols.f <- c("NVDA.f", "GOOG.f", "GE.f")
  2.  
  3. [1] "GE.f.12.31.2017"
  4. [2] "GE.f.12.31.2016"
  5. [3] "GE.f.12.31.2015"
  6. [4] "GE.f.12.31.2014"
  7. [5] "GOOG.f.12.31.2017"
  8. [6] "GOOG.f.12.31.2016"
  9. [7] "GOOG.f.12.31.2015"
  10. [8] "GOOG.f.12.31.2014"
  11. [9] "NVDA.f.1.28.2018"
  12. [10] "NVDA.f.1.29.2017"
  13. [11] "NVDA.f.1.31.2016"
  14. [12] "NVDA.f.1.25.2015"
  15.  
  16. [1] "GE2017"
  17. [2] "GE2016"
  18. [3] "GE2015"
  19. [4] "GE2014"
  20. [5] "GOOG2017"
  21. [6] "GOOG2016"
  22. [7] "GOOG2015"
  23. [8] "GOOG2014"
  24.  
  25. df <- structure(list(GE.f.12.31.2017 = c(18211000, NA, 46549000, 21923000,
  26. 5790000, 140110000, 38696000, 53874000, 83968000, 20273000, NA,
  27. 41024000, 6207000, 377945000, 15153000, 134591000, 21400000,
  28. 61893000, 108575000, 82597000, NA, 21122000, NA, 292560000, NA,
  29. NA, NA, 702000, 125682000, -62127000, NA, 22775000, 64257000,
  30. -39984000), GE.f.12.31.2016 = c(10525000, NA, 42687000, 22354000,
  31. 2867000, 149029000, 44313000, 50518000, 68070000, 16436000, NA,
  32. 34449000, 1833000, 365183000, 14435000, 136211000, 20772000,
  33. 70364000, 105080000, 83040000, NA, 4688000, NA, 284667000, NA,
  34. NA, NA, 702000, 139532000, -64412000, NA, 18626000, 75822000,
  35. -11052000), GE.f.12.31.2015 = c(10372000, NA, 43013000, 22515000,
  36. 5109000, 280896000, 31973000, 54095000, 65526000, 17797000, NA,
  37. 42784000, 3105000, 493071000, 13680000, 197602000, 27453000,
  38. 138270000, 144659000, 79175000, NA, 4836000, NA, 389961000, NA,
  39. NA, NA, 702000, 140020000, -42454000, NA, 21085000, 98268000,
  40. 14945000), GE.f.12.31.2014 = c(15916000, NA, 23237000, 17639000,
  41. 6566000, 460743000, 35505000, 48070000, 53207000, 13182000, NA,
  42. 44247000, 6183000, 654954000, 12067000, 261424000, 18203000,
  43. 229564000, 186596000, 70801000, NA, 8772000, NA, 518023000, NA,
  44. NA, NA, 702000, 155333000, -27876000, NA, 14717000, 128159000,
  45. 61770000), GOOG.f.12.31.2017 = c(10715000, 91156000, 18705000,
  46. 749000, 2983000, 124308000, 7813000, 42383000, 16747000, 2692000,
  47. NA, 3352000, 680000, 197295000, 3137000, 3969000, 10651000, 24183000,
  48. 3943000, 16641000, NA, NA, NA, 44793000, NA, NA, NA, 40247000,
  49. 113247000, -992000, NA, -992000, 152502000, 133063000), GOOG.f.12.31.2016 = c(12918000,
  50. 73415000, 15632000, 268000, 3175000, 105408000, 5878000, 34234000,
  51. 16468000, 3307000, NA, 2202000, 383000, 167497000, 2041000, 3935000,
  52. 5851000, 16756000, 3935000, 7770000, NA, NA, NA, 28461000, NA,
  53. NA, NA, 36307000, 105131000, -2402000, NA, -2402000, 139036000,
  54. 119261000), GOOG.f.12.31.2015 = c(15409000, 56517000, 13459000,
  55. 491000, 1590000, 90114000, 5183000, 29016000, 15869000, 3847000,
  56. NA, 3432000, 251000, 147461000, 1931000, 7648000, 4327000, 19310000,
  57. 1995000, 5825000, NA, NA, NA, 27130000, NA, NA, NA, 32982000,
  58. 89223000, -1874000, NA, -1874000, 120331000, 100615000), GOOG.f.12.31.2014 = c(16585000,
  59. 46048000, 9974000, NA, 2637000, 78656000, 3079000, 23883000,
  60. 15599000, 4607000, NA, 3363000, 176000, 129187000, 1715000, 8015000,
  61. 2803000, 16779000, 2992000, 5320000, NA, NA, NA, 25327000, NA,
  62. NA, NA, 28767000, 75066000, 27000, NA, 27000, 103860000, 83654000
  63. ), NVDA.f.1.28.2018 = c(7108000, NA, 1265000, 796000, NA, 9255000,
  64. NA, 997000, 618000, 52000, NA, 319000, NA, 11241000, 596000,
  65. 2e+06, NA, 1153000, 1985000, 632000, NA, NA, NA, 3770000, NA,
  66. NA, NA, 7471000, NA, NA, NA, NA, 7471000, 6801000), NVDA.f.1.29.2017 = c(1766000,
  67. 5032000, 826000, 794000, NA, 8536000, NA, 521000, 618000, 104000,
  68. NA, 62000, NA, 9841000, 485000, 2791000, 325000, 1788000, 1985000,
  69. 3e+05, NA, NA, NA, 4079000, NA, NA, NA, 1000, 6108000, -5055000,
  70. 4708000, -16000, 5762000, 5040000), NVDA.f.1.31.2016 = c(596000,
  71. 4441000, 505000, 418000, NA, 6053000, NA, 466000, 618000, 166000,
  72. NA, 67000, NA, 7370000, 296000, 1434000, 532000, 2351000, 7000,
  73. 533000, NA, NA, NA, 2901000, NA, NA, NA, 1000, 4350000, -4052000,
  74. 4170000, -4000, 4469000, 3685000), NVDA.f.1.25.2015 = c(497000,
  75. 4126000, 474000, 483000, 63000, 5713000, NA, 557000, 618000,
  76. 222000, NA, 91000, NA, 7201000, 293000, 1398000, 471000, 896000,
  77. 1384000, 489000, NA, NA, NA, 2783000, NA, NA, NA, 1000, 3949000,
  78. -3387000, 3855000, 8000, 4418000, 3578000)), .Names = c("GE.f.12.31.2017",
  79. "GE.f.12.31.2016", "GE.f.12.31.2015", "GE.f.12.31.2014", "GOOG.f.12.31.2017",
  80. "GOOG.f.12.31.2016", "GOOG.f.12.31.2015", "GOOG.f.12.31.2014",
  81. "NVDA.f.1.28.2018", "NVDA.f.1.29.2017", "NVDA.f.1.31.2016", "NVDA.f.1.25.2015"
  82. ), row.names = c("Cash And Cash Equivalents", "Short Term Investments",
  83. "Net Receivables", "Inventory", "Other Current Assets", "Total Current Assets",
  84. "Long Term Investments", "Property Plant and Equipment", "Goodwill",
  85. "Intangible Assets", "Accumulated Amortization", "Other Assets",
  86. "Deferred Long Term Asset Charges", "Total Assets", "Accounts Payable",
  87. "Short/Current Long Term Debt", "Other Current Liabilities",
  88. "Total Current Liabilities", "Long Term Debt", "Other Liabilities",
  89. "Deferred Long Term Liability Charges", "Minority Interest",
  90. "Negative Goodwill", "Total Liabilities", "Misc. Stocks Options Warrants",
  91. "Redeemable Preferred Stock", "Preferred Stock", "Common Stock",
  92. "Retained Earnings", "Treasury Stock", "Capital Surplus", "Other Stockholder Equity",
  93. "Total Stockholder Equity", "Net Tangible Assets"), class = "data.frame")
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