Postgres 9.5

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CREATE TABLE sales (
    id SERIAL PRIMARY KEY,
    country VARCHAR(255),
    sales_date DATE,
    sales_volume DECIMAL,
    fix_costs DECIMAL
);

INSERT INTO sales
(country, sales_date, sales_volume, fix_costs
)
VALUES 

('DE', '2020-01-03', '500', '0'),
('NL', '2020-01-03', '320', '0'),
('FR', '2020-01-03', '350', '0'),
('None', '2020-01-31', '0', '2000'),

('DE', '2020-02-15', '0', '0'),
('NL', '2020-02-15', '0', '0'),
('FR', '2020-02-15', '0', '0'),
('None', '2020-02-29', '0', '5000'),

('DE', '2020-03-27', '180', '0'),
('NL', '2020-03-27', '670', '0'),
('FR', '2020-03-27', '970', '0'),
('None', '2020-03-31', '0', '4000');
12 rows affected

SELECT
    *,
    NULLIF(SUM(sales_volume) FILTER (WHERE country != 'NL') OVER (PARTITION BY s1.sales_date), 0)
FROM sales s1


id
country
sales_date
sales_volume
fix_costs
nullif


1
DE
2020-01-03
500
0
850

2
NL
2020-01-03
320
0
850

3
FR
2020-01-03
350
0
850

4
None
2020-01-31
0
2000
null

5
DE
2020-02-15
0
0
null

6
NL
2020-02-15
0
0
null

7
FR
2020-02-15
0
0
null

8
None
2020-02-29
0
5000
null

9
DE
2020-03-27
180
0
1150

10
NL
2020-03-27
670
0
1150

11
FR
2020-03-27
970
0
1150

12
None
2020-03-31
0
4000
null


SELECT
    *,
    CASE WHEN country != 'NL' THEN sales_volume END 
        / NULLIF(SUM(sales_volume) FILTER (WHERE country != 'NL')  OVER (PARTITION BY s1.sales_date), 0)
FROM sales s1


id
country
sales_date
sales_volume
fix_costs
?column?


1
DE
2020-01-03
500
0
0.58823529411764705882

2
NL
2020-01-03
320
0
null

3
FR
2020-01-03
350
0
0.41176470588235294118

4
None
2020-01-31
0
2000
null

5
DE
2020-02-15
0
0
null

6
NL
2020-02-15
0
0
null

7
FR
2020-02-15
0
0
null

8
None
2020-02-29
0
5000
null

9
DE
2020-03-27
180
0
0.15652173913043478261

10
NL
2020-03-27
670
0
null

11
FR
2020-03-27
970
0
0.84347826086956521739

12
None
2020-03-31
0
4000
null


SELECT
    *,
    CASE WHEN s1.country != 'NL' THEN s1.sales_volume END  
        / NULLIF(SUM(s1.sales_volume) FILTER (WHERE s1.country != 'NL')  OVER (PARTITION BY s1.sales_date), 0)
FROM sales s1
JOIN sales s2 ON s1.country <> 'None' AND s2.country = 'None' 
    AND date_trunc('month', s1.sales_date) = date_trunc('month', s2.sales_date)


id
country
sales_date
sales_volume
fix_costs
id
country
sales_date
sales_volume
fix_costs
?column?


1
DE
2020-01-03
500
0
4
None
2020-01-31
0
2000
0.58823529411764705882

2
NL
2020-01-03
320
0
4
None
2020-01-31
0
2000
null

3
FR
2020-01-03
350
0
4
None
2020-01-31
0
2000
0.41176470588235294118

5
DE
2020-02-15
0
0
8
None
2020-02-29
0
5000
null

6
NL
2020-02-15
0
0
8
None
2020-02-29
0
5000
null

7
FR
2020-02-15
0
0
8
None
2020-02-29
0
5000
null

9
DE
2020-03-27
180
0
12
None
2020-03-31
0
4000
0.15652173913043478261

10
NL
2020-03-27
670
0
12
None
2020-03-31
0
4000
null

11
FR
2020-03-27
970
0
12
None
2020-03-31
0
4000
0.84347826086956521739


SELECT
    s1.*,
    s2.fix_costs / date_part('day', s2.sales_date),
    CASE WHEN s1.country != 'NL' THEN s1.sales_volume END  
        / NULLIF(SUM(s1.sales_volume) FILTER (WHERE s1.country != 'NL')  OVER (PARTITION BY s1.sales_date), 0)
FROM sales s1
JOIN sales s2 ON s1.country <> 'None' AND s2.country = 'None' 
    AND date_trunc('month', s1.sales_date) = date_trunc('month', s2.sales_date)


id
country
sales_date
sales_volume
fix_costs
?column?
?column?


1
DE
2020-01-03
500
0
64.5161290322581
0.58823529411764705882

2
NL
2020-01-03
320
0
64.5161290322581
null

3
FR
2020-01-03
350
0
64.5161290322581
0.41176470588235294118

5
DE
2020-02-15
0
0
172.413793103448
null

6
NL
2020-02-15
0
0
172.413793103448
null

7
FR
2020-02-15
0
0
172.413793103448
null

9
DE
2020-03-27
180
0
129.032258064516
0.15652173913043478261

10
NL
2020-03-27
670
0
129.032258064516
null

11
FR
2020-03-27
970
0
129.032258064516
0.84347826086956521739


SELECT
    s1.*,
    s2.fix_costs / date_part('day', s2.sales_date) *
        CASE WHEN s1.country != 'NL' THEN s1.sales_volume END  
            / NULLIF(SUM(s1.sales_volume) FILTER (WHERE s1.country != 'NL')  OVER (PARTITION BY s1.sales_date), 0)
FROM sales s1
JOIN sales s2 ON s1.country <> 'None' AND s2.country = 'None' 
    AND date_trunc('month', s1.sales_date) = date_trunc('month', s2.sales_date)


id
country
sales_date
sales_volume
fix_costs
?column?


1
DE
2020-01-03
500
0
37.9506641366224

2
NL
2020-01-03
320
0
null

3
FR
2020-01-03
350
0
26.5654648956357

5
DE
2020-02-15
0
0
null

6
NL
2020-02-15
0
0
null

7
FR
2020-02-15
0
0
null

9
DE
2020-03-27
180
0
20.1963534361851

10
NL
2020-03-27
670
0
null

11
FR
2020-03-27
970
0
108.835904628331


SELECT
    s1.*,
    COALESCE(
        s2.fix_costs / date_part('day', s2.sales_date) *
            CASE WHEN s1.country != 'NL' THEN s1.sales_volume END  
                / NULLIF(SUM(s1.sales_volume) FILTER (WHERE s1.country != 'NL')  OVER (PARTITION BY s1.sales_date), 0)
    , 0)        
FROM sales s1
JOIN sales s2 ON s1.country <> 'None' AND s2.country = 'None' 
    AND date_trunc('month', s1.sales_date) = date_trunc('month', s2.sales_date)


id
country
sales_date
sales_volume
fix_costs
coalesce


1
DE
2020-01-03
500
0
37.9506641366224

2
NL
2020-01-03
320
0
0

3
FR
2020-01-03
350
0
26.5654648956357

5
DE
2020-02-15
0
0
0

6
NL
2020-02-15
0
0
0

7
FR
2020-02-15
0
0
0

9
DE
2020-03-27
180
0
20.1963534361851

10
NL
2020-03-27
670
0
0

11
FR
2020-03-27
970
0
108.835904628331

id	country	sales_date	sales_volume	fix_costs	nullif
1	DE	2020-01-03	500	0	850
2	NL	2020-01-03	320	0	850
3	FR	2020-01-03	350	0	850
4	None	2020-01-31	0	2000	null
5	DE	2020-02-15	0	0	null
6	NL	2020-02-15	0	0	null
7	FR	2020-02-15	0	0	null
8	None	2020-02-29	0	5000	null
9	DE	2020-03-27	180	0	1150
10	NL	2020-03-27	670	0	1150
11	FR	2020-03-27	970	0	1150
12	None	2020-03-31	0	4000	null

id	country	sales_date	sales_volume	fix_costs	?column?
1	DE	2020-01-03	500	0	0.58823529411764705882
2	NL	2020-01-03	320	0	null
3	FR	2020-01-03	350	0	0.41176470588235294118
4	None	2020-01-31	0	2000	null
5	DE	2020-02-15	0	0	null
6	NL	2020-02-15	0	0	null
7	FR	2020-02-15	0	0	null
8	None	2020-02-29	0	5000	null
9	DE	2020-03-27	180	0	0.15652173913043478261
10	NL	2020-03-27	670	0	null
11	FR	2020-03-27	970	0	0.84347826086956521739
12	None	2020-03-31	0	4000	null

id	country	sales_date	sales_volume	?column?	?column?
1	DE	2020-01-03	500	64.5161290322581	0.58823529411764705882
2	NL	2020-01-03	320	64.5161290322581	null
3	FR	2020-01-03	350	64.5161290322581	0.41176470588235294118
5	DE	2020-02-15	0	172.413793103448	null
6	NL	2020-02-15	0	172.413793103448	null
7	FR	2020-02-15	0	172.413793103448	null
9	DE	2020-03-27	180	129.032258064516	0.15652173913043478261
10	NL	2020-03-27	670	129.032258064516	null
11	FR	2020-03-27	970	129.032258064516	0.84347826086956521739

id	country	sales_date	sales_volume	?column?
1	DE	2020-01-03	500	37.9506641366224
2	NL	2020-01-03	320	null
3	FR	2020-01-03	350	26.5654648956357
5	DE	2020-02-15	0	null
6	NL	2020-02-15	0	null
7	FR	2020-02-15	0	null
9	DE	2020-03-27	180	20.1963534361851
10	NL	2020-03-27	670	null
11	FR	2020-03-27	970	108.835904628331