Functionality

OUTPUT

Final MATLAB output will be a cell array with unstacked values over the queried period keeping the following information intact:

• @frequency
• provider_code
• dataset_code
• dataset_name
• series_code
• series_name
• original_period: the period as returned by DBnomics
• period (pd.Timestamp): the first day of original_period
• original_value (str or float): the observation value as returned by DBnomics, where not available values are represented by "NA"
• value (float or NaN): the observation value as returned by DBnomics, where not available values are represented by NaN

Followed by dimensions columns, corresponding to the dimensions of the dataset:

• dimensions labels (eg:freq, unit, geo)
• then dimensions values labels (eg: Frequency, Unit, Country)

FUNCTIONS

Keeping the original functionality of the R, Python plug-ins, the following functions are necessary:

• Fetch time series:
  • by ids
    • one series,
    • multiple series from same dataset,
    • multiple series from different datasets of different providers
  • by mask (CompatibleProviders = {"BIS", "ECB", "Eurostat", "FED", "IMF", "IMF-WEO", "INSEE", "OECD", "WTO"})
    • one series,
    • multiple series from same dataset,
    • all series along one dimension from the same dataset
    • all series along multiple dimensions from the same dataset
  • by dimensions (same dataset)
    • one series of one dimension,
    • multiple series of one dimension,
    • multiple series of multiple dimensions,
• Fetch series by api link (from the website/cart)
• Transform time series with filters
  • https://editor.nomics.world/filters
  • Note: array fields should change when filters are used
    • period_middle_day: the middle day of original_period (can be useful when you compare graphically interpolated series and original ones)
    • filtered (bool): True if the series is filtered
    • series_code: same as before for original series, but the suffix _filtered is added for filtered series
    • series_name: same as before for original series, but the suffix (filtered) is added for filtered series

changed milestone to %0.1

By Dóra Kocsis on 2020-01-29T15:14:55 (imported from GitLab project)

added enhancement label

List of functions

• fetch_series

• fetch_series_by_api_link

• fetch_series_page

• iter_series_infos

  • • yield_series

• flatten_dbnomics_series

• normalize_period

• normalize_value

• without_keys --> equivalent to rmfield

• iter_filtered_series

  • • grouper --> returns iterable
  • • flatten_editor_series

By Dóra Kocsis on 2020-02-14T15:10:49 (imported from GitLab project)

marked the task by ids as completed

By Dóra Kocsis on 2020-02-05T15:45:19 (imported from GitLab project)

marked the task Fetch series by api link (from the website/cart) as completed

By Dóra Kocsis on 2020-02-14T15:10:41 (imported from GitLab project)

marked the task by mask (CompatibleProviders = {"BIS", "ECB", "Eurostat", "FED", "IMF", "IMF-WEO", "INSEE", "OECD", "WTO"}) as completed

By Dóra Kocsis on 2020-02-14T17:20:01 (imported from GitLab project)

marked the task by dimensions (same dataset) as completed

By Dóra Kocsis on 2020-02-14T17:20:03 (imported from GitLab project)

marked the task Fetch time series: as completed

By Dóra Kocsis on 2020-02-14T17:20:04 (imported from GitLab project)

marked the checklist item Transform time series with filters as completed

closed via commit 14413931