Lambda Operations in Pandas

Question

I have two columns hours and minutes stored separately in columns: a and b I want to calculate the sum of both in terms of minutes(DURATION)

To convert the hour into minutes I have used the following:

        train['duration']=train.a.apply(lambda x:x*60)

Now I want to add the minutes to the newly created duration column.

        So that my final value is duration=(a*60)+b

I am unable to perform this operation using lambda and for loop takes forever to execute In pandas.

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score 0 · Answer 1 · answered Apr 06 '20 at 14:47

0

Pandas is a very powerful module with neat features. If you want to simply add values of 1 column to values in another respectively you can simply do + operation on the columns. Here is my example:

import pandas as pd

df = pd.DataFrame({"col1":[1,2,3,4], "col2":[10,20,30,40]})

df["sum of 2 columns"] = df["col1"] + df["col2"]

print(df)

And this is the output:

   col1  col2  sum of 2 columns
0     1    10                11
1     2    20                22
2     3    30                33
3     4    40                44

answered Apr 06 '20 at 14:47

Karl Olufsen

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Yes, but how to do the same thing using lambdas? – Nitin Kumar Apr 06 '20 at 14:52
But why do you even need lambdas when pandas can do this out of the box? – Karl Olufsen Apr 06 '20 at 14:56

Rajnish kumar · Accepted Answer · 2020-04-06T16:12:44.683

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You can do it using lambda as follows.

import pandas as pd
df = pd.DataFrame({'x': [1, 2, 3], 'y': [4, 5, 6]})
df["sum"] = df.apply(lambda row: row.x + row.y, axis=1)
print(df)

It will give following output:

   x  y  sum
0  1  4    5
1  2  5    7
2  3  6    9

Hope it helps. You can do it using List Comprehension as that will be fast also or as @Karl Olufsen suggested.

edited Apr 06 '20 at 16:12

answered Apr 06 '20 at 16:00

Rajnish kumar

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You wanted using Lambda only. So, here is the way you can do. – Rajnish kumar Apr 06 '20 at 16:02
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You should assign your `df.apply()` result to a new column, otherwise this is not visible in your `print(df)`. – arnaud Apr 06 '20 at 16:04
Ya, You are right. Thanks @Arnaud . I'll edit the answer – Rajnish kumar Apr 06 '20 at 16:10
I'm glad that you got what you were searching for – Rajnish kumar Apr 07 '20 at 12:01

Vishnudev Krishnadas · Answer 3 · 2020-04-06T16:13:34.070

0

Best would be to use vectorized code which would be faster than apply

df['duration_in_min'] = df['hour'] * 60 + df['min']

The time complexity of various operations from best(fastest) to worst(slowest) is:

Cython procedures < Vectorized code < apply < itertuples < iterrows

edited Apr 06 '20 at 16:13

answered Apr 06 '20 at 16:06

Vishnudev Krishnadas

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Lambda Operations in Pandas

3 Answers3