 Remove verbose from left_join
By : gkiran
Date : March 29 2020, 07:55 AM
Hope this helps You can explicitely provide the column by which you want to join and you avoid the message: code :
df <- left_join(df1, df2, by = "id")
|
dplyr::left_join produce NA values for new joined columns
By : James
Date : March 29 2020, 07:55 AM
I wish this help you I have two tables I wish to left_join through the dplyr package. The issue is that is produces NA values for all new columns (the ones I'm after). , There are two problems. code :
left_join(Avanza.XML, checkpoint, by = "Firm")
Avanza.XML$Firm <- as.character(Avanza.XML$Firm)
checkpoint$Firm <- as.character(checkpoint$Firm)
lvls <- sort(unique(c(levels(Avanza.XML$Firm),
levels(checkpoint$Firm))))
Avanza.XML$Firm <- factor(Avanza.XML$Firm, levels=lvls)
checkpoint$Firm <- factor(checkpoint$Firm, levels=lvls)
|
Prefix all columns resulting from left_join() with original table names
By : edubrulez
Date : March 29 2020, 07:55 AM
may help you . A straightforward way to achieve this would be to add the prefixes to the original tables before performing the join: code :
# add prefix before joining:
names(flights2) <- paste0("flights2.", names(flights2) )
names(airports2) <- paste0("airports2.", names(airports2) )
# in join, use names with prefixes
result <- flights2 %>% left_join(airports2, c("flights2.dest" = "airports2.faa") ) %>% head()
Source: local data frame [6 x 14]
flights2.year flights2.month flights2.day flights2.hour flights2.origin flights2.dest
(int) (int) (int) (dbl) (chr) (chr)
1 2013 1 1 5 EWR IAH
2 2013 1 1 5 LGA IAH
3 2013 1 1 5 JFK MIA
4 2013 1 1 5 JFK BQN
5 2013 1 1 5 LGA ATL
6 2013 1 1 5 EWR ORD
Variables not shown: flights2.tailnum (chr), flights2.carrier (chr), airports2.name (chr),
airports2.lat (dbl), airports2.lon (dbl), airports2.alt (int), airports2.tz (dbl),
airports2.dst (chr)
|
left_join R dataframes, merging two columns with NAs
By : Obexus
Date : March 29 2020, 07:55 AM
should help you out My problem is the following: Lets say I have an existing dataframe with the following columns: UID, foo, result. Result is already partially filled. A second model now predicts additional rows, generating a second dataframe containing a UID and a result column: (Code to reproduce at bottom) , coalesce is your second step. code :
left_join(df_main, new_prediction, by="UID") %>%
mutate(result = coalesce(result.x, result.y)) %>%
select(-result.x, -result.y)
# # A tibble: 5 x 3
# UID foo result
# <dbl> <chr> <chr>
# 1 1 moo Cow
# 2 2 rum <NA>
# 3 3 oink Pig
# 4 4 woof Dog
# 5 5 hiss Snake
|
r dplyr::left_join using datetime columns does not join properly
By : swarna
Date : March 29 2020, 07:55 AM
wish helps you On my separate dataset, checking both 'by' columns with lubridate::seconds(date_time) showed they were formatted differently due to milliseconds, though it didn't show up in most displays. "1522267608S" vs "1522267308.443S" (these aren't supposed to match, just to show formatting) Wrapping one or both of the columns in the following to remove milliseconds did the trick for me: code :
library(lubridate)
as_datetime(floor(seconds(date_time)))
|
code :
Related Posts :