Adding row and column total to pivot table fails
0
I want to display row and column total. I am using margin=True but the output does not show row total as below code and output:
import pandas as pd
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
pvt_all=pvt_all[['received','sent','to_send']]
pvt_all
received sent to_send
site
2 32.0 27.0 5.0
3 20.0 17.0 3.0
4 33.0 31.0 2.0
5 40.0 31.0 9.0
All 125.0 106.0 19.0
Sample data below to allow easiness for you besides it is a long one. You can also find in url provided in df vector above. The DataFrame consists of four variables: date, site, received and sent.
date site received sent
7/10/2018 2
7/10/2018 2
7/11/2018 2
7/11/2018 2
7/11/2018 2
7/12/2018 2
7/12/2018 2
7/12/2018 2
7/13/2018 2 7/13/2018 12:50 7/18/2018 14:44
7/13/2018 2
7/18/2018 2
7/19/2018 2
7/19/2018 2
7/23/2018 2
7/23/2018 2
7/12/2018 2
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7/19/2018 2
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7/26/2018 2
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7/25/2018 2
7/24/2018 2
7/23/2018 2 7/23/2018 15:53 7/25/2018 10:35
7/24/2018 2
7/23/2018 2
7/23/2018 2 7/23/2018 15:53 7/25/2018 10:35
7/24/2018 2
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7/23/2018 2 7/23/2018 15:53 7/25/2018 10:35
7/23/2018 2 7/23/2018 15:53 7/25/2018 10:35
7/23/2018 2
7/23/2018 2 7/23/2018 15:53 7/25/2018 10:35
7/24/2018 2
7/9/2018 2
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7/9/2018 2 7/9/2018 15:19 7/11/2018 10:25
7/10/2018 2 7/10/2018 12:26 7/11/2018 10:25
7/10/2018 2
7/19/2018 2
7/19/2018 2
7/19/2018 2 7/19/2018 14:22 7/25/2018 10:35
7/23/2018 2
7/23/2018 2 7/23/2018 15:53 7/25/2018 10:35
7/23/2018 2
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7/19/2018 5
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7/10/2018 2 7/10/2018 12:26 7/11/2018 10:25
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7/11/2018 2 7/11/2018 14:54 7/18/2018 14:44
7/11/2018 2
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7/18/2018 2 7/18/2018 14:35 7/25/2018 10:35
7/19/2018 2
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7/26/2018 2 7/26/2018 15:35
7/25/2018 2
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7/23/2018 2
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7/24/2018 2 7/24/2018 15:31 7/25/2018 10:35
7/25/2018 2
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7/25/2018 2 7/25/2018 15:34
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7/3/2018 2 7/3/2018 15:20 7/4/2018 11:35
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7/25/2018 2
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7/5/2018 2 7/5/2018 15:15 7/11/2018 10:25
7/6/2018 2
7/9/2018 2 7/9/2018 15:19 7/11/2018 10:25
7/9/2018 2
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7/5/2018 2 7/5/2018 15:15 7/11/2018 10:25
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7/2/2018 2 7/2/2018 15:38 7/4/2018 11:35
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7/17/2018 2
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7/27/2018 2
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6/19/2018 5 6/19/2018 14:20 6/28/2018 14:20
6/19/2018 5 6/19/2018 14:20 6/28/2018 14:20
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python pandas rowsum column-sum
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
|
show 2 more comments
0
I want to display row and column total. I am using margin=True but the output does not show row total as below code and output:
import pandas as pd
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
pvt_all=pvt_all[['received','sent','to_send']]
pvt_all
received sent to_send
site
2 32.0 27.0 5.0
3 20.0 17.0 3.0
4 33.0 31.0 2.0
5 40.0 31.0 9.0
All 125.0 106.0 19.0
Sample data below to allow easiness for you besides it is a long one. You can also find in url provided in df vector above. The DataFrame consists of four variables: date, site, received and sent.
date site received sent
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python pandas rowsum column-sum
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
would you be able to post the sample data? and you may want to look at this post
– MattR
Jan 10 at 21:03
@MattR, sample data are already in the code here: df2 = pd.read_csv("dropbox.com/s/90y07129zn351z9/…)
– MGB.py
Jan 10 at 21:05
@MattR, I already had read that podt you shared and thought not applicable to my case.Thanks
– MGB.py
Jan 10 at 21:08
1
the reason why you will want to add sample data instead of dropbox is two fold. Some people do not want to go to external sites to help answer your question. Also, if that link breaks in the future, those who come to this post won't be able to follow along. I suggest you add the sample data and read this post on creating good pandas examples. The easier you make it for those to help you, the more help you may receive :)
– MattR
Jan 10 at 21:23
@MattR, thanks for your explanation and clarification. Now, I understand the reasons. Please, check again, I have updated my question.
– MGB.py
Jan 10 at 22:28
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I want to display row and column total. I am using margin=True but the output does not show row total as below code and output:
import pandas as pd
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
pvt_all=pvt_all[['received','sent','to_send']]
pvt_all
received sent to_send
site
2 32.0 27.0 5.0
3 20.0 17.0 3.0
4 33.0 31.0 2.0
5 40.0 31.0 9.0
All 125.0 106.0 19.0
Sample data below to allow easiness for you besides it is a long one. You can also find in url provided in df vector above. The DataFrame consists of four variables: date, site, received and sent.
date site received sent
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python pandas rowsum column-sum
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
I want to display row and column total. I am using margin=True but the output does not show row total as below code and output:
import pandas as pd
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
pvt_all=pvt_all[['received','sent','to_send']]
pvt_all
received sent to_send
site
2 32.0 27.0 5.0
3 20.0 17.0 3.0
4 33.0 31.0 2.0
5 40.0 31.0 9.0
All 125.0 106.0 19.0
Sample data below to allow easiness for you besides it is a long one. You can also find in url provided in df vector above. The DataFrame consists of four variables: date, site, received and sent.
date site received sent
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python pandas rowsum column-sum
python pandas rowsum column-sum
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
edited Jan 10 at 22:27
MGB.py
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
asked Jan 10 at 20:42
MGB.pyMGB.py
6510
6510
would you be able to post the sample data? and you may want to look at this post
– MattR
Jan 10 at 21:03
@MattR, sample data are already in the code here: df2 = pd.read_csv("dropbox.com/s/90y07129zn351z9/…)
– MGB.py
Jan 10 at 21:05
@MattR, I already had read that podt you shared and thought not applicable to my case.Thanks
– MGB.py
Jan 10 at 21:08
1
the reason why you will want to add sample data instead of dropbox is two fold. Some people do not want to go to external sites to help answer your question. Also, if that link breaks in the future, those who come to this post won't be able to follow along. I suggest you add the sample data and read this post on creating good pandas examples. The easier you make it for those to help you, the more help you may receive :)
– MattR
Jan 10 at 21:23
@MattR, thanks for your explanation and clarification. Now, I understand the reasons. Please, check again, I have updated my question.
– MGB.py
Jan 10 at 22:28
|
show 2 more comments
would you be able to post the sample data? and you may want to look at this post
– MattR
Jan 10 at 21:03
@MattR, sample data are already in the code here: df2 = pd.read_csv("dropbox.com/s/90y07129zn351z9/…)
– MGB.py
Jan 10 at 21:05
@MattR, I already had read that podt you shared and thought not applicable to my case.Thanks
– MGB.py
Jan 10 at 21:08
1
the reason why you will want to add sample data instead of dropbox is two fold. Some people do not want to go to external sites to help answer your question. Also, if that link breaks in the future, those who come to this post won't be able to follow along. I suggest you add the sample data and read this post on creating good pandas examples. The easier you make it for those to help you, the more help you may receive :)
– MattR
Jan 10 at 21:23
@MattR, thanks for your explanation and clarification. Now, I understand the reasons. Please, check again, I have updated my question.
– MGB.py
Jan 10 at 22:28
would you be able to post the sample data? and you may want to look at this post
– MattR
Jan 10 at 21:03
would you be able to post the sample data? and you may want to look at this post
– MattR
Jan 10 at 21:03
@MattR, sample data are already in the code here: df2 = pd.read_csv("dropbox.com/s/90y07129zn351z9/…)
– MGB.py
Jan 10 at 21:05
@MattR, sample data are already in the code here: df2 = pd.read_csv("dropbox.com/s/90y07129zn351z9/…)
– MGB.py
Jan 10 at 21:05
@MattR, I already had read that podt you shared and thought not applicable to my case.Thanks
– MGB.py
Jan 10 at 21:08
@MattR, I already had read that podt you shared and thought not applicable to my case.Thanks
– MGB.py
Jan 10 at 21:08
1
1
the reason why you will want to add sample data instead of dropbox is two fold. Some people do not want to go to external sites to help answer your question. Also, if that link breaks in the future, those who come to this post won't be able to follow along. I suggest you add the sample data and read this post on creating good pandas examples. The easier you make it for those to help you, the more help you may receive :)
– MattR
Jan 10 at 21:23
the reason why you will want to add sample data instead of dropbox is two fold. Some people do not want to go to external sites to help answer your question. Also, if that link breaks in the future, those who come to this post won't be able to follow along. I suggest you add the sample data and read this post on creating good pandas examples. The easier you make it for those to help you, the more help you may receive :)
– MattR
Jan 10 at 21:23
@MattR, thanks for your explanation and clarification. Now, I understand the reasons. Please, check again, I have updated my question.
– MGB.py
Jan 10 at 22:28
@MattR, thanks for your explanation and clarification. Now, I understand the reasons. Please, check again, I have updated my question.
– MGB.py
Jan 10 at 22:28
|
show 2 more comments
2 Answers
2
active
oldest
votes
1
Try this, using eval:
df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index='site', values=['received','sent'],
aggfunc='count', margins=True, dropna=False).eval('Total = received + sent')
Output:
received sent Total
site
2 32 27 59
3 20 17 37
4 33 31 64
5 40 31 71
All 125 106 231
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
Thanks but doesnt work for me. 8 pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent']) .pivot_table(index='site', values=['received','sent'], aggfunc='count', margins=True, dropna=False).eval('Total = received + sent') ----> 9 pvt_all['to_send']= pvt_all['received']-pvt_all['sent'] 10 pvt_all=pvt_all[['received','sent','to_send']] 11 pvt_all TypeError: 'NoneType' object is not subscriptable
– MGB.py
Jan 10 at 23:07
add a comment |
0
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
import pandas as pd
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
#pvt_all['Total'] = pvt_all.received + pvt_all.sent + pvt_all.to_send
pvt_all['Total'] = pvt_all.sum(axis=1) #Add Total column for row subtotal
#and Total
pvt_all=pvt_all[['received','sent','to_send','Total']]
pvt_all
received sent to_send Total
site
2 32.0 27.0 5.0 64.0
3 20.0 17.0 3.0 40.0
4 33.0 31.0 2.0 66.0
5 40.0 31.0 9.0 80.0
All 125.0 106.0 19.0 250.0
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
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
1
Try this, using eval:
df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index='site', values=['received','sent'],
aggfunc='count', margins=True, dropna=False).eval('Total = received + sent')
Output:
received sent Total
site
2 32 27 59
3 20 17 37
4 33 31 64
5 40 31 71
All 125 106 231
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
Thanks but doesnt work for me. 8 pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent']) .pivot_table(index='site', values=['received','sent'], aggfunc='count', margins=True, dropna=False).eval('Total = received + sent') ----> 9 pvt_all['to_send']= pvt_all['received']-pvt_all['sent'] 10 pvt_all=pvt_all[['received','sent','to_send']] 11 pvt_all TypeError: 'NoneType' object is not subscriptable
– MGB.py
Jan 10 at 23:07
add a comment |
1
Try this, using eval:
df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index='site', values=['received','sent'],
aggfunc='count', margins=True, dropna=False).eval('Total = received + sent')
Output:
received sent Total
site
2 32 27 59
3 20 17 37
4 33 31 64
5 40 31 71
All 125 106 231
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
Thanks but doesnt work for me. 8 pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent']) .pivot_table(index='site', values=['received','sent'], aggfunc='count', margins=True, dropna=False).eval('Total = received + sent') ----> 9 pvt_all['to_send']= pvt_all['received']-pvt_all['sent'] 10 pvt_all=pvt_all[['received','sent','to_send']] 11 pvt_all TypeError: 'NoneType' object is not subscriptable
– MGB.py
Jan 10 at 23:07
add a comment |
1
1
1
Try this, using eval:
df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index='site', values=['received','sent'],
aggfunc='count', margins=True, dropna=False).eval('Total = received + sent')
Output:
received sent Total
site
2 32 27 59
3 20 17 37
4 33 31 64
5 40 31 71
All 125 106 231
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
Try this, using eval:
df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index='site', values=['received','sent'],
aggfunc='count', margins=True, dropna=False).eval('Total = received + sent')
Output:
received sent Total
site
2 32 27 59
3 20 17 37
4 33 31 64
5 40 31 71
All 125 106 231
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
answered Jan 10 at 22:40
Scott BostonScott Boston
53.5k73055
53.5k73055
Thanks but doesnt work for me. 8 pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent']) .pivot_table(index='site', values=['received','sent'], aggfunc='count', margins=True, dropna=False).eval('Total = received + sent') ----> 9 pvt_all['to_send']= pvt_all['received']-pvt_all['sent'] 10 pvt_all=pvt_all[['received','sent','to_send']] 11 pvt_all TypeError: 'NoneType' object is not subscriptable
– MGB.py
Jan 10 at 23:07
add a comment |
Thanks but doesnt work for me. 8 pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent']) .pivot_table(index='site', values=['received','sent'], aggfunc='count', margins=True, dropna=False).eval('Total = received + sent') ----> 9 pvt_all['to_send']= pvt_all['received']-pvt_all['sent'] 10 pvt_all=pvt_all[['received','sent','to_send']] 11 pvt_all TypeError: 'NoneType' object is not subscriptable
– MGB.py
Jan 10 at 23:07
Thanks but doesnt work for me. 8 pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent']) .pivot_table(index='site', values=['received','sent'], aggfunc='count', margins=True, dropna=False).eval('Total = received + sent') ----> 9 pvt_all['to_send']= pvt_all['received']-pvt_all['sent'] 10 pvt_all=pvt_all[['received','sent','to_send']] 11 pvt_all TypeError: 'NoneType' object is not subscriptable
– MGB.py
Jan 10 at 23:07
Thanks but doesnt work for me. 8 pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent']) .pivot_table(index='site', values=['received','sent'], aggfunc='count', margins=True, dropna=False).eval('Total = received + sent') ----> 9 pvt_all['to_send']= pvt_all['received']-pvt_all['sent'] 10 pvt_all=pvt_all[['received','sent','to_send']] 11 pvt_all TypeError: 'NoneType' object is not subscriptable
– MGB.py
Jan 10 at 23:07
add a comment |
0
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
import pandas as pd
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
#pvt_all['Total'] = pvt_all.received + pvt_all.sent + pvt_all.to_send
pvt_all['Total'] = pvt_all.sum(axis=1) #Add Total column for row subtotal
#and Total
pvt_all=pvt_all[['received','sent','to_send','Total']]
pvt_all
received sent to_send Total
site
2 32.0 27.0 5.0 64.0
3 20.0 17.0 3.0 40.0
4 33.0 31.0 2.0 66.0
5 40.0 31.0 9.0 80.0
All 125.0 106.0 19.0 250.0
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
add a comment |
0
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
import pandas as pd
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
#pvt_all['Total'] = pvt_all.received + pvt_all.sent + pvt_all.to_send
pvt_all['Total'] = pvt_all.sum(axis=1) #Add Total column for row subtotal
#and Total
pvt_all=pvt_all[['received','sent','to_send','Total']]
pvt_all
received sent to_send Total
site
2 32.0 27.0 5.0 64.0
3 20.0 17.0 3.0 40.0
4 33.0 31.0 2.0 66.0
5 40.0 31.0 9.0 80.0
All 125.0 106.0 19.0 250.0
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
add a comment |
0
0
0
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
import pandas as pd
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
#pvt_all['Total'] = pvt_all.received + pvt_all.sent + pvt_all.to_send
pvt_all['Total'] = pvt_all.sum(axis=1) #Add Total column for row subtotal
#and Total
pvt_all=pvt_all[['received','sent','to_send','Total']]
pvt_all
received sent to_send Total
site
2 32.0 27.0 5.0 64.0
3 20.0 17.0 3.0 40.0
4 33.0 31.0 2.0 66.0
5 40.0 31.0 9.0 80.0
All 125.0 106.0 19.0 250.0
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
df2 = pd.read_csv("https://www.dropbox.com/s/90y07129zn351z9/test_data.csv?dl=1",encoding="latin-1")
df2['received'] = pd.to_datetime(df2['received'])
df2['sent'] = pd.to_datetime(df2['sent'])
import pandas as pd
pvt_all = df2.dropna(axis=0, how='all', subset=['received', 'sent'])
.pivot_table(index=['site'], values=['received','sent'],
aggfunc='count', margins=True, dropna=False)
pvt_all['to_send']= pvt_all['received']-pvt_all['sent']
#pvt_all['Total'] = pvt_all.received + pvt_all.sent + pvt_all.to_send
pvt_all['Total'] = pvt_all.sum(axis=1) #Add Total column for row subtotal
#and Total
pvt_all=pvt_all[['received','sent','to_send','Total']]
pvt_all
received sent to_send Total
site
2 32.0 27.0 5.0 64.0
3 20.0 17.0 3.0 40.0
4 33.0 31.0 2.0 66.0
5 40.0 31.0 9.0 80.0
All 125.0 106.0 19.0 250.0
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
answered Jan 18 at 23:39
MGB.pyMGB.py
6510
6510
add a comment |
add a comment |
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would you be able to post the sample data? and you may want to look at this post
– MattR
Jan 10 at 21:03
@MattR, sample data are already in the code here: df2 = pd.read_csv("dropbox.com/s/90y07129zn351z9/…)
– MGB.py
Jan 10 at 21:05
@MattR, I already had read that podt you shared and thought not applicable to my case.Thanks
– MGB.py
Jan 10 at 21:08
1
the reason why you will want to add sample data instead of dropbox is two fold. Some people do not want to go to external sites to help answer your question. Also, if that link breaks in the future, those who come to this post won't be able to follow along. I suggest you add the sample data and read this post on creating good pandas examples. The easier you make it for those to help you, the more help you may receive :)
– MattR
Jan 10 at 21:23
@MattR, thanks for your explanation and clarification. Now, I understand the reasons. Please, check again, I have updated my question.
– MGB.py
Jan 10 at 22:28