pypsa-eur/data/heat_load_profile.csv

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hour,residential space weekday,residential space weekend,residential water weekday,residential water weekend,services space weekday,services space weekend,services water weekday,services water weekend
0,0.9181438689,0.9421512708,1,1,0.9181438689,0.9421512708,1,1
1,0.9172359071,0.9400891069,1,1,0.9172359071,0.9400891069,1,1
2,0.9269464481,0.9461062015,1,1,0.9269464481,0.9461062015,1,1
3,0.9415047932,0.9535084941,1,1,0.9415047932,0.9535084941,1,1
4,0.9656299507,0.9651094993,1,1,0.9656299507,0.9651094993,1,1
5,1.0221166443,0.9834676747,1,1,1.0221166443,0.9834676747,1,1
6,1.1553090493,1.0124171051,1,1,1.1553090493,1.0124171051,1,1
7,1.2093411031,1.0446615927,1,1,1.2093411031,1.0446615927,1,1
8,1.1470295942,1.088203419,1,1,1.1470295942,1.088203419,1,1
9,1.0877191341,1.1110334576,1,1,1.0877191341,1.1110334576,1,1
10,1.0418327372,1.0926752822,1,1,1.0418327372,1.0926752822,1,1
11,1.0062977133,1.055488209,1,1,1.0062977133,1.055488209,1,1
12,0.9837030359,1.0251266112,1,1,0.9837030359,1.0251266112,1,1
13,0.9667570278,0.9990015154,1,1,0.9667570278,0.9990015154,1,1
14,0.9548320932,0.9782897278,1,1,0.9548320932,0.9782897278,1,1
15,0.9509232061,0.9698167237,1,1,0.9509232061,0.9698167237,1,1
16,0.9636973319,0.974288587,1,1,0.9636973319,0.974288587,1,1
17,0.9799372563,0.9886456216,1,1,0.9799372563,0.9886456216,1,1
18,1.0046501848,1.0084159643,1,1,1.0046501848,1.0084159643,1,1
19,1.0079452419,1.0171243296,1,1,1.0079452419,1.0171243296,1,1
20,0.9860566481,0.9994722379,1,1,0.9860566481,0.9994722379,1,1
21,0.9705228074,0.982761591,1,1,0.9705228074,0.982761591,1,1
22,0.9586485819,0.9698167237,1,1,0.9586485819,0.9698167237,1,1
23,0.9335023778,0.9515079292,1,1,0.9335023778,0.9515079292,1,1