基于R语言按姓名分组排查同名不同银行账户的员工数据问题

The core issue with your current code is that you're deduplicating bank accounts across all names instead of checking for duplicates within each name group. That's why Chris's 1280 account got removed—because Cassy's 1280 appeared first in your sorted data.

Here's the corrected approach using dplyr that groups by name, filters for names with multiple distinct bank accounts, and keeps unique account entries per name:

library(dplyr)

# Your original sample data
sample <- data.frame(
  Emp_id = c("123","134","143","143","235","433","231","120","135","150","150","900","900"),
  Name = c("Joan","Karyn","Larry","Larry","Larry","Larry","Larry","Amy","Amy","Chris","Chris","Cassy","Cassy"),
  Bank_Account = c("6758","1244","4900","5201","5201","5201","5201","7890","7890","1280","6565","1280","9873")
)

# Step-by-step solution
result <- sample %>%
  # Group rows by employee name
  group_by(Name) %>%
  # Only keep groups where there are 2+ distinct bank accounts
  filter(n_distinct(Bank_Account) > 1) %>%
  # Keep one unique entry per (Name, Bank_Account) pair (preserving Emp_id)
  distinct(Bank_Account, .keep_all = TRUE) %>%
  # Remove grouping and sort by name for readability
  ungroup() %>%
  arrange(Name)

# View the result
print(result)

Expected Output: #

Emp_id  Name Bank_Account
1    900 Cassy         1280
2    900 Cassy         9873
3    150 Chris         1280
4    150 Chris         6565
5    143 Larry         4900
6    143 Larry         5201

Key Fixes Explained: #

1. Grouping by Name: Ensures we only analyze bank accounts within each employee's name group, not across all names.
2. Filtering for Multiple Accounts: Uses n_distinct(Bank_Account) > 1 to keep only names that have different bank accounts.
3. Distinct per Group: distinct(Bank_Account, .keep_all = TRUE) keeps one row for each unique bank account per name, avoiding cross-name deduplication.

内容的提问来源于stack exchange，提问作者Jazz