Update a 'data.frame' object with new data. Can be used to append new updated time series data to an existing dataframe, where each observation is indexed by a unique timestamp/identifier in a key column.
df_append(old, new, key = "time", keep.attr = "timestamp")data.frame object containing existing data.
data.frame object containing new data.
[default 'time'] column name used as key, provided as a character string.
[default 'timestamp'] name of an attribute in 'new' to retain, if present, provided as a character string.
A data.frame of the existing data appended with the new data. If the data in 'new' contains data with the same value for the key column as 'old', the data in 'new' will overwrite the data in 'old'.
If the attribute specified by 'keep.attr' is present in 'new', this is retained. All other non-required attributes are dropped.
Can be used to update price dataframes retrieved by oanda.
The function is designed to update existing data with new values as they
become available. As opposed to df_merge, the data in 'new'
will overwrite the data in 'old' rather than create duplicates.
data1 <- sample_ohlc_data[1:8, ]
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
#> 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
data2 <- sample_ohlc_data[7:10, ]
data2
#> time open high low close volume
#> 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_append(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