Thanks!

Here are series from ECB not updated in Dbnomics since 2024:

EXR.D.E03.EUR.EN00.A
EXR.D.USD.EUR.SP00.A
EXR.M.E02.EUR.EN00.A
EXR.M.E02.EUR.ERP0.A
EXR.M.E02.EUR.ERC0.A
EXR.M.E03.EUR.ERC0.A
EXR.M.E03.EUR.EN00.A
EXR.M.CNY.EUR.SP00.A
EXR.M.CNY.EUR.SP00.E
EXR.M.JPY.EUR.SP00.A
EXR.M.JPY.EUR.SP00.E
EXR.M.GBP.EUR.SP00.A
EXR.M.GBP.EUR.SP00.E
EXR.M.RUB.EUR.SP00.A
EXR.M.RUB.EUR.SP00.E
EXR.Q.E02.EUR.ERD0.A
EXR.Q.E02.EUR.ERU1.A
BSI.M..N.A.A20.A.4.U6.2240.Z01.E
BSI.M..N.A.A20T.A.I.U2.2240.Z01.A
IVF.M.U2.N.T0.A5A.A.1.Z5.0000.Z01.E
IVF.M.U2.N.T0.T00.A.1.Z5.0000.Z01.E
BPS.Q.N.I9.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL
BPS.Q.Y.I9.W1.S1.S1.T.B.CA._Z._Z._Z.EUR._T._X.N.ALL
EWT.M.U2.N.WT.COVR._T.4F0._Z
EWT.M.U2.N.WT.INWS._T.4F0.GY
EWT.M.U2.N.WT.INWX._T.4F0.GY
EWT.M.U2.N.WT.INWR._T.4F0.GY
MNA.Q.Y..W2.S1.S1.B.B1GQ._Z._Z._Z.EUR.LR.N
MNA.Q.Y.I9.W0.S1.S1.D.P3T5._Z._Z._Z.EUR.LR.N
QSA.Q.Y..W0.S1.S1._Z.B.B6G._Z._Z._Z.XDC._T.S.V.N._T
QSA.Q.N..W0.S1.S1._Z.B.B6G._Z._Z._Z.XDC._T.S.V.N._T
QSA.Q.N..W0.S1M.S1._Z.B.B6G._Z._Z._Z.XDC._T.S.V.N._T
QSA.Q.N..W0.S1.S1._Z.B.B8G._Z._Z._Z.XDC._T.S.V.N._T
QSA.Q.N..W0.S1M.S1._Z.B.B8G._Z._Z._Z.XDC._T.S.V.N._T
QSA.Q.Y.*.W0.S1.S1._Z.B.B8G._Z._Z._Z.XDC._T.S.V.N._T
BLS.Q.U2.ALL.O.E.Z.B3.ST.S.WFNET
BLS.Q.U2.ALL.O.E.Z.B3.ZZ.D.WFNET
BLS.Q.U2.ALL.Z.H.H.B3.ZZ.D.WFNET
BLS.Q.U2.ALL.Z.H.C.B3.ZZ.D.WFNET

Not found in Dbnomics:
CAR.M.I9.Y.CREG.PC0000.4F0.N.PN
LFSI.M.I10.S.UNEHRT.TOTAL0.15_74.T
EWT.Q.U2.N.WT.INWR._T.4F0.G

Eric from BDF Paris

I’m using the python client to fetch data. Will the API key be relevant there too in the future?

Thanks in advance,

kr

Is there a problem with the fetcher? Even a monthly update would be great even though the policy rate data updates daily. I’m specifically after the BIS/WS_CBPOL data series.

Thank you!

However I didn’t find any NA in the Excel file (downloaded by clicking on the Download button from the link you provided). Could you tell me which period has a misleading NA?

Highly recommended — I’ll be revisiting this for reference

First off, you can now create your own user account. We warmly invite you to do so — having an account unlocks several features and will help us provide a better experience.

We’ve also replaced the cart with a star system: you can add a star to your favorite series and list them on your account page, similar to what you see on services like GitHub. Unlike the old cart, which was stored only locally in your browser, stars are linked to your user account. That means your starred series follow you across devices and browsers. On your first login, all series in your old cart will automatically be migrated to stars, so you won’t lose anything.

For those using our web API, please note that rate limits will soon apply to requests made without an API key. You can generate your API key directly from your account. After a grace period of three months, requests without a key will be blocked to prevent abuses and an error message will remind you to create one.

Navigation has been improved with a collapsible sidebar, which can be toggled using the button or the common shortcut Ctrl-B, giving you more space, especially on dataset pages.

Finally, we’ve added a Sponsorship page. Users and institutions can now support DBnomics through a paid plan and enjoy corresponding benefits, helping us sustain and grow the project. In particular, contributions directly help fund developers who fix data fetchers and reduce the delay between providers’ updates and their availability on DBnomics.

Our core premise remains the same: most macroeconomic series exist thanks to public funding. They are a common good for administrations, researchers, and businesses alike, and should be freely accessible without costly intermediaries.

I assume there might be a problem with the data fetcher for both providers. Can someone please check.

Very much appreciated!

Would it be possible to update the WEO for the October release. If anyone has any workarounds/ other code that you use for the October WEO through an API/function that would be great.

Cheers!

Japan National Accounts haven’t been updated on DBnomics, whereas they are online since yesterday on the ESRI website. Usually, the update is very quick. Do you know if they will be updated soon ?

Thanks a lot !

Sabine

In May I indeed saw the names of the series switched from lower case to uppercase. However, when i check it now, the most recent updates are done for the series with lower case again?

Also, I would expect that the gross part of the lower case and upper case series should be the same, but they seem to differ even for figures of >10y ago.

An example:

namq_10_an6, SCA, CLV20, National currency, quarterly data, N11MG for Bulgaria:
Eurostat/NAMQ_10_AN6/Q.CLV20_MNAC.N11MG.SCA.BG | DBnomics
vs.
Eurostat/namq_10_an6/Q.CLV20_MNAC.N11MG.SCA.BG | DBnomics

Checked the data on eurostat too, but this doesn’t really help, as the figures there are slightly different from both series on dbnomics, even though same filters are applied:

[namq_10_an6] Gross fixed capital formation by main asset type

Any idea which series will be continued (upper or lower case?). And possibly also any idea about the discrepancy with eurostat? For the unadjusted data (ie neither seasonally nor calendar adjusted), the non preliminary figures on dbnomics match the ones of eurostat.

Kr, rk

Working on the dbnomics client for gretl I came across a few anomalies in the category trees for certain providers, which make life a bit more difficult than it needs to be for authors of client programs.

• Almost all datasets have both a code and a name, but the OECD dataset with code “REGION_ECONOM” has a JSON null value in place of a name.
• In the tree for the Bank for International Settlements, many “name” fields have a string of the expected sort, but with a newline character and a chunk of whitespace appended.

In both of these cases some additional work is needed to make the “name” usable in third-party code.

I was wondering if somebody knows why the new Ameco spring forecasts published 19 of May dataset ist not available yet. Is the delay of availability usually this long for this dataset?

Thanks for your help!

I have been struggling with technical issues, sorry for the delay this time!

Now the datasets for 2025-04 are online:

• IMF/WEO:2025-04 | DBnomics
• IMF/WEOAGG:2025-04 | DBnomics

More context: IMF WEO datasets are published on a sub-part of IMF website as attached files, making difficult their automation.

Best regards,

Before: https://db.nomics.world/Eurostat/prc_hicp_MIDX
Now: Eurostat/PRC_HICP_MIDX | DBnomics

This may seem minor but basically implies all pre-existing code using this data via DBnomics won’t work unless adjusted.

More importantly, other data that is listed as available in the provider list (on DBnomics and is available in the original Eurostat website) is currently Non Available:

Example:
https://db.nomics.world/Eurostat/GOV_10DD_EDPT

I was able to idenfity other data with this issue. I put them here in case it helps:

LC_AN_COSTH
LC_LCI_LEV
GOV_10DD_EDPT2
GOV_10DD_EDPT3

I hope this can be resolved. I really like downloading economic/statistical data via DBnomics rather than through a browser in the original provider’s website.

Good luck with the fixes and thanks for your work!

C

A current related problem, however, is that for some data the link exists but the data shows as not available:
https://db.nomics.world/Eurostat/GOV_10DD_EDPT1

I was forced to download the data in Excel, and then transform them to match the DBnomics format as a temporary solution. I can share my Python code if you’d find it useful.

I was wondering if somebody knows why the new WEO April 2025 published 22 of April dataset ist not available yet here. Is the delay of availability usually this long?

Thanks for your help!

since this month I am facing an issue with the API for the following statement:

    def source_gdp_historical(self):
        return dbnomics.fetch_series(dataset_code="IFS", provider_code="IMF",
                                 series_code=f"A.{'+'.join(self.countries['Alpha-2'])}.NGDP_R_XDC", max_nb_series=500)

The following error is produced when calling my function:

dbnomics.FetchError: Could not fetch data from URL 'https://api.db.nomics.world/v22/series/IMF/IFS/A.AD+AE+AF+AG+AG+AI+AL+AM+AO+AQ+AR+AS+AT+AU+AW+AX+AZ+BA+BB+BD+BE+BF+BG+BH+BI+BJ+BL+BM+BN+BO+BQ+BR+BS+BT+BV+BW+BY+BZ+CA+CC+CD+CF+CG+CH+CI+CK+CL+CM+CN+CO+CR+CU+CV+CW+CX+CY+CZ+CZ+DE+DJ+DK+DM+DO+DZ+EC+EE+EG+EH+ER+ES+ET+FI+FJ+FK+FM+FO+FR+GA+GB+GD+GE+GF+GG+GH+GI+GL+GM+GN+GP+GQ+GR+GS+GT+GU+GW+GY+HK+HM+HN+HR+HT+HU+ID+IE+IL+IM+IN+IO+IQ+IR+IS+IT+JE+JM+JO+JP+KE+KG+KH+KI+KM+KN+KP+KR+KW+KY+KZ+LA+LB+LC+LI+LK+LR+LS+LT+LU+LV+LY+MA+MC+MD+ME+MF+MG+MH+MK+MK+ML+MM+MN+MO+MP+MQ+MR+MS+MT+MU+MV+MW+MX+MY+MZ+NA+NC+NE+NF+NG+NI+NL+NO+NP+NR+NU+NZ+OM+PA+PE+PF+PG+PH+PK+PL+PM+PN+PR+PS+PT+PW+PY+QA+RE+RO+RS+RU+RW+SA+SB+SC+SD+SE+SG+SH+SI+SJ+SK+SL+SM+SN+SO+SR+SS+ST+SV+SX+SY+SZ+SZ+TC+TD+TF+TG+TH+TJ+TK+TL+TL+TM+TN+TO+TR+TT+TT+TV+TW+TZ+UA+UG+UM+US+UY+UZ+VA+VC+VE+VG+VI+VN+VU+WF+WS+XK+YE+YT+ZA+ZM+ZW.NGDP_R_XDC?observations=1&offset=0'

When accessing the link directly via a browser you get the following error message:
{“_meta”:{“version”:“22.1.17”},“message”:“500 Internal Server Error: The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.”}

If “observations=1” is removed from the URL a response is given.

For context I am using Python 3.12. I have seen a similiar issue where the root cause was the httpx package. I have tried the newest Version, the Version that fixed the issue in the old Topic and a few between.

I am also using the latest dbnomics api version 1.2.6 (also tried 1.2.5)

Can you help me fix the issue?
Thank you!

Edit: From manual testing I saw that if I reduce the amount of countries to (<=100) the API request works. I will check tomorrow if it also works in the Python call.
A workaround could then be to loop over the countries and merge the results.

The internal Server Error also occurs when accessing the same data on the DBNomics side and clicking “Download”

Eurostat updated its SDMX API quite recently and I had to rewrite its data fetcher.

After a trial-and-error process it has now finished downloading and converting Eurostat data, and it is currently finishing importing data.

Up-to-date data should be available soon – a matter of days now.

Sorry for inconvenience. I will keep you informed here.

We are struggling with this data update stop as well.
Do you have any updates on the topic?

paybyplatema

I think I’m experiencing an issue similar to yours. I was using the rdbnomics package to extract the OECD EO data automatically using R, and just using “EO” as the dataset code would always return the latest version. However, for some time now, it has been returning an outdated version from 2024.

From what I can tell, the data is available though you would need to use “DSD_EO@DF_EO” instead of just “EO”. For me, changing this in my R code partially solved the issue and I was able to get the latest data as they appear on the website, though I wasn’t able to extract the whole dataset as I could before, just a few time series. Hope this helps.

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While exploring the tool, I noticed that it doesn’t directly provide a feature for zipping files, but I think this could be a valuable addition. I’ve had to rely on external software for this process, and while it works, it’s a bit cumbersome to handle files outside the tool. My idea is to integrate the ability to compress files into zip format directly within DBnomics. This could streamline workflows, especially for users like me who frequently work with datasets that need to be shared or stored efficiently. The ability to zip files within DBnomics itself could save time and make the platform even more user-friendly for people who don’t want to toggle between different tools.

To dive deeper into my thoughts, I feel that adding this feature would simplify how data is handled in DBnomics. Currently, when sharing large files, the need to manually compress them through a third-party tool adds an unnecessary layer of complexity. It’s a simple process in other platforms, and I believe it could fit seamlessly into DBnomics. By enabling users to zip their files directly within the platform, DBnomics could offer a more complete and integrated experience.

File to zip refers to the process of converting folders or files into a compressed .zip format. This format reduces the file size, making it easier to store and share large datasets. When you convert folders to .zip, multiple files are bundled together into a single compressed file, which significantly reduces the space they take up. This method not only saves storage space but also simplifies the sharing process by providing one file to send rather than multiple individual files. It’s a common practice in data management and file sharing across various tools and platforms, and I think it would be an excellent feature to include within DBnomics to enhance the user experience.

I was inspired by the simple concept of file compression that I came across while working with other tools. In my experience, tools that offer an integrated solution for file compression tend to improve efficiency significantly. It eliminates the need for users to download, compress, and then upload files back to a platform. Everything can be done within the same interface, leading to a more seamless workflow. I believe adding a zip feature would not only make the platform more comprehensive but also more attractive to a broader audience who values time-saving and simplicity.

I’m curious to know if others have found ways to overcome this limitation within DBnomics, or if anyone else sees this as an area for improvement. Perhaps there’s already a workaround I haven’t discovered yet, or maybe there’s a reason the zip feature hasn’t been integrated so far. I would love to hear from anyone with suggestions on how I might streamline this process or any insights into how DBnomics might improve in this area.

In particular, I’d like to know if anyone else feels the same need for a file compression feature within DBnomics. Could it be integrated in a way that would make the tool even more versatile without cluttering its interface? I’m open to ideas from the community on how to handle large files more effectively in DBnomics, and I’m eager to explore whether the tool can evolve to better meet these needs.

In conclusion, while I’m grateful for the functionality DBnomics offers, I think the ability to zip files within the platform would enhance my experience as a user. Not only would it save time, but it would also make sharing files with colleagues or partners much easier. I’m looking forward to hearing from others who might have had similar experiences or who might have solutions to this challenge. Your thoughts and input are greatly appreciated as I try to navigate this issue more effectively within the tool.

Can you please confirm whether or not there is something wrong with the data and if there is what would the ETA be for fixing those?

glanceintuitinfo

The fetcher for ONS was rewritten in 2025-01 and the datasets are now up-to-date.

Sorry for the late reply

Tellsubway

It appears from the database that the inflation dataset is being updated. However the latest observations are not showing up. At the moment the latest index values are from November, however the December index values were released some time ago.

Eurostat/prc_hicp_midx | DBnomics

Grateful if you could advise when this will be updated.

Could someone confirm whether more recent data will be pulled from WB soon, please?

filters <- list(
  sector = c("S1"),
  unit = "CP_MNAC",
  na_item = c("P52_P53"),
  s_adj = "NSA"
  #geo = "PL"
  #time = "2023-Q4"
)
dataset_code <- "nasq_10_nf_tr"

eurost <- eurostat::get_eurostat(id = dataset_code, filters = filters)
dbnomics <- rdbnomics::rdb(provider_code = "Eurostat", dataset_code = dataset_code, 
                       dimensions = filters)
dbnomics <- dbnomics  |> select(na_item, geo, direct, period, sector, value)
eurost <- eurost |> select(na_item, direct, geo, time, sector, values) |> rename(period = time)

inner_join(eurost, dbnomics) |> mutate(difference = values - value) |> filter(difference>1)

peryourhealth

Okdhslogin

publixpassport

Myhtspacelive

First of all, many thanks for the wonderful service you provide. Really good work!

I wanted to flag that the daily exchange rates published by the ECB have not been updated since 2024-12-04 in DBnomics, whereas the underlying data provided by the ECB itself is up to date. See for instance the series D.USD.EUR.SP00.A under ECB.EXR.

Many thanks in advance for looking into this.
Pablo