Python filling in missing values based on existing data

Question

I have a dataframe containing a one missing value.

   exam_id   exam  
0        1   french   
1        2   italian 
2        3   chinese  
3        4   english  
4        3   chinese  
5        5   russian  
6        1   french       
7      NaN   russian   
8        1   french   
9        2   italian

I want to fill in the missing exam_id for russian exam based on existing information. Since exam_id for russian is 5 I would like to have the same value assigned to the missing one.

just once? or for all missing values

ryugie
– ryugie

2017-03-13 19:22:02 +00:00
Commented Mar 13, 2017 at 19:22 — ryugie
– ryugie, Commented Mar 13, 2017 at 19:22
for all missing values!

Sheron
– Sheron

2017-03-13 19:22:19 +00:00
Commented Mar 13, 2017 at 19:22 — Sheron
– Sheron, Commented Mar 13, 2017 at 19:22

akuiper · Accepted Answer · 2017-03-13 19:22:41Z

3

You can group your data frame by exam, then do a ffill + bfill in case there are missing values before and after the existing value:

df.groupby("exam").ffill().bfill()

answered Mar 13, 2017 at 19:22

akuiper

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Comments

3novak · Accepted Answer · 2017-03-13 19:25:57Z

1

This approach does not only fill missing values. So beware. However, this would also take care of miscodings (e.g., "french" being coded as 3). Building a dictionary for the languages and their values and then applying it via a map will create a new exam_id column. Do note, however, that if a language doesn't appear in the dictionary (e.g. "French"), it will produce a missing value.

language_test_map = {'french': 1,
                     'italian': 2,
                     'chinese': 3,
                     'english': 4,
                     'russian': 5}

df['exam_id'] = df['exam'].map(language_test_map)

answered Mar 13, 2017 at 19:25

3novak

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