Pandas groupby with delimiter join
3
I tried to use groupby to group rows with multiple values.
col val
A Cat
A Tiger
B Ball
B Bat
import pandas as pd
df = pd.read_csv("Inputfile.txt", sep='t')
group = df.groupby(['col'])['val'].sum()
I got
A CatTiger
B BallBat
I want to introduce a delimiter, so that my output looks like
A Cat-Tiger
B Ball-Bat
I tried,
group = df.groupby(['col'])['val'].sum().apply(lambda x: '-'.join(x))
this yielded,
A C-a-t-T-i-g-e-r
B B-a-l-l-B-a-t
What is the issue here ?
Thanks,
AP
python-3.x pandas pandas-groupby
asked Jun 5 '17 at 12:03
ArunArun
18711
add a comment |
3
I tried to use groupby to group rows with multiple values.
col val
A Cat
A Tiger
B Ball
B Bat
import pandas as pd
df = pd.read_csv("Inputfile.txt", sep='t')
group = df.groupby(['col'])['val'].sum()
I got
A CatTiger
B BallBat
I want to introduce a delimiter, so that my output looks like
A Cat-Tiger
B Ball-Bat
I tried,
group = df.groupby(['col'])['val'].sum().apply(lambda x: '-'.join(x))
this yielded,
A C-a-t-T-i-g-e-r
B B-a-l-l-B-a-t
What is the issue here ?
Thanks,
AP
python-3.x pandas pandas-groupby
asked Jun 5 '17 at 12:03
ArunArun
18711
add a comment |
3
3
3
1
I tried to use groupby to group rows with multiple values.
col val
A Cat
A Tiger
B Ball
B Bat
import pandas as pd
df = pd.read_csv("Inputfile.txt", sep='t')
group = df.groupby(['col'])['val'].sum()
I got
A CatTiger
B BallBat
I want to introduce a delimiter, so that my output looks like
A Cat-Tiger
B Ball-Bat
I tried,
group = df.groupby(['col'])['val'].sum().apply(lambda x: '-'.join(x))
this yielded,
A C-a-t-T-i-g-e-r
B B-a-l-l-B-a-t
What is the issue here ?
Thanks,
AP
python-3.x pandas pandas-groupby
asked Jun 5 '17 at 12:03
ArunArun
18711
I tried to use groupby to group rows with multiple values.
col val
A Cat
A Tiger
B Ball
B Bat
import pandas as pd
df = pd.read_csv("Inputfile.txt", sep='t')
group = df.groupby(['col'])['val'].sum()
I got
A CatTiger
B BallBat
I want to introduce a delimiter, so that my output looks like
A Cat-Tiger
B Ball-Bat
I tried,
group = df.groupby(['col'])['val'].sum().apply(lambda x: '-'.join(x))
this yielded,
A C-a-t-T-i-g-e-r
B B-a-l-l-B-a-t
What is the issue here ?
Thanks,
AP
python-3.x pandas pandas-groupby
python-3.x pandas pandas-groupby
asked Jun 5 '17 at 12:03
ArunArun
18711
asked Jun 5 '17 at 12:03
ArunArun
18711
asked Jun 5 '17 at 12:03
ArunArun
18711
asked Jun 5 '17 at 12:03
ArunArun
18711
asked Jun 5 '17 at 12:03
ArunArun
18711
18711
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
4
Alternatively you can do it this way:
In [48]: df.groupby('col')['val'].agg('-'.join)
Out[48]:
col
A Cat-Tiger
B Ball-Bat
Name: val, dtype: object
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
add a comment |
1
just try
group = df.groupby(['col'])['val'].apply(lambda x: '-'.join(x))
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
4
Alternatively you can do it this way:
In [48]: df.groupby('col')['val'].agg('-'.join)
Out[48]:
col
A Cat-Tiger
B Ball-Bat
Name: val, dtype: object
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
add a comment |
4
Alternatively you can do it this way:
In [48]: df.groupby('col')['val'].agg('-'.join)
Out[48]:
col
A Cat-Tiger
B Ball-Bat
Name: val, dtype: object
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
add a comment |
4
4
4
Alternatively you can do it this way:
In [48]: df.groupby('col')['val'].agg('-'.join)
Out[48]:
col
A Cat-Tiger
B Ball-Bat
Name: val, dtype: object
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
Alternatively you can do it this way:
In [48]: df.groupby('col')['val'].agg('-'.join)
Out[48]:
col
A Cat-Tiger
B Ball-Bat
Name: val, dtype: object
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
answered Jun 5 '17 at 12:13
MaxUMaxU
121k12118169
121k12118169
add a comment |
add a comment |
1
just try
group = df.groupby(['col'])['val'].apply(lambda x: '-'.join(x))
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
add a comment |
1
just try
group = df.groupby(['col'])['val'].apply(lambda x: '-'.join(x))
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
add a comment |
1
1
1
just try
group = df.groupby(['col'])['val'].apply(lambda x: '-'.join(x))
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
just try
group = df.groupby(['col'])['val'].apply(lambda x: '-'.join(x))
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
answered Jun 5 '17 at 12:08
ℕʘʘḆḽḘℕʘʘḆḽḘ
6,930945102
6,930945102
add a comment |
add a comment |
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