SteveJones22 SteveJones22 - 1 month ago 15
R Question

converting zoo to dataframe

I converted a zoo time series into a dataframe in R and the date became the index of the dataframe. Is there a way to have the date represented as a normal column in the dataframe?

monthly_df <- data.frame(monthly_zoo)

head(monthly_zoo)

zoo output

head(monthly_df)

dataframe output

Answer

You want as.data.frame(). Witness:

R> library(quantmod)
Loading required package: xts
Loading required package: TTR
Version 0.4-0 included new data defaults. See ?getSymbols.
R> IBM <- as.zoo(getSymbols("IBM"))  # convert from xts
R> class(IBM)
[1] "zoo"
R> tail(IBM)
           IBM.Open IBM.High IBM.Low IBM.Close IBM.Volume IBM.Adjusted
2016-10-11   156.73   156.95  153.89    154.79    2901300       154.79
2016-10-12   154.97   154.97  153.08    154.29    2964000       154.29
2016-10-13   153.70   154.22  152.27    153.72    2909900       153.72
2016-10-14   154.47   155.53  154.09    154.45    4358200       154.45
2016-10-17   154.45   155.89  154.34    154.77    5890400       154.77
2016-10-18   150.02   151.00  147.79    150.72   12705700       150.72
R> as.data.frame(tail(IBM))
           IBM.Open IBM.High IBM.Low IBM.Close IBM.Volume IBM.Adjusted
2016-10-11   156.73   156.95  153.89    154.79    2901300       154.79
2016-10-12   154.97   154.97  153.08    154.29    2964000       154.29
2016-10-13   153.70   154.22  152.27    153.72    2909900       153.72
2016-10-14   154.47   155.53  154.09    154.45    4358200       154.45
2016-10-17   154.45   155.89  154.34    154.77    5890400       154.77
2016-10-18   150.02   151.00  147.79    150.72   12705700       150.72
R> class(as.data.frame(tail(IBM)))
[1] "data.frame"
R> 

To add the date as a column (instead of relying on the default rownames) make it explicit:

R> IBM <- getSymbols("IBM")  # keep as xts
R> tail(data.frame(index(IBM), as.data.frame(IBM)))
           index.IBM. IBM.Open IBM.High IBM.Low IBM.Close IBM.Volume IBM.Adjusted
2016-10-11 2016-10-11   156.73   156.95  153.89    154.79    2901300       154.79
2016-10-12 2016-10-12   154.97   154.97  153.08    154.29    2964000       154.29
2016-10-13 2016-10-13   153.70   154.22  152.27    153.72    2909900       153.72
2016-10-14 2016-10-14   154.47   155.53  154.09    154.45    4358200       154.45
2016-10-17 2016-10-17   154.45   155.89  154.34    154.77    5890400       154.77
2016-10-18 2016-10-18   150.02   151.00  147.79    150.72   12705700       150.72
R> 
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