`query_crossborder_flows` fails in August 2021 for `DE`->`NL` #144

charelF · 2021-11-23T10:15:00Z

Problem

There seems to be a problem with crossborder flows query_crossborder_flows.
In particular, querying over DE -> NL crossborder flows over summer 2021, there is a bug in august.
I assume it happens because the frequency in July is hourly data, and in September its quarterly (15min) data. Probably somewhere in august it switches from hourly to quarterly, which in turn messes up the dataframe and causes the error

Information

pandas: 1.3.4
entsoe-py: 0.4.1
python: 3.9.7
os: macOS monterey 12.0.1

Reproduction

July 2021: Correct

start = pd.Timestamp(str(int(2021_07_01)), tz='Europe/Amsterdam')
end = pd.Timestamp(str(int(2021_08_01)), tz='Europe/Amsterdam')
client.query_crossborder_flows("DE", "NL", start=start, end=end)

returns the expected output:

2021-07-01 00:00:00+02:00    1110.0
2021-07-01 01:00:00+02:00     925.0
2021-07-01 02:00:00+02:00     540.0
2021-07-01 03:00:00+02:00     743.0
2021-07-01 04:00:00+02:00     538.0
                              ...  
2021-07-31 19:00:00+02:00    1437.0
2021-07-31 20:00:00+02:00    1266.0
2021-07-31 21:00:00+02:00    2218.0
2021-07-31 22:00:00+02:00    2171.0
2021-07-31 23:00:00+02:00    2313.0
Freq: 60T, Length: 744, dtype: float64

September 2021: Correct

Similarly,

start = pd.Timestamp(str(int(2021_09_01)), tz='Europe/Amsterdam')
end = pd.Timestamp(str(int(2021_10_01)), tz='Europe/Amsterdam')
client.query_crossborder_flows("DE", "NL", start=start, end=end)

returns the expected output:

2021-09-01 00:00:00+02:00    2579.0
2021-09-01 00:15:00+02:00    2430.0
2021-09-01 00:30:00+02:00    2378.0
2021-09-01 00:45:00+02:00    2281.0
2021-09-01 01:00:00+02:00    2287.0
                              ...  
2021-09-30 22:45:00+02:00     843.0
2021-09-30 23:00:00+02:00    1210.0
2021-09-30 23:15:00+02:00    1191.0
2021-09-30 23:30:00+02:00    1233.0
2021-09-30 23:45:00+02:00    1233.0
Freq: 15T, Length: 2880, dtype: float64

August 2021: Problem

However this one fails:

start = pd.Timestamp(str(int(2021_08_01)), tz='Europe/Amsterdam')
end = pd.Timestamp(str(int(2021_09_01)), tz='Europe/Amsterdam')
client.query_crossborder_flows("DE", "NL", start=start, end=end)

with

ValueError: Length mismatch: Expected axis has 22 elements, new values have 85 elements

Lastly, I just wanted to thank all contributors of this library, it has saved me enormous amount of time and headaches I had working with the entsoe XML API. Thanks!

The text was updated successfully, but these errors were encountered:

charelF · 2021-11-23T10:16:29Z

Here is the full error message btw:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/d9/6_lw279s459fpbps9x1mxd6m0000gn/T/ipykernel_18198/2060622407.py in <module>
      1 start = pd.Timestamp(str(int(2021_08_01)), tz='Europe/Amsterdam')
      2 end = pd.Timestamp(str(int(2021_09_01)), tz='Europe/Amsterdam')
----> 3 client.query_crossborder_flows("DE", "NL", start=start, end=end)

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/entsoe/decorators.py in year_wrapper(start, end, *args, **kwargs)
     62         for _start, _end in blocks:
     63             try:
---> 64                 frame = func(*args, start=_start, end=_end, **kwargs)
     65             except NoMatchingDataError:
     66                 logging.debug(f"NoMatchingDataError: between {_start} and {_end}")

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/entsoe/entsoe.py in query_crossborder_flows(self, country_code_from, country_code_to, start, end, **kwargs)
   1180             start=start,
   1181             end=end)
-> 1182         ts = parse_crossborder_flows(text)
   1183         ts = ts.tz_convert(area_from.tz)
   1184         ts = ts.truncate(before=start, after=end)

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/entsoe/parsers.py in parse_crossborder_flows(xml_text)
    229     series = pd.Series(dtype = 'object')
    230     for soup in _extract_timeseries(xml_text):
--> 231         series = series.append(_parse_crossborder_flows_timeseries(soup))
    232     series = series.sort_index()
    233     return series

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/entsoe/parsers.py in _parse_crossborder_flows_timeseries(soup)
    659     series = pd.Series(index=positions, data=flows)
    660     series = series.sort_index()
--> 661     series.index = _parse_datetimeindex(soup)
    662 
    663     return series

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pandas/core/generic.py in __setattr__(self, name, value)
   5498         try:
   5499             object.__getattribute__(self, name)
-> 5500             return object.__setattr__(self, name, value)
   5501         except AttributeError:
   5502             pass

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pandas/_libs/properties.pyx in pandas._libs.properties.AxisProperty.__set__()

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pandas/core/series.py in _set_axis(self, axis, labels, fastpath)
    557         if not fastpath:
    558             # The ensure_index call above ensures we have an Index object
--> 559             self._mgr.set_axis(axis, labels)
    560 
    561     # ndarray compatibility

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pandas/core/internals/managers.py in set_axis(self, axis, new_labels)
    214     def set_axis(self, axis: int, new_labels: Index) -> None:
    215         # Caller is responsible for ensuring we have an Index object.
--> 216         self._validate_set_axis(axis, new_labels)
    217         self.axes[axis] = new_labels
    218 

/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/pandas/core/internals/base.py in _validate_set_axis(self, axis, new_labels)
     55 
     56         elif new_len != old_len:
---> 57             raise ValueError(
     58                 f"Length mismatch: Expected axis has {old_len} elements, new "
     59                 f"values have {new_len} elements"

ValueError: Length mismatch: Expected axis has 22 elements, new values have 85 elements

fboerman · 2021-11-23T10:21:07Z

Hi thanks for your elaborate report! I will look into it when I get home/have time. Is this possibly related to #133? Also you're welcome thanks for the kind words! Sent from ProtonMail mobile

…

-------- Original Message --------

On 23 Nov 2021, 11:16, Charel Felten wrote: Here is the full error message btw: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - ValueError Traceback ( most recent call last ) / var / folders / d9 / 6_l w279s459fpbps9x1mxd6m0000gn / T / ipykernel_18198 / 2060622407. py in < module > 1 start = pd . Timestamp ( str ( int ( 2021_08_01 )), tz = 'Europe/Amsterdam' ) 2 end = pd . Timestamp ( str ( int ( 2021_09_01 )), tz = 'Europe/Amsterdam' ) - - - - > 3 client . query_crossborder_flows ( "DE" , "NL" , start = start , end = end ) / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / entsoe / decorators . py in year_wrapper ( start , end , * args , ** kwargs ) 62 for _start , _end in blocks : 63 try : - - - > 64 frame = func ( * args , start = _start , end = _end , ** kwargs ) 65 except NoMatchingDataError : 66 logging . debug ( f"NoMatchingDataError: between { _start } and { _end } " ) / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / entsoe / entsoe . py in query_crossborder_flows ( self , country_code_from , country_code_to , start , end , ** kwargs ) 1180 start = start , 1181 end = end ) -> 1182 ts = parse_crossborder_flows ( text ) 1183 ts = ts . tz_convert ( area_from . tz ) 1184 ts = ts . truncate ( before = start , after = end ) / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / entsoe / parsers . py in parse_crossborder_flows ( xml_text ) 229 series = pd . Series ( dtype = 'object' ) 230 for soup in _extract_timeseries ( xml_text ): - - > 231 series = series . append ( _parse_crossborder_flows_timeseries ( soup )) 232 series = series . sort_index () 233 return series / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / entsoe / parsers . py in _parse_crossborder_flows_timeseries ( soup ) 659 series = pd . Series ( index = positions , data = flows ) 660 series = series . sort_index () - - > 661 series . index = _parse_datetimeindex ( soup ) 662 663 return series / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / pandas / core / generic . py in __setattr__ ( self , name , value ) 5498 try : 5499 object . __getattribute__ ( self , name ) -> 5500 return object . __setattr__ ( self , name , value ) 5501 except AttributeError : 5502 pass / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / pandas / _libs / properties . pyx in pandas . _libs . properties . AxisProperty . __set__ () / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / pandas / core / series . py in _set_axis ( self , axis , labels , fastpath ) 557 if not fastpath : 558 # The ensure_index call above ensures we have an Index object - - > 559 self . _mgr . set_axis ( axis , labels ) 560 561 # ndarray compatibility / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / pandas / core / internals / managers . py in set_axis ( self , axis , new_labels ) 214 def set_axis ( self , axis : int , new_labels : Index ) - > None : 215 # Caller is responsible for ensuring we have an Index object. - - > 216 self . _validate_set_axis ( axis , new_labels ) 217 self . axes [ axis ] = new_labels 218 / Library / Frameworks / Python . framework / Versions / 3.9 / lib / python3 . 9 / site - packages / pandas / core / internals / base . py in _validate_set_axis ( self , axis , new_labels ) 55 56 elif new_len != old_len : - - - > 57 raise ValueError ( 58 f"Length mismatch: Expected axis has { old_len } elements, new " 59 f"values have { new_len } elements" ValueError : Length mismatch : Expected axis has 22 elements , new values have 85 elements — You are receiving this because you are subscribed to this thread. Reply to this email directly, [view it on GitHub](#144 (comment)), or [unsubscribe](https://github.com/notifications/unsubscribe-auth/ABEC63WKXBCLX2HFTKTY4QDUNNSYRANCNFSM5ITDSPTQ). Triage notifications on the go with GitHub Mobile for [iOS](https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675) or [Android](https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub).

charelF · 2021-11-23T10:28:01Z

I'm not sure its related to #137 given that user seems to have incorrect data whereas in my case it just fails.

Altough interestingly

start = pd.Timestamp(str(int(2021_08_01)), tz='Europe/Amsterdam')
end = pd.Timestamp(str(int(2021_09_01)), tz='Europe/Amsterdam')
client.query_crossborder_flows("CZ", "AT", start=start, end=end)

returns

2021-08-01 00:00:00+02:00    1103.0
2021-08-01 01:00:00+02:00    1121.0
2021-08-01 02:00:00+02:00    1062.0
2021-08-01 03:00:00+02:00    1037.0
2021-08-01 04:00:00+02:00     945.0
                              ...  
2021-08-31 19:00:00+02:00     899.0
2021-08-31 20:00:00+02:00     821.0
2021-08-31 21:00:00+02:00     766.0
2021-08-31 22:00:00+02:00    1054.0
2021-08-31 23:00:00+02:00     969.0
Freq: 60T, Length: 744, dtype: float64

which is indeed a DataFrame, which makes me think that the issue I have is potentially only present from DE->NL queries. I added this to the title of the issue.

fboerman · 2021-11-23T10:30:49Z

Yes it is true that 15 min trading was introduced this year for that border. It is very possible that that breaks some assumption of the code. Sent from ProtonMail mobile

…

-------- Original Message --------

On 23 Nov 2021, 11:28, Charel Felten wrote: I'm not sure its related to [#137](#137) given that user seems to have incorrect data whereas in my case it just fails. Altough interestingly start = pd . Timestamp ( str ( int ( 2021_08_01 )), tz = 'Europe/Amsterdam' ) end = pd . Timestamp ( str ( int ( 2021_09_01 )), tz = 'Europe/Amsterdam' ) client . query_crossborder_flows ( "CZ" , "AT" , start = start , end = end ) returns 2021-08-01 00:00:00+02:00 1103.0 2021-08-01 01:00:00+02:00 1121.0 2021-08-01 02:00:00+02:00 1062.0 2021-08-01 03:00:00+02:00 1037.0 2021-08-01 04:00:00+02:00 945.0 ... 2021-08-31 19:00:00+02:00 899.0 2021-08-31 20:00:00+02:00 821.0 2021-08-31 21:00:00+02:00 766.0 2021-08-31 22:00:00+02:00 1054.0 2021-08-31 23:00:00+02:00 969.0 Freq: 60T, Length: 744, dtype: float64 which is indeed a DataFrame, which makes me think that the issue I have is potentially only present from DE->NL queries. I added this to the title of the issue. — You are receiving this because you commented. Reply to this email directly, [view it on GitHub](#144 (comment)), or [unsubscribe](https://github.com/notifications/unsubscribe-auth/ABEC63UEXBNU75FBTAACNT3UNNUDXANCNFSM5ITDSPTQ). Triage notifications on the go with GitHub Mobile for [iOS](https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675) or [Android](https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub).

charelF · 2021-11-23T10:44:33Z

It gets a bit weirder:

I narrowed the problem down to the 1st of August 2021. Because from August 2nd onwards, we get the correct result (15min interval)

start = pd.Timestamp(year=2021, month=8, day=2, tz='Europe/Amsterdam')
end = pd.Timestamp(year=2021, month=9, day=1, tz='Europe/Amsterdam')
client.query_crossborder_flows("DE", "NL", start=start, end=end)

gives the correct looking df:

2021-08-02 02:00:00+02:00    2144.0
2021-08-02 02:15:00+02:00    1819.0
2021-08-02 02:30:00+02:00    1677.0
2021-08-02 02:45:00+02:00    1559.0
2021-08-02 03:00:00+02:00    1343.0
                              ...  
2021-08-31 22:45:00+02:00    3312.0
2021-08-31 23:00:00+02:00    3314.0
2021-08-31 23:15:00+02:00    3290.0
2021-08-31 23:30:00+02:00    3276.0
2021-08-31 23:45:00+02:00    3145.0
Freq: 15T, Length: 2872, dtype: float64

The problem seems to be only for 1st of august, for example:

start = pd.Timestamp(year=2021, month=8, day=1, hour=10, tz='Europe/Amsterdam')
end = pd.Timestamp(year=2021, month=8, day=1, hour=15, tz='Europe/Amsterdam')
client.query_crossborder_flows("DE", "NL", start=start, end=end)

gives again:

ValueError: Length mismatch: Expected axis has 5 elements, new values have 17 elements

However what is really interesting:

Querying every single hour of august 1st individually does work:

for h1, h2 in zip(range(23), range(1,24)):
    start = pd.Timestamp(year=2021, month=8, day=1, hour=h1, tz='Europe/Amsterdam')
    end = pd.Timestamp(year=2021, month=8, day=1, hour=h2, tz='Europe/Amsterdam')
    print(client.query_crossborder_flows("DE", "NL", start=start, end=end))

gives

2021-08-01 00:00:00+02:00    1345.0
Freq: 60T, dtype: float64
2021-08-01 01:00:00+02:00    1046.0
Freq: 60T, dtype: float64
2021-08-01 02:00:00+02:00    1070.0
Freq: 15T, dtype: float64
2021-08-01 03:00:00+02:00    1965.0
Freq: 15T, dtype: float64
2021-08-01 04:00:00+02:00    1950.0
Freq: 15T, dtype: float64
2021-08-01 05:00:00+02:00    2696.0
Freq: 15T, dtype: float64
2021-08-01 06:00:00+02:00    2276.0
Freq: 15T, dtype: float64
2021-08-01 07:00:00+02:00    2174.0
Freq: 15T, dtype: float64
2021-08-01 08:00:00+02:00    1366.0
Freq: 15T, dtype: float64
2021-08-01 09:00:00+02:00    799.0
Freq: 15T, dtype: float64
2021-08-01 10:00:00+02:00    453.0
Freq: 15T, dtype: float64
2021-08-01 11:00:00+02:00    252.0
Freq: 15T, dtype: float64
2021-08-01 12:00:00+02:00    561.0
Freq: 15T, dtype: float64
2021-08-01 13:00:00+02:00    451.0
Freq: 15T, dtype: float64
2021-08-01 14:00:00+02:00    226.0
Freq: 15T, dtype: float64
2021-08-01 15:00:00+02:00    179.0
Freq: 15T, dtype: float64
2021-08-01 16:00:00+02:00    563.0
Freq: 15T, dtype: float64
2021-08-01 17:00:00+02:00    1833.0
Freq: 15T, dtype: float64
2021-08-01 18:00:00+02:00    2561.0
Freq: 15T, dtype: float64
2021-08-01 19:00:00+02:00    1432.0
Freq: 15T, dtype: float64
2021-08-01 20:00:00+02:00    1609.0
Freq: 15T, dtype: float64
2021-08-01 21:00:00+02:00    1405.0
Freq: 15T, dtype: float64
2021-08-01 22:00:00+02:00    2261.0
Freq: 15T, dtype: float64

To me it looks like the frequency is changed from 60T to 15T halfway through the day, which I assume means from 1H to 15min, however the data returned on that day is still only hourly. And if querying for multiple hours on that day, we get 1H data from entsoe, while the index freq is 15min, which causes the problems. At least that is my hypothesis right now.

fboerman · 2021-11-23T19:52:24Z

hi @charelF thank you for your thorough investigation. That seems like a very good reasoning of why it goes wrong. The question is what would be the best fix. This is a one time occurence so maybe just put in a static fix would be fine. But it is possible that this will occur on more borders. I am not sure yet what is the best solution. Do you have a good idea?

charelF · 2021-11-23T21:00:42Z

Do you have a good idea?

Unfortunately I am both new to this library and also new to this domain, so I do not feel qualified to give an answer on how to best fix this in the library (particularly since the call stack is still somewhat obscure to me, in particular the soup parts) nor to comment on how common this would be on other borders.

That being said, I did more investigations:

On here, I looked at the 3 dates:
https://transparency.entsoe.eu/transmission-domain/physicalFlow/show?name=&defaultValue=false&viewType=TABLE&areaType=BORDER_CTY&atch=false&dateTime.dateTime=31.07.2021+00:00|UTC|DAY&border.values=CTY|10YNL----------L!CTY_CTY|10YNL----------L_CTY_CTY|10Y1001A1001A83F&dateTime.timezone=UTC&dateTime.timezone_input=UTC

July 31st 2021

We have normal 1 hour intervals

August 2nd 2021

Normal 15 min intervals

August 1st 2021

Oh no... so it looks like a mix between 1 hour intervals and 15 min intervals --> This is probably where the error comes from, so I assume its an issue from entsoe

I checked, an this issue is not present for any of the other borders of NL, at least not on that particular day.

With these insights, I would say this is an error from entsoe, so probably a manual fix would apply here, since one can assume this should not happen again...

fboerman · 2021-11-23T21:06:26Z

Do you have a good idea?

Unfortunately I am both new to this library and also new to this domain, so I do not feel qualified to give an answer on how to best fix this in the library (particularly since the call stack is still somewhat obscure to me, in particular the soup parts) nor to comment on how common this would be on other borders.

That being said, I did more investigations:

On here, I looked at the 3 dates: https://transparency.entsoe.eu/transmission-domain/physicalFlow/show?name=&defaultValue=false&viewType=TABLE&areaType=BORDER_CTY&atch=false&dateTime.dateTime=31.07.2021+00:00|UTC|DAY&border.values=CTY|10YNL----------L!CTY_CTY|10YNL----------L_CTY_CTY|10Y1001A1001A83F&dateTime.timezone=UTC&dateTime.timezone_input=UTC

July 31st 2021

We have normal 1 hour intervals

August 2nd 2021

Normal 15 min intervals

August 1st 2021

Oh no... so it looks like a mix between 1 hour intervals and 15 min intervals --> This is probably where the error comes from, so I assume its an issue from entsoe

I checked, an this issue is not present for any of the other borders of NL, at least not on that particular day.

With these insights, I would say this is an error from entsoe, so probably a manual fix would apply here, since one can assume this should not happen again...

I can perhaps look up the exact implementation date of the 15 min trade. it is very possible it is not a problem from entsoe but from tennet side on the way it is reported. I will talk to my contact at the TenneT transparancy team tomorrow (disclaimer: I also work at TenneT) how this was handled. Thanks for the thorough background info! I whish that all issue authors would be like this haha

charelF · 2021-11-23T21:18:00Z

Thanks for the thorough background info! I whish that all issue authors would be like this haha

Thanks, I am happy to pay some of the time this library saved me back!

fboerman · 2021-11-24T16:51:02Z

hi @charelF I have poked some people and they are looking into it. ill update the issue when I know more

MattEwen · 2021-12-16T10:10:59Z

Hiya - just wanted to add that the same issue seems to occur for Germany for both Switzerland:

and Luxembourg:

where the time granularity changes early in the month and means the data can't be parsed. I get the same

ValueError: Length mismatch: Expected axis has 22 elements, new values have 85 elements

Only mention this because strangely I don't get this error for DE and NL - only on these two cases.

And thanks again so much for the library, it really is great

fboerman · 2021-12-17T10:15:11Z

hi @MattEwen this seems like a consistent issue then. I will open a support ticket with entsoe.

fboerman · 2022-01-06T15:29:37Z

hi @MattEwen I have received a reply it is fixed now on dutch borders but the other borders they are sill looking into.

fboerman · 2022-01-14T14:43:40Z

hi @MattEwen and @charelF the issue is now fixed by ENTSO-E for all cases we discussed here :D

charelF · 2022-01-15T09:44:49Z

thanks, thats nice to hear!

charelF changed the title ~~query_crossborder_flows fails in August 2021~~ query_crossborder_flows fails in August 2021 for DE->NL Nov 23, 2021

fboerman added the server bug when an issue isn't entsoe-py's issue, but on the server side label Nov 24, 2021

fboerman closed this as completed Jan 14, 2022

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`query_crossborder_flows` fails in August 2021 for `DE`->`NL` #144

`query_crossborder_flows` fails in August 2021 for `DE`->`NL` #144

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July 31st 2021

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charelF commented Jan 15, 2022

query_crossborder_flows fails in August 2021 for DE->NL #144

query_crossborder_flows fails in August 2021 for DE->NL #144

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charelF commented Nov 23, 2021 • edited Loading

Problem

Information

Reproduction

July 2021: Correct

September 2021: Correct

August 2021: Problem

charelF commented Nov 23, 2021

fboerman commented Nov 23, 2021 via email

charelF commented Nov 23, 2021

fboerman commented Nov 23, 2021 via email

charelF commented Nov 23, 2021

However what is really interesting:

fboerman commented Nov 23, 2021

charelF commented Nov 23, 2021 • edited Loading

July 31st 2021

August 2nd 2021

August 1st 2021

fboerman commented Nov 23, 2021

July 31st 2021

August 2nd 2021

August 1st 2021

charelF commented Nov 23, 2021 • edited Loading

fboerman commented Nov 24, 2021

MattEwen commented Dec 16, 2021

fboerman commented Dec 17, 2021

fboerman commented Jan 6, 2022

fboerman commented Jan 14, 2022 • edited Loading

charelF commented Jan 15, 2022

`query_crossborder_flows` fails in August 2021 for `DE`->`NL` #144

`query_crossborder_flows` fails in August 2021 for `DE`->`NL` #144

charelF commented Nov 23, 2021 •

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charelF commented Nov 23, 2021 •

edited

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charelF commented Nov 23, 2021 •

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fboerman commented Jan 14, 2022 •

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