Full join on an arbitrary number of 'data.frame' objects passed as arguments, preserving all unique entries. Can be used to combine historical time series data where each observation is indexed by a unique timestamp and all periods are complete.
Details
Can be used to join price dataframes retrieved by oanda.
The function is designed to join complete historical data. If the data to
be merged contains data with incomplete periods, all entries are
preserved rather than updated. If incomplete periods are detected within
the data, a warning is issued, and the resulting dataframe should be
manually checked in case it contains unwanted duplicates. Use
df_append for updating dataframes with new values.
Examples
data1 <- sample_ohlc_data[1:6, ]
data1
#> time open high low close volume
#> 1 2020-01-02 123.0 123.1 122.5 122.7 1875
#> 2 2020-01-03 122.7 122.8 122.6 122.8 1479
#> 3 2020-01-06 122.8 123.4 122.4 123.3 1792
#> 4 2020-01-07 123.3 124.3 123.3 124.1 1977
#> 5 2020-01-08 124.1 124.8 124.0 124.8 2239
#> 6 2020-01-09 124.8 125.4 124.5 125.3 1842
data2 <- sample_ohlc_data[4:10, ]
data2
#> time open high low close volume
#> 4 2020-01-07 123.3 124.3 123.3 124.1 1977
#> 5 2020-01-08 124.1 124.8 124.0 124.8 2239
#> 6 2020-01-09 124.8 125.4 124.5 125.3 1842
#> 7 2020-01-10 125.3 125.3 124.8 125.2 2548
#> 8 2020-01-13 125.2 125.3 125.1 125.2 2946
#> 9 2020-01-14 125.2 125.2 124.3 124.4 2796
#> 10 2020-01-15 124.4 124.5 123.7 123.9 2879
df_merge(data1, data2)
#> time open high low close volume
#> 1 2020-01-02 123.0 123.1 122.5 122.7 1875
#> 2 2020-01-03 122.7 122.8 122.6 122.8 1479
#> 3 2020-01-06 122.8 123.4 122.4 123.3 1792
#> 4 2020-01-07 123.3 124.3 123.3 124.1 1977
#> 5 2020-01-08 124.1 124.8 124.0 124.8 2239
#> 6 2020-01-09 124.8 125.4 124.5 125.3 1842
#> 7 2020-01-10 125.3 125.3 124.8 125.2 2548
#> 8 2020-01-13 125.2 125.3 125.1 125.2 2946
#> 9 2020-01-14 125.2 125.2 124.3 124.4 2796
#> 10 2020-01-15 124.4 124.5 123.7 123.9 2879