CODEWITHSUNDEEP
pythonpandas
winnie
winnie

Reputation: 109

How to optimise this type of search and replace in pandas

I have a dataframe that roughly looks like this

ID    VAL 
2     3
2     7
2     4
2     5
2     2
3     4
3     6
3     7
3     2
4     2
4     3
4     4
4     5
4     6

Another dataframe that roughly looks like this

ID     VAL
2       5
3       7

I want to do an operation that for each row in the second dataframe, the row will move to the top.

ID    VAL 
2     5
2     3
2     7
2     4
2     2
3     7
3     4
3     6
3     2
4     2
4     3
4     4
4     5
4     6

See that the (2, 5) tuple and the (3, 7) tuple have been moved up to where that "ID" begins.

I've currently a horribly inefficient implementation.

Any help would be appreciated!

Upvotes: 2

Views: 28

Answers (1)

BENY
BENY

Reputation: 323316

I am using a help key create by using merge then we sort_values

df1.merge(df2.assign(key=0),how='left').fillna({'key':1}).sort_values(['ID','key'])
# you can add .drop('key',1) at the end :-)
    ID  VAL  key
3    2    5  0.0
0    2    3  1.0
1    2    7  1.0
2    2    4  1.0
4    2    2  1.0
7    3    7  0.0
5    3    4  1.0
6    3    6  1.0
8    3    2  1.0
9    4    2  1.0
10   4    3  1.0
11   4    4  1.0
12   4    5  1.0
13   4    6  1.0

Upvotes: 3

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