Merge two data frames: having more rows issues

rstudio

#1

Hello,

I have two data frames:

  • Data frame 1: is the sale fact with customer ID (there are duplicates, obviously).**

  • Data frame 2: is the rewards dataset which assigns each unique customer (there is not duplicate customer IDs this data frame) a number corresponding to a reward level.

Goal:

  • Attach Data frame 2 to Data frame 1 --> create a new data frame in which each row contains both a customer ID and a reward number/code.

Warning:

  • Since in the data frame 1, there are new customers every day and they may not exist in data frame 2, I would like to assign those customers a value NA or 0. --> later on, I will remove them out of the final data frame.
  • There can be some customers in data frame 2 assigned a reward number/code but they do not exist in data frame 1 --> what is the best way to solve this issue?

Can I do this using tiyverse package?

Thank you!


#2

A good place to start might be the dplyr vignette on two-table verbs:
https://dplyr.tidyverse.org/articles/two-table.html


#3

jcblum:
I used merge() function and it works perfectly.
The result is that the new data frame just take the row that has observations appear in BOTH data frames 1 and 2.

Thank you!


#4

I need more help on this topic.

I am trying to merge two data frames by using full_join() by a variable name called "CUSTOMER_NUMBER".
I got help from Martin.R before to work in this:

  • First, I converted CUSTOMER_NUMBER into numeric as.numeric(as.character(orginal_data1$CUSTOMER_NUMBER))
  • The reason why he suggested me doing that was that there existed an issue when I merged two data frames together, there were new rows coming out of nowhere.

Now, the issue is, the original data set has 84,961 unique customers and after I did convert that column, there is one row less (i.e 84, 960).
If I do this ...%>% na.omit(), then there will be even one more row less (i.e 84, 959).
I did View(data) and there are a few customers ID 0 but my original data set has only 1 customer ID 000000.
What is the issue?

library(tidyverse) 
library(dplyr)
library(reprex)

data = structure(list(CUSTOMER_NUMBER = c("240464833", "240464833", 
                                          "304200341", "328200716", "328804035", "341165440", "344200356", 
                                          "344200356", "344257899", "345114321", "368200262", "371200189", 
                                          "373128923", "373156382", "373182845", "373200097", "373200163", 
                                          "373305193", "373305193", "373654228", "373655997", "373655997", 
                                          "373746845", "374200116", "374200116", "374200245", "374200567", 
                                          "374547687", "374547687", "328200227", "328200258", "328200324", 
                                          "328200449", "328200665", "328200854", "328200930", "328432553", 
                                          "328484858", "328503426", "360545696", "373102040", "373461662", 
                                          "328200940", "342170407", "422201038", "422201038", "422295043", 
                                          "456200526", "462626501", "632198401", "656558734", "728468964", 
                                          "743200015", "760553604", "764326192", "374547687", "374770073", 
                                          "375315324", "402200379", "408488309", "408748740", "410200334", 
                                          "410200334", "410527343", "422112098", "422761648", "438200798", 
                                          "438461197", "373552475", "373552475", "373552475", "373746845", 
                                          "374615602", "375200313", "375360703", "410574873", "422886800", 
                                          "444701998", "448200314", "448267635", "456442639", "768152705", 
                                          "768200259", "209200110", "209200110", "209200320", "209426442", 
                                          "209733492", "212149526", "220739357", "230257275", "240464878", 
                                          "240506379", "246232660", "444474214", "448361237", "448455525", 
                                          "450504833", "454200908", "454803092", "458503336", "458879597", 
                                          "460447273", "462387101", "610152257", "610152257", "632569663", 
                                          "458346229", "458575623", "632200352", "656493726", "704200304", 
                                          "704201434", "710198201", "710743579", "728119488", "728201030", 
                                          "744538875", "760378672", "760378672", "763385790", "246524598", 
                                          "304106135", "328546392", "328689306", "332200105", "336608543", 
                                          "336608543", "336608543", "342782537", "344200356", "344257899", 
                                          "360200004", "360217257", "632735606", "642221462", "704200334", 
                                          "704557802", "704576852", "704615849", "704746835", "708505217", 
                                          "710155532", "710339414", "710421769", "728279411", "728343667", 
                                          "764157626", "766319650", "768200171", "768200516")), class = c("data.table", 
                                                                                                          "data.frame"), row.names = c(NA, -151L))
 data$CUSTOMER_NUMBER %>% unique() %>% length()
#> [1] 132

data$CUSTOMER_NUMBER = as.numeric(as.character(data$CUSTOMER_NUMBER))

 data$CUSTOMER_NUMBER %>% unique() %>% length()
#> [1] 132

Created on 2018-07-18 by the reprex
package
(v0.2.0).


#5

There are words in my customers ID.
I just figured that out.
What a messed up data set!

I got it, team. Thanks!


#6

Story of every analyst’s life! :sweat_smile:


#7

I meant I am not gonna say I am mad, but it took away 3 hours of my life.... and I skipped dinner!