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merge 2 data frames in a loop for each column in one of them

By : Renuka Aggarwal
Date : October 17 2020, 08:10 PM
around this issue We could use lapply over all the columns of mydf and match the value in mydf with that code column in codetable and get corresponding translation.
code :
mydf[] <- lapply(mydf, function(x) codetable$translation[match(x, codetable$code)])

#   a b c
#1  H F F
#2  H F J
#3  A I I
#4  H G C
#5  A E G
#6  G D H
#7  J G C
#8  H B G
#9  J I F
#10 C I B
mydf <- data.frame(a=sample(1:10, 20, replace=T), 
                   b=sample(1:10, 20, replace=T), 
                   c=sample(1:10, 20, replace=T))

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Merge and name data frames in for loop

By : Maxim Elets
Date : March 29 2020, 07:55 AM
seems to work fine I have a bunch of DF named like: df1, df2, ..., dfN , If your data frames are in a list, writing a for loop is trivial:
code :
# lt = list(lt1, lt2, lt3, ...)
# if your data is very big, this may run you out of memory
lt = lapply(ls(pattern = "lt[0-9]*"), get)

merged_data = merge(lt[[1]], lt[[2]])

for (i in 3:length(lt)) {
    merged_data = merge(merged_data, lt[[i]])
    save(merged_data, file = paste0("merging", i, ".rda"))

Merge Two data frames column by column. (creating a table out of two data frames)

By : davidel323
Date : March 29 2020, 07:55 AM
it fixes the issue We can use order on the sequence of columns, then get the names of dataset based on the order, rbind with the 'Date' column to create a vector of column names. This can be used to order the columns in the full dataset (cbind(df1, df2))
code :
cbind(df1, df2)[c(rbind('Date', matrix(c(names(df1)[-1], 
       names(df2)[-1])[order(c(seq_along(df1)[-1], seq_along(df2)[-1]))], ncol=2)))]
#      Date customer1 order1 Date.1 customer2 order2
#1    1         6      0      1         2      0
#2    2         7      1      2         3      1
#3    3         8      3      3         6      0
#4    4         4      0      4         5      0
#5    5         2      1      5         3      2

Changing Column names of multiple data frames using a for loop with data frames loaded into a List

By : Er Dileep kumar
Date : March 29 2020, 07:55 AM
hope this fix your issue I am trying to change the variable names in all data frames in a for loop. Any example of the data is:
code :
L <- lapply(L, function(x){
  colnames(x) <- c("NewName1", "NewName2")
} )

How do I merge two data frames if a column and it's values exist in both data frames?

By : Antonio Faillace
Date : March 29 2020, 07:55 AM
this one helps. IIUC, you can do df.combine_first() which
code :
        A       B      C
0  'name1'   'foo'  'bar'
1  'name2'  'foo''  'bar'
2  'name3'   'foo'  'bar'
3  'name4'   'foo'  'bar'

how to merge data across data.frame rows based on identical column values, for data.frames with multiple column formats

By : Josh Max Bacarac Gui
Date : March 29 2020, 07:55 AM
it should still fix some issue I have raw data in the format of df below that I'm needing to condense into a fewer row data.frame. The data represent eventual GIS point data (columns for coordinates are left off here) so I'm hoping to avoid plotting any duplicate points. Each row represents one point for which either or both of agency1 and agency2 publish data. A simpler case with fewer column formats is answered here. , You can make use of this. Might not be the most concise solution.
code :
# Data with NA values in column - agency3_id
df_na <- df[is.na(df$agency3_id), ]

# Logic
df <- df[!is.na(df$agency3_id), ] %>% 
  group_by(agency3_id) %>% 
  summarise_all(list(~ if(all(is.na(.))) NA else .[!is.na(.)][1]))

# Merge dataframes
rbind(df, df_na)
# Result
# A tibble: 5 x 9
  agency3_id agency1_id agency2_id agency1_val agency2_val agency1_desc agency2_desc agency1_dtm        
* <fct>           <dbl> <fct>            <dbl>       <dbl> <fct>        <fct>        <dttm>             
1 abcde            2007 xcv               0.23        6.3  ko           vf           2019-05-30 04:35:00
2 ertyu              NA zxc               1.5         4.4  NA           lo           NA                 
3 qwert            1500 NA                0.21        0.05 st           NA           2019-05-30 04:30:00
4 NA               4501 NA                4.3        NA    ui           NA           2019-05-30 04:33:00
5 NA                 NA bnm              NA           2    NA           kl           NA                 
# … with 1 more variable: agency2_dtm <dttm>
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