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MacroEconomic Monthly 50 Countries,17000 Series

MacroEconomic Monthly with > 50 countries and17000 series from OECD, 2010-2023 M

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series

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About this Dataset

MacroEconomic Monthly 50 Countries,17000 Series

Data has several macro-economic data collected from OECD website. Data had to be downloaded in batches as the website doesn’t support bulk download.

Contains 17,000 time series of key factors related to labour-unemployment statistics, exports, imports, CPI/inflation, production by industry types etc..

Use this data to practise: Feature reduction for beginners or for modelling prices or economic factors interdependencies.
Impact on your sector of interest (Eg. textile, manufacturing, retail, energy, trade prices etc..) ..

Tables

Med Merged

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.med_merged
  • 35.44 MB
  • 2892441 rows
  • 20 columns
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CREATE TABLE med_merged (
  "unnamed_0" BIGINT,
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

Med All Features

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.med_all_features
  • 29.07 MB
  • 159 rows
  • 17259 columns
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CREATE TABLE med_all_features (
  "unnamed_0" TIMESTAMP,
  "deu_odmnto01_ixob" DOUBLE,
  "deu_odmnto01_ixobsa" DOUBLE,
  "swe_odmnto01_ixobsa" DOUBLE,
  "deu_slmncn01_ixob" DOUBLE,
  "deu_slmncn01_ixobsa" DOUBLE,
  "aut_prmnto01_ixob" DOUBLE,
  "aut_prmnto01_ixobsa" DOUBLE,
  "aut_prmnto01_gpsa" DOUBLE,
  "bel_prmnto01_ixob" DOUBLE,
  "bel_prmnto01_ixobsa" DOUBLE,
  "bel_prmnto01_gpsa" DOUBLE,
  "can_prmnto01_ixob" DOUBLE,
  "can_prmnto01_ixobsa" DOUBLE,
  "can_prmnto01_ml" DOUBLE,
  "can_prmnto01_mlsa" DOUBLE,
  "can_prmnto01_gpsa" DOUBLE,
  "cze_prmnto01_ixob" DOUBLE,
  "cze_prmnto01_ixobsa" DOUBLE,
  "cze_prmnto01_gpsa" DOUBLE,
  "dnk_prmnto01_ixob" DOUBLE,
  "dnk_prmnto01_ixobsa" DOUBLE,
  "dnk_prmnto01_gpsa" DOUBLE,
  "fin_prmnto01_ixob" DOUBLE,
  "fin_prmnto01_ixobsa" DOUBLE,
  "fin_prmnto01_gpsa" DOUBLE,
  "fra_prmnto01_ixob" DOUBLE,
  "fra_prmnto01_ixobsa" DOUBLE,
  "fra_prmnto01_gpsa" DOUBLE,
  "deu_prmnto01_ixob" DOUBLE,
  "deu_prmnto01_ixobsa" DOUBLE,
  "deu_prmnto01_gpsa" DOUBLE,
  "grc_prmnto01_ixob" DOUBLE,
  "grc_prmnto01_ixobsa" DOUBLE,
  "grc_prmnto01_gpsa" DOUBLE,
  "hun_prmnto01_ixob" DOUBLE,
  "hun_prmnto01_ixobsa" DOUBLE,
  "hun_prmnto01_gpsa" DOUBLE,
  "isl_prmnto01_ixob" DOUBLE,
  "isl_prmnto01_ixobsa" DOUBLE,
  "isl_prmnto01_ml" DOUBLE,
  "isl_prmnto01_mlsa" DOUBLE,
  "isl_prmnto01_gpsa" DOUBLE,
  "isl_prmnto01_gysa" DOUBLE,
  "irl_prmnto01_ixob" DOUBLE,
  "irl_prmnto01_ixobsa" DOUBLE,
  "irl_prmnto01_gpsa" DOUBLE,
  "ita_prmnto01_ixob" DOUBLE,
  "ita_prmnto01_ixobsa" DOUBLE,
  "ita_prmnto01_gpsa" DOUBLE,
  "jpn_prmnto01_ixob" DOUBLE,
  "jpn_prmnto01_ixobsa" DOUBLE,
  "jpn_prmnto01_gpsa" DOUBLE,
  "kor_prmnto01_ixob" DOUBLE,
  "kor_prmnto01_ixobsa" DOUBLE,
  "kor_prmnto01_gpsa" DOUBLE,
  "lux_prmnto01_ixob" DOUBLE,
  "lux_prmnto01_ixobsa" DOUBLE,
  "lux_prmnto01_gpsa" DOUBLE,
  "mex_prmnto01_ixob" DOUBLE,
  "mex_prmnto01_ixobsa" DOUBLE,
  "mex_prmnto01_gpsa" DOUBLE,
  "nld_prmnto01_ixob" DOUBLE,
  "nld_prmnto01_ixobsa" DOUBLE,
  "nld_prmnto01_gpsa" DOUBLE,
  "nor_prmnto01_ixob" DOUBLE,
  "nor_prmnto01_ixobsa" DOUBLE,
  "nor_prmnto01_gpsa" DOUBLE,
  "pol_prmnto01_ixob" DOUBLE,
  "pol_prmnto01_ixobsa" DOUBLE,
  "pol_prmnto01_gpsa" DOUBLE,
  "prt_prmnto01_ixob" DOUBLE,
  "prt_prmnto01_ixobsa" DOUBLE,
  "prt_prmnto01_gpsa" DOUBLE,
  "svk_prmnto01_ixob" DOUBLE,
  "svk_prmnto01_ixobsa" DOUBLE,
  "svk_prmnto01_gpsa" DOUBLE,
  "esp_prmnto01_ixob" DOUBLE,
  "esp_prmnto01_ixobsa" DOUBLE,
  "esp_prmnto01_gpsa" DOUBLE,
  "swe_prmnto01_ixob" DOUBLE,
  "swe_prmnto01_ixobsa" DOUBLE,
  "swe_prmnto01_gpsa" DOUBLE,
  "tur_prmnto01_ixob" DOUBLE,
  "tur_prmnto01_ixobsa" DOUBLE,
  "tur_prmnto01_gpsa" DOUBLE,
  "gbr_prmnto01_ixob" DOUBLE,
  "gbr_prmnto01_ixobsa" DOUBLE,
  "gbr_prmnto01_gpsa" DOUBLE,
  "usa_prmnto01_ixob" DOUBLE,
  "usa_prmnto01_ixobsa" DOUBLE,
  "usa_prmnto01_gpsa" DOUBLE,
  "bra_prmnto01_ixob" DOUBLE,
  "bra_prmnto01_ixobsa" DOUBLE,
  "bra_prmnto01_gpsa" DOUBLE,
  "chl_prmnto01_ixob" DOUBLE,
  "chl_prmnto01_ixobsa" DOUBLE,
  "chl_prmnto01_gpsa" DOUBLE,
  "chl_prmnto01_gysa" DOUBLE,
  "est_prmnto01_ixob" DOUBLE
);

P8

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p8
  • 66.95 KB
  • 8736 rows
  • 19 columns
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CREATE TABLE p8 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P5–2

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p5_2
  • 2.21 MB
  • 287284 rows
  • 19 columns
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CREATE TABLE p5_2 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P7

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p7
  • 2.26 MB
  • 255203 rows
  • 19 columns
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CREATE TABLE p7 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P6

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p6
  • 23.58 KB
  • 1094 rows
  • 19 columns
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CREATE TABLE p6 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P5–3

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p5_3
  • 47.91 KB
  • 4386 rows
  • 19 columns
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CREATE TABLE p5_3 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P5–1–1

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p5_1_1
  • 1.49 MB
  • 171145 rows
  • 19 columns
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CREATE TABLE p5_1_1 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P4

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p4
  • 1.66 MB
  • 284147 rows
  • 19 columns
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CREATE TABLE p4 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P2

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p2
  • 3.92 MB
  • 638661 rows
  • 19 columns
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CREATE TABLE p2 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P3

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p3
  • 2 MB
  • 315308 rows
  • 19 columns
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CREATE TABLE p3 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P5–1–2

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p5_1_2
  • 762.13 KB
  • 370681 rows
  • 19 columns
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CREATE TABLE p5_1_2 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P5–1–3

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p5_1_3
  • 1.8 MB
  • 224071 rows
  • 19 columns
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CREATE TABLE p5_1_3 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

P1

@kaggle.pawankumark_macroeconomic_monthly_50_countries17000_series.p1
  • 2.39 MB
  • 331725 rows
  • 19 columns
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CREATE TABLE p1 (
  "location" VARCHAR,
  "country" VARCHAR,
  "subject" VARCHAR,
  "subject_fda041" VARCHAR,
  "measure" VARCHAR,
  "measure_277efb" VARCHAR,
  "frequency" VARCHAR,
  "frequency_659f01" VARCHAR,
  "time" TIMESTAMP,
  "time_660678" VARCHAR,
  "unit_code" VARCHAR,
  "unit" VARCHAR,
  "powercode_code" BIGINT,
  "powercode" VARCHAR,
  "reference_period_code" VARCHAR,
  "reference_period" VARCHAR,
  "value" DOUBLE,
  "flag_codes" VARCHAR,
  "flags" VARCHAR
);

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