I want to merge the range of cells with reference to a unique cell value and require VBA for the same.
Sample Data
Name
Phone No.
Car Company
Car Model
Car Expiry
DL No.
Charlie Andrew
98765
CA123
Charlie Andrew
98765
Mercedes
D201
Charlie Andrew
D201
Jun-50
Charlie Andrew
98765
Volkswagon
CA123
Charlie Andrew
Volkswagon
POLO
Charlie Andrew
POLO
MAR-25
Charlie Andrew
98765
Jun-50
Charlie Andrew
12345
BMW
520D
Charlie Andrew
520D
MAY-40
CA456
Stephen Logan
556644
GM MOTORS
Stephen Logan
GM MOTORS
2255H
Stephen Logan
2255H
APR-30
Stephen Logan
556644
SL987
Desired Result
Name
Phone No.
Car Company
Car Model
Car Expiry
DL No.
Charlie Andrew
987654
Mercedes; Volkswagon
D201; POLO
Jun-50; mar-25
CA123
Charlie Andrew
12345
BMW
520D
MAY-40
CA456
Stephen Logan
556644
GM MOTORS
2255H
APRIL-30
SL987
Please note that, DL No. should not be merged as it is a unique value
Thanks in Advance
I tried various VBA's but didn't get desired result.
Related
This should be pretty simple I think.
In Excel I've got a list of data I'm gathering from various sources:
name
time 1
time 2
time 3
Time 4
jimmy
00:30
1:30
john
01:09
1:45
bobby
01:09
2:49
elaine
00:39
1:19
greg
01:09
1:45
jimmy
0:33
1:29
bobby
0:45
1:15
elaine
1:24
2:01
jack
0:10
0:50
Desired result:
name
time 1
time 2
time 3
Time 4
jimmy
00:30
1:30
0:33
1:29
john
01:09
1:45
bobby
01:09
2:49
0:45
1:15
elaine
00:39
1:19
1:24
2:01
greg
01:09
1:45
jack
0:10
0:50
I'm either not knowing the proper way to search for this or something because my normally pretty good google-fu is failing me today.
Edit to clarify:
name
time 1
time 2
time 3
Time 4
jimmy
Burger
HotDog
john
Salami
Samosa
bobby
Burger
Paella
elaine
Sorbet
Muffin
greg
HotDog
Wonton
jimmy
Tamale
Waffle
bobby
Paella
Tamale
elaine
Waffle
Toffee
jack
Quinoa
Kiwano
name
time 1
time 2
time 3
Time 4
jimmy
Burger
HotDog
Tamale
Waffle
john
Salami
Samosa
bobby
Burger
Paella
Paella
Tamale
elaine
Sorbet
Muffin
Waffle
Toffee
greg
HotDog
Wonton
jack
Quinoa
Kiwano
Rollback
If you have Excel-365 then use below formulas.
G2 cell =UNIQUE(A2:A10)
H2 cell =#FILTER(B$2:B$10,($A$2:$A$10=$G2)*(B$2:B$10<>""),"")
Drag down and across H2 cell formula as needed.
You can use sumifs formula.
=SUMIFS(B:B,$A:$A,$K2)
for example,
i have kept the unique names in the K column
use sumifs formula for B , C , D , E column
change the format of the cells to time
I am trying to remove a custom list of stop words, but its not working.
desc = pd.DataFrame(description, columns =['description'])
print(desc)
Which gives the following results
description
188693 The Kentucky Cannabis Company and Bluegrass He...
181535 Ohio County Sheriff
11443 According to new reports from federal authorit...
213919 KANSAS CITY, Mo. (AP)The Chiefs will be withou...
171509 The crew of Insight, WCNY's weekly public affa...
... ...
2732 The Arkansas Supreme Court on Thursday cleared...
183367 Larry Pegram, co-owner of Pure Ohio Wellness, ...
134291 Joe Biden will spend the next five months pres...
239270 Find out where your Texas representatives stan...
246070 SAN TAN VALLEY — Two men have been charged wit...
[9875 rows x 1 columns]
I found the following code here, but it doesn't seem to work
remove_words = ["marijuana", "cannabis", "hemp", "thc", "cbd"]
pat = '|'.join([r'\b{}\b'.format(w) for w in remove_words])
desc.assign(new_desc=desc.replace(dict(string={pat: ''}), regex=True))
Which produces the following results
description new_desc
188693 The Kentucky Cannabis Company and Bluegrass He... The Kentucky Cannabis Company and Bluegrass He...
181535 Ohio County Sheriff Ohio County Sheriff
11443 According to new reports from federal authorit... According to new reports from federal authorit...
213919 KANSAS CITY, Mo. (AP)The Chiefs will be withou... KANSAS CITY, Mo. (AP)The Chiefs will be withou...
171509 The crew of Insight, WCNY's weekly public affa... The crew of Insight, WCNY's weekly public affa...
... ... ...
2732 The Arkansas Supreme Court on Thursday cleared... The Arkansas Supreme Court on Thursday cleared...
183367 Larry Pegram, co-owner of Pure Ohio Wellness, ... Larry Pegram, co-owner of Pure Ohio Wellness, ...
134291 Joe Biden will spend the next five months pres... Joe Biden will spend the next five months pres...
239270 Find out where your Texas representatives stan... Find out where your Texas representatives stan...
246070 SAN TAN VALLEY — Two men have been charged wit... SAN TAN VALLEY — Two men have been charged wit...
9875 rows × 2 columns
As you can see, the stop words weren't removed. Any help you can provide would be greatly appreciated.
Handle the case, simplify pattern,
remove_words = ["marijuana", "cannabis", "hemp", "thc", "cbd"]
pat = '|'.join(remove_words)
desc['new_desc'] = desc.description.str.lower().replace(pat,'', regex=True)
description new_desc
0 The Kentucky Cannabis Company and Bluegrass He... the kentucky company and bluegrass he...
1 Ohio County Sheriff ohio county sheriff
2 According to new reports from federal authorit... according to new reports from federal authorit...
3 KANSAS CITY, Mo. (AP)The Chiefs will be mariju... kansas city, mo. (ap)the chiefs will be witho...
4 The crew of Insight, WCNY's weekly public affa... the crew of insight, wcny's weekly public affa...
Here is a small set of the dataset that I am currently working on.
FirstName LastName cities occupation time
---------------------------------------------------------------
---------------------------------------------------------------
Alice Oumi Queens software engineer 1/1/2019
Alice Oumi New York software engineer 12/3/2018
Sam Charles Santa Clara Engineer 2/5/2017
Sam Charles Santa Monica Engineer 8/9/2018
Sam Charles Santa Clara Engineer 12/12/2019
Alice Oumi New York software engineer 1/2/2017
As you see above, the same person could be living in a same place but for a different duration of a time. I want to make clean this dataset that should what places did Alice and Sam live. For example, instead of having 2 rows of Alice living in New York, I only need to have one. Something similar to the following table
FirstName LastName cities FirstTime SecondTime
---------------------------------------------------------------
---------------------------------------------------------------
Alice Oumi Queens 1/1/2019 NA
Alice Oumi New York 1/2/2017 12/3/2018
Sam Charles Santa Clara 2/5/2017 12/12/2019
Sam Charles Santa Monica 8/9/2018 NA
I am kinda new to python and trying to learn. but i have tried to use for loops using iterrows() but didn't work.
What can use to achieve this table?
Thank you so much in advance
You can do that as follows:
# number the times a person lived in the same city (with the same occupation)
df['sequence']= df.groupby(['FirstName', 'LastName', 'cities', 'occupation']).cumcount()+1
# now create the "pivot" table
result= df.set_index(['FirstName', 'LastName', 'cities', 'occupation', 'sequence']).unstack()
# rename the columns
result.columns= ['FirstTime', 'SecondTime']
# reset the index (it was just needed for "pivoting"
result.reset_index(inplace=True)
The result looks like:
Out[483]:
FirstName LastName cities occupation FirstTime SecondTime
0 Alice Oumi New York software engineer 12/3/2018 1/2/2017
1 Alice Oumi Queens software engineer 1/1/2019 NaN
2 Sam Charles Santa Clara Engineer 2/5/2017 12/12/2019
3 Sam Charles Santa Monica Engineer 8/9/2018 None NaN
For example I have names like these:
John Lucas Smith
Kevin Thomas Bacon
I need to do it with regexp_substr, or replace or something like that.
and what I want to get is:
John Smith
Kevin Bacon
Thank you!
Something like this?
SQL> with test (col) as
2 (select 'John Lucas Smith' from dual union
3 select 'Kevin Thomas Bacon' from dual union
4 select 'Little Foot' from dual
5 )
6 select regexp_substr(col, '^\w+') ||' '||
7 regexp_substr(col, '\w+$') first_and_last
8 from test;
FIRST_AND_LAST
-------------------------------------
John Smith
Kevin Bacon
Little Foot
SQL>
I have a single column text file looking like this:
John
Doe
Male
1984
Marie
Parker
Female
1989
And I would like to convert it to look like this:
John Doe Male 1984
Marie Parker Female 1989
I've tried using awk and modulo but I cannot manage to find a working solution.
$ pr -4at file
John Doe Male 1984
Marie Parker Female 1989
or your format
$ pr -4ats' ' file
John Doe Male 1984
Marie Parker Female 1989
of course with awk
$ awk 'ORS=NR%4?FS:RS' file
John Doe Male 1984
Marie Parker Female 1989
with paste
$ paste -d' ' - - - - < file
John Doe Male 1984
Marie Parker Female 1989