Instalación
install.packages("quantmod")
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.3'
## (as 'lib' is unspecified)
Ejecución de la libreria
library(quantmod)
## Loading required package: xts
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
## Loading required package: TTR
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
Scraping a Apple
apple_df <- getSymbols('AAPL', src='yahoo', auto.assign=FALSE)
apple_df
## AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume
## 2007-01-03 3.081786 3.092143 2.925000 2.992857 1238319600
## 2007-01-04 3.001786 3.069643 2.993571 3.059286 847260400
## 2007-01-05 3.063214 3.078571 3.014286 3.037500 834741600
## 2007-01-08 3.070000 3.090357 3.045714 3.052500 797106800
## 2007-01-09 3.087500 3.320714 3.041071 3.306071 3349298400
## 2007-01-10 3.383929 3.492857 3.337500 3.464286 2952880000
## 2007-01-11 3.426429 3.456429 3.396429 3.421429 1440252800
## 2007-01-12 3.378214 3.395000 3.329643 3.379286 1312690400
## 2007-01-16 3.417143 3.473214 3.408929 3.467857 1244076400
## 2007-01-17 3.484286 3.485714 3.386429 3.391071 1646260000
## ...
## 2023-07-17 191.899994 194.320007 191.809998 193.990005 50520200
## 2023-07-18 193.350006 194.330002 192.419998 193.729996 48353800
## 2023-07-19 193.100006 198.229996 192.649994 195.100006 80507300
## 2023-07-20 195.089996 196.470001 192.500000 193.130005 59581200
## 2023-07-21 194.100006 194.970001 191.229996 191.940002 71917800
## 2023-07-24 193.410004 194.910004 192.250000 192.750000 45377800
## 2023-07-25 193.330002 194.440002 192.919998 193.619995 37283200
## 2023-07-26 193.669998 195.639999 193.320007 194.500000 47471900
## 2023-07-27 196.020004 197.199997 192.550003 193.220001 47460200
## 2023-07-28 194.669998 196.630005 194.139999 195.830002 48254600
## AAPL.Adjusted
## 2007-01-03 2.543757
## 2007-01-04 2.600217
## 2007-01-05 2.581701
## 2007-01-08 2.594451
## 2007-01-09 2.809971
## 2007-01-10 2.944444
## 2007-01-11 2.908018
## 2007-01-12 2.872200
## 2007-01-16 2.947480
## 2007-01-17 2.882216
## ...
## 2023-07-17 193.990005
## 2023-07-18 193.729996
## 2023-07-19 195.100006
## 2023-07-20 193.130005
## 2023-07-21 191.940002
## 2023-07-24 192.750000
## 2023-07-25 193.619995
## 2023-07-26 194.500000
## 2023-07-27 193.220001
## 2023-07-28 195.830002
Grafica
chartSeries(apple_df, name="AAPL", subset="last 6 months", theme=chartTheme("white"))
Scraping a Microsoft
MSFT_df <- getSymbols('MSFT', src='yahoo', auto.assign=FALSE)
MSFT_df
## MSFT.Open MSFT.High MSFT.Low MSFT.Close MSFT.Volume MSFT.Adjusted
## 2007-01-03 29.91 30.25 29.40 29.86 76935100 21.52598
## 2007-01-04 29.70 29.97 29.44 29.81 45774500 21.48993
## 2007-01-05 29.63 29.75 29.45 29.64 44607200 21.36739
## 2007-01-08 29.65 30.10 29.53 29.93 50220200 21.57644
## 2007-01-09 30.00 30.18 29.73 29.96 44636600 21.59807
## 2007-01-10 29.80 29.89 29.43 29.66 55017400 21.38181
## 2007-01-11 29.76 30.75 29.65 30.70 99464300 22.13154
## 2007-01-12 30.65 31.39 30.64 31.21 103972500 22.49919
## 2007-01-16 31.26 31.45 31.03 31.16 62379600 22.46315
## 2007-01-17 31.26 31.44 31.01 31.10 58519600 22.41990
## ...
## 2023-07-17 345.68 346.99 342.20 345.73 20363900 345.73001
## 2023-07-18 345.83 366.78 342.17 359.49 64872700 359.48999
## 2023-07-19 361.75 362.46 352.44 355.08 39732900 355.07999
## 2023-07-20 353.57 357.97 345.37 346.87 33778400 346.87000
## 2023-07-21 349.15 350.30 339.83 343.77 69368900 343.76999
## 2023-07-24 345.85 346.92 342.31 345.11 26678100 345.10999
## 2023-07-25 347.11 351.89 345.07 350.98 41637700 350.98001
## 2023-07-26 341.44 344.67 333.11 337.77 58383700 337.76999
## 2023-07-27 340.48 341.33 329.05 330.72 39635300 330.72000
## 2023-07-28 333.67 340.01 333.17 338.37 28463000 338.37000
Grafica
chartSeries(MSFT_df, name="Microsoft", subset="last 6 months", theme=chartTheme("white"))
Scraping a Coca cola
KO_df <- getSymbols('KO', src='yahoo', auto.assign=FALSE)
KO_df
## KO.Open KO.High KO.Low KO.Close KO.Volume KO.Adjusted
## 2007-01-03 24.180 24.440 24.140 24.290 15753400 14.65590
## 2007-01-04 24.210 24.350 24.125 24.300 11810400 14.66193
## 2007-01-05 24.250 24.285 24.085 24.130 11607000 14.55936
## 2007-01-08 24.005 24.335 24.005 24.285 17551000 14.65288
## 2007-01-09 24.270 24.415 24.230 24.305 13724000 14.66495
## 2007-01-10 24.245 24.395 24.185 24.340 8928000 14.68606
## 2007-01-11 24.375 24.435 24.300 24.370 11009600 14.70417
## 2007-01-12 24.300 24.335 24.125 24.275 13667200 14.64684
## 2007-01-16 24.240 24.345 24.170 24.250 12685200 14.63176
## 2007-01-17 24.265 24.430 24.240 24.300 14400200 14.66193
## ...
## 2023-07-17 60.760 61.100 60.490 60.810 10014300 60.81000
## 2023-07-18 60.960 61.250 60.410 60.570 11152900 60.57000
## 2023-07-19 60.770 61.790 60.680 61.640 12936000 61.64000
## 2023-07-20 61.680 62.410 61.670 62.390 11563000 62.39000
## 2023-07-21 62.460 62.680 62.240 62.440 12813200 62.44000
## 2023-07-24 62.420 62.810 62.400 62.460 10251100 62.46000
## 2023-07-25 62.300 62.390 62.050 62.250 13422700 62.25000
## 2023-07-26 61.860 63.170 61.390 63.050 17145500 63.05000
## 2023-07-27 63.050 63.270 62.380 62.440 11517100 62.44000
## 2023-07-28 62.590 62.770 62.220 62.480 9721800 62.48000
Grafica
chartSeries(KO_df, name="Coca Cola", subset="last 6 months", theme=chartTheme("white"))
Scraping a Toyota
TM_df <- getSymbols('TM', src='yahoo', auto.assign=FALSE)
TM_df
## TM.Open TM.High TM.Low TM.Close TM.Volume TM.Adjusted
## 2007-01-03 135.25 136.54 134.45 135.30 758600 107.8092
## 2007-01-04 136.65 137.97 135.64 137.77 842700 109.7774
## 2007-01-05 133.30 133.87 132.55 133.72 1068400 106.5502
## 2007-01-08 134.60 134.74 133.80 133.97 511600 106.7494
## 2007-01-09 132.17 132.94 131.24 132.16 645700 105.3072
## 2007-01-10 129.00 129.86 128.21 129.43 726200 103.1319
## 2007-01-11 128.00 130.43 127.81 128.78 803900 102.6140
## 2007-01-12 129.87 130.89 129.79 130.89 498500 104.2953
## 2007-01-16 131.49 132.49 130.75 131.21 641200 104.5502
## 2007-01-17 131.64 131.89 130.78 131.10 641100 104.4626
## ...
## 2023-07-17 159.40 159.59 158.17 159.45 241300 159.4500
## 2023-07-18 161.94 163.53 161.87 163.19 435500 163.1900
## 2023-07-19 164.95 164.98 163.68 163.97 216700 163.9700
## 2023-07-20 163.08 163.64 162.40 163.28 217800 163.2800
## 2023-07-21 163.58 163.68 162.60 162.81 214400 162.8100
## 2023-07-24 164.58 164.92 164.25 164.53 212100 164.5300
## 2023-07-25 165.00 165.80 164.74 165.56 233300 165.5600
## 2023-07-26 165.16 166.02 164.88 165.70 162300 165.7000
## 2023-07-27 165.87 166.73 165.38 165.43 182200 165.4300
## 2023-07-28 167.10 167.80 166.69 167.15 292200 167.1500
Grafica
chartSeries(TM_df, name="Toyota", subset="last 6 months", theme=chartTheme("white"))
