Basic example to calculate heat demand

python_scripts/run_simstadt_from_python/Parse heat demand csv.ipynb

+%% Cell type:code id:d2c68f35 tags:
+
+``` python
+import pandas as pd
+```
+
+%% Cell type:code id:66f2a037 tags:
+
+``` python
+df = pd.read_csv(r"C:\Users\eric.duminil\git\simstadt2\TestRepository\Gruenbuehl.proj\99_HeatDemand.flow\04_MonthlyEnergyBalance.step\Gruenbuehl_LOD2_ALKIS_1010_DIN18599_HEATING.csv",
+            skiprows=list(range(19)) + [20],
+            sep=';',
+            decimal=','
+           )
+```
+
+%% Cell type:code id:c94d6456 tags:
+
+``` python
+df
+```
+
+%%%% Output: execute_result
+
+                     GMLId  ParentGMLId  Latitude  Longitude  X-coordinate  \
+    0    DEBW_LOD2_1004495          NaN  48.87950    9.21478    3515829.63
+    1    DEBW_LOD2_1004496          NaN  48.87939    9.21456    3515813.56
+    2    DEBW_LOD2_1003853          NaN  48.87800    9.21559    3515888.84
+    3    DEBW_LOD2_1003651          NaN  48.87778    9.21467    3515821.59
+    4    DEBW_LOD2_1003854          NaN  48.87811    9.21559    3515889.08
+    ..                 ...          ...       ...        ...           ...
+    100     DEBW_LOD2_2158          NaN  48.87861    9.21813    3516075.53
+    101     DEBW_LOD2_2200          NaN  48.87856    9.21908    3516145.22
+    102     DEBW_LOD2_2147          NaN  48.87856    9.21771    3516044.74
+    103     DEBW_LOD2_2146          NaN  48.87869    9.21771    3516044.42
+    104     DEBW_LOD2_1249          NaN  48.87922    9.21722    3516008.53
+    
+         Y-coordinate    LOD  Year of construction  Year of refurbishment  \
+    0      5415809.40  LOD_2                  1968                    NaN
+    1      5415796.91  LOD_2                  1968                    NaN
+    2      5415642.86  LOD_2                  1968                    NaN
+    3      5415617.69  LOD_2                  1957                    NaN
+    4      5415655.22  LOD_2                  1968                    NaN
+    ..            ...    ...                   ...                    ...
+    100    5415710.81  LOD_2                  1968                    NaN
+    101    5415705.71  LOD_2                  1994                    NaN
+    102    5415705.26  LOD_2                  1968                    NaN
+    103    5415719.66  LOD_2                  1968                    NaN
+    104    5415779.04  LOD_2                  1968                    NaN
+    
+        Refurbishment Variant  ...  March Heating demand April Heating demand  \
+    0                Original  ...                 15987                 4566
+    1                Original  ...                  3973                 1011
+    2                Original  ...                  2998                  868
+    3                Original  ...                 11847                 2785
+    4                Original  ...                  3669                 1102
+    ..                    ...  ...                   ...                  ...
+    100              Original  ...                  8581                 2153
+    101              Original  ...                 15099                 2708
+    102              Original  ...                  8622                 2174
+    103              Original  ...                  6895                 1762
+    104              Original  ...                  7505                 1981
+    
+         May Heating demand June Heating demand  July Heating demand  \
+    0                   673                   2                    0
+    1                   117                   0                    0
+    2                   125                   0                    0
+    3                   333                   1                    0
+    4                   154                   0                    0
+    ..                  ...                 ...                  ...
+    100                 289                   1                    0
+    101                 207                   1                    0
+    102                 298                   1                    0
+    103                 226                   1                    0
+    104                 254                   0                    0
+    
+        August Heating demand  September Heating demand  October Heating demand  \
+    0                       0                       690                    8449
+    1                       0                       120                    2085
+    2                       0                       120                    1578
+    3                       0                       401                    6428
+    4                       0                       140                    1938
+    ..                    ...                       ...                     ...
+    100                     0                       286                    4447
+    101                     0                       295                    7775
+    102                     0                       292                    4476
+    103                     0                       284                    3871
+    104                     0                       307                    4159
+    
+         November Heating demand  December Heating demand
+    0                      19075                    26508
+    1                       4933                     6905
+    2                       3597                     5006
+    3                      15161                    21212
+    4                       4310                     5964
+    ..                       ...                      ...
+    100                    10780                    15176
+    101                    20013                    28298
+    102                    10820                    15219
+    103                     8580                    11813
+    104                     9307                    12859
+    
+    [105 rows x 54 columns]
+
+%% Cell type:code id:adbf8c7c tags:
+
+``` python
+df['Yearly Heating demand'].sum()
+```
+
+%%%% Output: execute_result
+
+    8001948
+
+%% Cell type:code id:9c62ba61 tags:
+
+``` python
+```