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.
df_merge(...)
data.frame objects to combine.
A data.frame containing all unique entries in the objects passed as argument.
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.
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