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Data Wrangling 2025
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Data Wrangling
1
My dataset has a field with concatenated entries. Each row of the dataset has a different number of concatenated entries, and the entries are not in any particular order. Should I split the concatenated entries into many rows, or many columns?
Select one or more answers
Probably better to split into rows
Probably better to split into columns
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Data Wrangling
2
I want to merge two datasets. Do I need to check if there are any duplicate entries in each dataset?
Select one or more answers
No, I don't need to worry about duplicates
Yes, because duplicates might create errors or problems when I merge the datasets
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Data Wrangling
3
When should I check for duplicates?
Select one or more answers
Before merging two datasets
After merging two datasets
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Data Wrangling
4
I am going to merge two datasets on fields "Date" and "ID". The first dataset has 6 other fields. What duplicates do I care about in that dataset?
Select one or more answers
Duplicates with the same Date and ID
Duplicates with all 8 fields the same
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Data Wrangling
5
I am having trouble merging the two datasets on fields A and B. The error message suggests the formats of field A do not match in datasets 1 and 2. What should I do first?
Select one or more answers
Try to convert field A to character in both the datasets
Look at a few of the entries from field A in the two datasets
Check what data type is in field A in each dataset
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Data Wrangling
6
When I try to convert the data type of field A, I get a message "NAs introduced by coercion". Do I need to worry about this?
Select one or more answers
No, it just means I will have some missing data
Yes, it may mean some of the entries in field A are inconsistent with each other and I need to process them more carefully
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Data Wrangling
7
It turns out that dataset 1 has field "Birth Year" and dataset 2 has field "Birth Date". Some elements of the "Birth Date" field are of the form "1984" or "1945"; others are of the form "c. 1488" or "c. 1659"; and others are of the form "1964-05-19" or "1934-11-13". What should I do with them?
Select 1 answer
Convert them all to character and convert the "Birth Year" entries to character too, then find exact matches
Extract the years from the Birth Date entries and match them against "Birth Years"
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Data Wrangling
8
Datasets 1 and 2 both list individuals by full display name. Is it ok for me to merge the datasets on display names, ignoring other fields?
Select 1 answer
No, it's likely that would create some mismatches because many names are common, and because some names may have been recorded differently in different datasets
Yes, I can merge by full display name only
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