Stack Overflow Asked by Steminist on November 24, 2021
I have a Dataframe with two columns "Start_location"
and "end_location"
. I want to create a new column called "location"
from the 2 previous columns with the following conditions.
If the values of "start_location" == "end_location"
, then the value of "location"
will be either of the values of the first two columns.
else, if the values of of "start_location"
and "end_location
are different, then values of "Location"
will be "start_location"-"end_location".
An example of what I want is this.
+---+--------------------+-----------------------+
| | Start_location | End_location |
+---+--------------------+-----------------------+
| 1 | Stratford | Stratford |
| 2 | Bromley | Stratford |
| 3 | Brighton | Manchester |
| 4 | Delaware | Delaware |
+---+--------------------+-----------------------+
The result I want is this.
+---+--------------------+-----------------------+--------------------+
| | Start_location | End_location | Location |
+---+--------------------+-----------------------+--------------------+
| 1 | Stratford | Stratford | Stratford |
| 2 | Bromley | Stratford | Brombley-Stratford |
| 3 | Brighton | Manchester | Brighton-Manchester|
| 4 | Delaware | Delaware | Delaware |
+---+--------------------+-----------------------+--------------------+
I would be happy if anyone can help.
PS- forgive me if this is a very basic question. I have gone through some similar questions on this topic but couldn’t get a headway.
You can use Numpy
to compare both columns.
Follow This code
import numpy as np
df["Location"] = np.where((df['Start_location'] == df['End_location'])
, df['Start_location'],df['Start_location']+"-"+ df['End_location'])
df
Output:
Start_location End_location Location
0 Stratford Stratford Stratford
1 Bromley Stratford Bromley-Stratford
2 Brighton Manchester Brighton-Manchester
3 Delaware Delaware Delaware
Answered by Tarequzzaman Khan on November 24, 2021
Use np.select(condition, choice)
. To join start, use .str.cat()
method
import numpy as np
condition=[df['Start_location']==df['End_location'],df['Start_location']!= df['End_location']]
choice=[df['Start_location'], df['Start_location'].str.cat(df['End_location'], sep='_')]
df['Location']=np.select(condition, choice)
df
Start_location End_location Location
1 Stratford Stratford Stratford
2 Bromley Stratford Bromley_Stratford
3 Brighton Manchester Brighton_Manchester
4 Delaware Delaware Delaware
Answered by wwnde on November 24, 2021
df['Location'] = df[['start_location','end_location']].apply(lambda x: x[0] if x[0] == x[1] else x[0] + '-' + x[1], axis = 1)
Answered by Mini Fridge on November 24, 2021
You can make your own function that does this and then use apply
and a lambda function:
def get_location(start, end):
if start == end:
return start
else:
return start + ' - ' + end
df['location'] = df.apply(lambda x: get_location(x.Start_location, x.End_location), axis = 1)
Answered by Chris Schmitz on November 24, 2021
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