Mixing
Python: How do I change a value in column A if another value in column B repeats itself?
1
I have many excel files with the same columns in one folder. I need to browse each file and compare which values of the column "User Number" of one file are the same as the other file. And then manipulate another column named "Date" based on that. For exemple:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-11-04
18732A 2017-06-25
So in this case I want the program to check for matches of User Number values and then, if the date - linked to this number - of one file is different from the date of the other file, I want to change both dates to be the oldest date.
In this case I would have:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-08-06
18732A 2017-06-22
I appended all the files:
import os
import glob
import pandas as pd
path=r'C/.../files'
files = os.listdir(path)
df = pd.DataFrame()
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
df=df.append(data)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
The logic doesn't work like javascript logic, so I'm not sure how to do the condition. I've tried:
df_number = df["User Number"]
for number in df[df_number.duplicated()]:
number.df["Date"]number.df["Date"].min()
And other methods, but nothing works. Any help is appreciated.
python pandas dataframe series glob
edited Nov 21 '18 at 15:04
Yuca
2,9042625
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
add a comment |
1
I have many excel files with the same columns in one folder. I need to browse each file and compare which values of the column "User Number" of one file are the same as the other file. And then manipulate another column named "Date" based on that. For exemple:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-11-04
18732A 2017-06-25
So in this case I want the program to check for matches of User Number values and then, if the date - linked to this number - of one file is different from the date of the other file, I want to change both dates to be the oldest date.
In this case I would have:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-08-06
18732A 2017-06-22
I appended all the files:
import os
import glob
import pandas as pd
path=r'C/.../files'
files = os.listdir(path)
df = pd.DataFrame()
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
df=df.append(data)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
The logic doesn't work like javascript logic, so I'm not sure how to do the condition. I've tried:
df_number = df["User Number"]
for number in df[df_number.duplicated()]:
number.df["Date"]number.df["Date"].min()
And other methods, but nothing works. Any help is appreciated.
python pandas dataframe series glob
edited Nov 21 '18 at 15:04
Yuca
2,9042625
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
are you sure your code is complete? last line of code seems like nonsense without '='
– Yuca
Nov 21 '18 at 15:11
it's not completed, I'm still trying to understand the logic. I don't know how to change the date based on the value of number (and at the same time compare both dates to see which one is the oldest).
– Fernanda F.
Nov 21 '18 at 15:14
add a comment |
1
1
1
I have many excel files with the same columns in one folder. I need to browse each file and compare which values of the column "User Number" of one file are the same as the other file. And then manipulate another column named "Date" based on that. For exemple:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-11-04
18732A 2017-06-25
So in this case I want the program to check for matches of User Number values and then, if the date - linked to this number - of one file is different from the date of the other file, I want to change both dates to be the oldest date.
In this case I would have:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-08-06
18732A 2017-06-22
I appended all the files:
import os
import glob
import pandas as pd
path=r'C/.../files'
files = os.listdir(path)
df = pd.DataFrame()
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
df=df.append(data)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
The logic doesn't work like javascript logic, so I'm not sure how to do the condition. I've tried:
df_number = df["User Number"]
for number in df[df_number.duplicated()]:
number.df["Date"]number.df["Date"].min()
And other methods, but nothing works. Any help is appreciated.
python pandas dataframe series glob
edited Nov 21 '18 at 15:04
Yuca
2,9042625
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
I have many excel files with the same columns in one folder. I need to browse each file and compare which values of the column "User Number" of one file are the same as the other file. And then manipulate another column named "Date" based on that. For exemple:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-11-04
18732A 2017-06-25
So in this case I want the program to check for matches of User Number values and then, if the date - linked to this number - of one file is different from the date of the other file, I want to change both dates to be the oldest date.
In this case I would have:
A2018_02_01 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
23872Z 2017-08-06
82716A 2017-09-18
77629B 2017-09-12
A2018_02_02 file has:
User_Number Date
18732A 2017-06-22
27192B 2017-08-06
54321R 2017-12-11
23872Z 2017-08-06
18732A 2017-06-22
I appended all the files:
import os
import glob
import pandas as pd
path=r'C/.../files'
files = os.listdir(path)
df = pd.DataFrame()
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
df=df.append(data)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
The logic doesn't work like javascript logic, so I'm not sure how to do the condition. I've tried:
df_number = df["User Number"]
for number in df[df_number.duplicated()]:
number.df["Date"]number.df["Date"].min()
And other methods, but nothing works. Any help is appreciated.
python pandas dataframe series glob
python pandas dataframe series glob
edited Nov 21 '18 at 15:04
Yuca
2,9042625
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
edited Nov 21 '18 at 15:04
Yuca
2,9042625
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
edited Nov 21 '18 at 15:04
Yuca
2,9042625
edited Nov 21 '18 at 15:04
Yuca
2,9042625
edited Nov 21 '18 at 15:04
Yuca
2,9042625
2,9042625
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
asked Nov 21 '18 at 14:59
Fernanda F.Fernanda F.
83
83
are you sure your code is complete? last line of code seems like nonsense without '='
– Yuca
Nov 21 '18 at 15:11
it's not completed, I'm still trying to understand the logic. I don't know how to change the date based on the value of number (and at the same time compare both dates to see which one is the oldest).
– Fernanda F.
Nov 21 '18 at 15:14
add a comment |
are you sure your code is complete? last line of code seems like nonsense without '='
– Yuca
Nov 21 '18 at 15:11
it's not completed, I'm still trying to understand the logic. I don't know how to change the date based on the value of number (and at the same time compare both dates to see which one is the oldest).
– Fernanda F.
Nov 21 '18 at 15:14
are you sure your code is complete? last line of code seems like nonsense without '='
– Yuca
Nov 21 '18 at 15:11
are you sure your code is complete? last line of code seems like nonsense without '='
– Yuca
Nov 21 '18 at 15:11
it's not completed, I'm still trying to understand the logic. I don't know how to change the date based on the value of number (and at the same time compare both dates to see which one is the oldest).
– Fernanda F.
Nov 21 '18 at 15:14
it's not completed, I'm still trying to understand the logic. I don't know how to change the date based on the value of number (and at the same time compare both dates to see which one is the oldest).
– Fernanda F.
Nov 21 '18 at 15:14
add a comment |
1 Answer
1
active
oldest
votes
1
My solution is to create a master mapper with all the min dates:
master=pd.concat([df1, df2]).groupby('User_Number').min()
and then join each dataframe to the master to find the adjusted date:
df1.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
df2.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
Output:
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 23872Z 2017-08-06
3 82716A 2017-09-18
4 77629B 2017-09-12
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 54321R 2017-12-11
3 23872Z 2017-08-06
4 18732A 2017-06-22
Adapting it to your code:
list_of_df =
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
list_of_df.append(data)
df = pd.concat(list_of_df)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
master=df.groupby('User_Number').min()
for aux_df in list_of_df:
aux_df['Date'] = aux_df.join(master,rsuffix='_adj',on='User_Number')[['Date_adj']])
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
It works, thanks so much! :D
– Fernanda F.
Nov 21 '18 at 16:48
I did it :) just another question: in this case, you compared 2 dataframes. How can I do it with an unknown number of dataframes? I have a file with x dataframes.
– Fernanda F.
Nov 21 '18 at 17:05
when you say that I compare, I guess you refer to the concatenation of two dataframes. If you have a list of dataframes,pd.concat(list_of_df)will create one from all your dfs
– Yuca
Nov 21 '18 at 17:08
<code> for f in glob.glob(path + "/*.xlsx"): data = pd.read_excel(f,header=2) df=df.concat(data) .groupby('User_Number').min() data.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']]) <code>but when I call data, I get an error saying that data is not defined
– Fernanda F.
Nov 21 '18 at 17:16
I updated my answer to better fit your original code
– Yuca
Nov 21 '18 at 17:24
|
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
My solution is to create a master mapper with all the min dates:
master=pd.concat([df1, df2]).groupby('User_Number').min()
and then join each dataframe to the master to find the adjusted date:
df1.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
df2.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
Output:
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 23872Z 2017-08-06
3 82716A 2017-09-18
4 77629B 2017-09-12
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 54321R 2017-12-11
3 23872Z 2017-08-06
4 18732A 2017-06-22
Adapting it to your code:
list_of_df =
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
list_of_df.append(data)
df = pd.concat(list_of_df)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
master=df.groupby('User_Number').min()
for aux_df in list_of_df:
aux_df['Date'] = aux_df.join(master,rsuffix='_adj',on='User_Number')[['Date_adj']])
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
It works, thanks so much! :D
– Fernanda F.
Nov 21 '18 at 16:48
I did it :) just another question: in this case, you compared 2 dataframes. How can I do it with an unknown number of dataframes? I have a file with x dataframes.
– Fernanda F.
Nov 21 '18 at 17:05
when you say that I compare, I guess you refer to the concatenation of two dataframes. If you have a list of dataframes,pd.concat(list_of_df)will create one from all your dfs
– Yuca
Nov 21 '18 at 17:08
<code> for f in glob.glob(path + "/*.xlsx"): data = pd.read_excel(f,header=2) df=df.concat(data) .groupby('User_Number').min() data.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']]) <code>but when I call data, I get an error saying that data is not defined
– Fernanda F.
Nov 21 '18 at 17:16
I updated my answer to better fit your original code
– Yuca
Nov 21 '18 at 17:24
|
show 1 more comment
1
My solution is to create a master mapper with all the min dates:
master=pd.concat([df1, df2]).groupby('User_Number').min()
and then join each dataframe to the master to find the adjusted date:
df1.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
df2.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
Output:
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 23872Z 2017-08-06
3 82716A 2017-09-18
4 77629B 2017-09-12
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 54321R 2017-12-11
3 23872Z 2017-08-06
4 18732A 2017-06-22
Adapting it to your code:
list_of_df =
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
list_of_df.append(data)
df = pd.concat(list_of_df)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
master=df.groupby('User_Number').min()
for aux_df in list_of_df:
aux_df['Date'] = aux_df.join(master,rsuffix='_adj',on='User_Number')[['Date_adj']])
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
It works, thanks so much! :D
– Fernanda F.
Nov 21 '18 at 16:48
I did it :) just another question: in this case, you compared 2 dataframes. How can I do it with an unknown number of dataframes? I have a file with x dataframes.
– Fernanda F.
Nov 21 '18 at 17:05
when you say that I compare, I guess you refer to the concatenation of two dataframes. If you have a list of dataframes,pd.concat(list_of_df)will create one from all your dfs
– Yuca
Nov 21 '18 at 17:08
<code> for f in glob.glob(path + "/*.xlsx"): data = pd.read_excel(f,header=2) df=df.concat(data) .groupby('User_Number').min() data.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']]) <code>but when I call data, I get an error saying that data is not defined
– Fernanda F.
Nov 21 '18 at 17:16
I updated my answer to better fit your original code
– Yuca
Nov 21 '18 at 17:24
|
show 1 more comment
1
1
1
My solution is to create a master mapper with all the min dates:
master=pd.concat([df1, df2]).groupby('User_Number').min()
and then join each dataframe to the master to find the adjusted date:
df1.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
df2.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
Output:
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 23872Z 2017-08-06
3 82716A 2017-09-18
4 77629B 2017-09-12
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 54321R 2017-12-11
3 23872Z 2017-08-06
4 18732A 2017-06-22
Adapting it to your code:
list_of_df =
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
list_of_df.append(data)
df = pd.concat(list_of_df)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
master=df.groupby('User_Number').min()
for aux_df in list_of_df:
aux_df['Date'] = aux_df.join(master,rsuffix='_adj',on='User_Number')[['Date_adj']])
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
My solution is to create a master mapper with all the min dates:
master=pd.concat([df1, df2]).groupby('User_Number').min()
and then join each dataframe to the master to find the adjusted date:
df1.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
df2.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']])
Output:
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 23872Z 2017-08-06
3 82716A 2017-09-18
4 77629B 2017-09-12
User_Number Date_adj
0 18732A 2017-06-22
1 27192B 2017-08-06
2 54321R 2017-12-11
3 23872Z 2017-08-06
4 18732A 2017-06-22
Adapting it to your code:
list_of_df =
for f in glob.glob(path + "/*.xlsx"):
data = pd.read_excel(f,header=2)
list_of_df.append(data)
df = pd.concat(list_of_df)
df["Date"]=pd.to_datetime(df["Date"], errors='coerce')
master=df.groupby('User_Number').min()
for aux_df in list_of_df:
aux_df['Date'] = aux_df.join(master,rsuffix='_adj',on='User_Number')[['Date_adj']])
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
edited Nov 21 '18 at 17:24
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
answered Nov 21 '18 at 15:21
YucaYuca
2,9042625
2,9042625
It works, thanks so much! :D
– Fernanda F.
Nov 21 '18 at 16:48
I did it :) just another question: in this case, you compared 2 dataframes. How can I do it with an unknown number of dataframes? I have a file with x dataframes.
– Fernanda F.
Nov 21 '18 at 17:05
when you say that I compare, I guess you refer to the concatenation of two dataframes. If you have a list of dataframes,pd.concat(list_of_df)will create one from all your dfs
– Yuca
Nov 21 '18 at 17:08
<code> for f in glob.glob(path + "/*.xlsx"): data = pd.read_excel(f,header=2) df=df.concat(data) .groupby('User_Number').min() data.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']]) <code>but when I call data, I get an error saying that data is not defined
– Fernanda F.
Nov 21 '18 at 17:16
I updated my answer to better fit your original code
– Yuca
Nov 21 '18 at 17:24
|
show 1 more comment
It works, thanks so much! :D
– Fernanda F.
Nov 21 '18 at 16:48
I did it :) just another question: in this case, you compared 2 dataframes. How can I do it with an unknown number of dataframes? I have a file with x dataframes.
– Fernanda F.
Nov 21 '18 at 17:05
when you say that I compare, I guess you refer to the concatenation of two dataframes. If you have a list of dataframes,pd.concat(list_of_df)will create one from all your dfs
– Yuca
Nov 21 '18 at 17:08
<code> for f in glob.glob(path + "/*.xlsx"): data = pd.read_excel(f,header=2) df=df.concat(data) .groupby('User_Number').min() data.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']]) <code>but when I call data, I get an error saying that data is not defined
– Fernanda F.
Nov 21 '18 at 17:16
I updated my answer to better fit your original code
– Yuca
Nov 21 '18 at 17:24
It works, thanks so much! :D
– Fernanda F.
Nov 21 '18 at 16:48
It works, thanks so much! :D
– Fernanda F.
Nov 21 '18 at 16:48
I did it :) just another question: in this case, you compared 2 dataframes. How can I do it with an unknown number of dataframes? I have a file with x dataframes.
– Fernanda F.
Nov 21 '18 at 17:05
I did it :) just another question: in this case, you compared 2 dataframes. How can I do it with an unknown number of dataframes? I have a file with x dataframes.
– Fernanda F.
Nov 21 '18 at 17:05
when you say that I compare, I guess you refer to the concatenation of two dataframes. If you have a list of dataframes,
pd.concat(list_of_df) will create one from all your dfs– Yuca
Nov 21 '18 at 17:08
when you say that I compare, I guess you refer to the concatenation of two dataframes. If you have a list of dataframes,
pd.concat(list_of_df) will create one from all your dfs– Yuca
Nov 21 '18 at 17:08
<code> for f in glob.glob(path + "/*.xlsx"): data = pd.read_excel(f,header=2) df=df.concat(data) .groupby('User_Number').min() data.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']]) <code>but when I call data, I get an error saying that data is not defined
– Fernanda F.
Nov 21 '18 at 17:16
<code> for f in glob.glob(path + "/*.xlsx"): data = pd.read_excel(f,header=2) df=df.concat(data) .groupby('User_Number').min() data.join(master,rsuffix='_adj',on='User_Number')[['User_Number', 'Date_adj']]) <code>but when I call data, I get an error saying that data is not defined
– Fernanda F.
Nov 21 '18 at 17:16
I updated my answer to better fit your original code
– Yuca
Nov 21 '18 at 17:24
I updated my answer to better fit your original code
– Yuca
Nov 21 '18 at 17:24
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are you sure your code is complete? last line of code seems like nonsense without '='
– Yuca
Nov 21 '18 at 15:11
it's not completed, I'm still trying to understand the logic. I don't know how to change the date based on the value of number (and at the same time compare both dates to see which one is the oldest).
– Fernanda F.
Nov 21 '18 at 15:14