Name: Financial-environmental Multi Time Series
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

Financial-environmental Multi Time Series

The dataset contains 63 of the most important European companies with their Financial and Environmental data.
We have a total of 4 financial tables and 2 environmental tables already cleaned up

Financial data:

ROE: return on equity
ROA: return on assets
Dividend per share
Total assets

Environmental data:

CO2 Equivalents Emission direct : SCOPE1 (e.g. emissions due to production)
CO2 Equivalents Emission Indirect : SCOPE2 (e.g. energy purchased by the company)

The Time period is 2010-2020 and the columns are the years

Tables

Div

@kaggle.giuliofabbri_environment_data.div

29.36 kB
63 rows
29 columns

CREATE TABLE div (
  "company" VARCHAR,
  "quartile" VARCHAR,
  "country" VARCHAR,
  "economic_sector" VARCHAR,
  "sub_industry" VARCHAR,
  "pollution" VARCHAR,
  "metric" VARCHAR,
  "n_2010" DOUBLE  -- 2010,
  "n_2011" DOUBLE  -- 2011,
  "n_2012" DOUBLE  -- 2012,
  "n_2013" DOUBLE  -- 2013,
  "n_2014" DOUBLE  -- 2014,
  "n_2015" DOUBLE  -- 2015,
  "n_2016" DOUBLE  -- 2016,
  "n_2017" DOUBLE  -- 2017,
  "n_2018" DOUBLE  -- 2018,
  "n_2019" DOUBLE  -- 2019,
  "n_2020" DOUBLE  -- 2020,
  "wa_10" DOUBLE,
  "wa_11" DOUBLE,
  "wa_12" DOUBLE,
  "wa_13" DOUBLE,
  "wa_14" DOUBLE,
  "wa_15" DOUBLE,
  "wa_16" DOUBLE,
  "wa_17" DOUBLE,
  "wa_18" DOUBLE,
  "wa_19" DOUBLE,
  "wa_20" DOUBLE
);

Roa

@kaggle.giuliofabbri_environment_data.roa

17.95 kB
63 rows
17 columns

CREATE TABLE roa (
  "company" VARCHAR,
  "country" VARCHAR,
  "economic_sector" VARCHAR,
  "sub_industry" VARCHAR,
  "pollution" VARCHAR,
  "metric" VARCHAR,
  "n_2010" DOUBLE  -- 2010,
  "n_2011" DOUBLE  -- 2011,
  "n_2012" DOUBLE  -- 2012,
  "n_2013" DOUBLE  -- 2013,
  "n_2014" DOUBLE  -- 2014,
  "n_2015" DOUBLE  -- 2015,
  "n_2016" DOUBLE  -- 2016,
  "n_2017" DOUBLE  -- 2017,
  "n_2018" DOUBLE  -- 2018,
  "n_2019" DOUBLE  -- 2019,
  "n_2020" DOUBLE  -- 2020
);

Roe

@kaggle.giuliofabbri_environment_data.roe

18.25 kB
63 rows
17 columns

CREATE TABLE roe (
  "company" VARCHAR,
  "country" VARCHAR,
  "economic_sector" VARCHAR,
  "sub_industry" VARCHAR,
  "pollution" VARCHAR,
  "metric" VARCHAR,
  "n_2010" DOUBLE  -- 2010,
  "n_2011" DOUBLE  -- 2011,
  "n_2012" DOUBLE  -- 2012,
  "n_2013" DOUBLE  -- 2013,
  "n_2014" DOUBLE  -- 2014,
  "n_2015" DOUBLE  -- 2015,
  "n_2016" DOUBLE  -- 2016,
  "n_2017" DOUBLE  -- 2017,
  "n_2018" DOUBLE  -- 2018,
  "n_2019" DOUBLE  -- 2019,
  "n_2020" DOUBLE  -- 2020
);

Scope1

@kaggle.giuliofabbri_environment_data.scope1

30.87 kB
63 rows
27 columns

CREATE TABLE scope1 (
  "company" VARCHAR,
  "country" VARCHAR,
  "economic_sector" VARCHAR,
  "sub_industry" VARCHAR,
  "metric" VARCHAR,
  "n_2010" DOUBLE  -- 2010,
  "n_2011" DOUBLE  -- 2011,
  "n_2012" DOUBLE  -- 2012,
  "n_2013" DOUBLE  -- 2013,
  "n_2014" DOUBLE  -- 2014,
  "n_2015" DOUBLE  -- 2015,
  "n_2016" DOUBLE  -- 2016,
  "n_2017" DOUBLE  -- 2017,
  "n_2018" DOUBLE  -- 2018,
  "n_2019" DOUBLE  -- 2019,
  "n_2020" DOUBLE  -- 2020,
  "wa_10" DOUBLE,
  "wa_11" DOUBLE,
  "wa_12" DOUBLE,
  "wa_13" DOUBLE,
  "wa_14" DOUBLE,
  "wa_15" DOUBLE,
  "wa_16" DOUBLE,
  "wa_17" DOUBLE,
  "wa_18" DOUBLE,
  "wa_19" DOUBLE,
  "wa_20" DOUBLE
);

Scope2

@kaggle.giuliofabbri_environment_data.scope2

27.88 kB
63 rows
24 columns

CREATE TABLE scope2 (
  "company" VARCHAR,
  "metric" VARCHAR,
  "n_2010" DOUBLE  -- 2010,
  "n_2011" DOUBLE  -- 2011,
  "n_2012" DOUBLE  -- 2012,
  "n_2013" DOUBLE  -- 2013,
  "n_2014" DOUBLE  -- 2014,
  "n_2015" DOUBLE  -- 2015,
  "n_2016" DOUBLE  -- 2016,
  "n_2017" DOUBLE  -- 2017,
  "n_2018" DOUBLE  -- 2018,
  "n_2019" DOUBLE  -- 2019,
  "n_2020" DOUBLE  -- 2020,
  "wa_10" DOUBLE,
  "wa_11" DOUBLE,
  "wa_12" DOUBLE,
  "wa_13" DOUBLE,
  "wa_14" DOUBLE,
  "wa_15" DOUBLE,
  "wa_16" DOUBLE,
  "wa_17" DOUBLE,
  "wa_18" DOUBLE,
  "wa_19" DOUBLE,
  "wa_20" DOUBLE
);

Tot Ass

@kaggle.giuliofabbri_environment_data.tot_ass

64.29 kB
1,449 rows
40 columns

CREATE TABLE tot_ass (
  "company" VARCHAR,
  "country" VARCHAR,
  "economic_sector" VARCHAR,
  "sub_industry" DOUBLE,
  "pollution" DOUBLE,
  "metric" DOUBLE,
  "n_2010" DOUBLE  -- 2010,
  "n_2011" DOUBLE  -- 2011,
  "n_2012" DOUBLE  -- 2012,
  "n_2013" VARCHAR  -- 2013,
  "n_2014" VARCHAR  -- 2014,
  "n_2015" DOUBLE  -- 2015,
  "n_2016" DOUBLE  -- 2016,
  "n_2017" DOUBLE  -- 2017,
  "n_2018" VARCHAR  -- 2018,
  "n_2019" DOUBLE  -- 2019,
  "n_2020" DOUBLE  -- 2020,
  "weight_10" DOUBLE,
  "weight_11" DOUBLE,
  "weight_12" DOUBLE,
  "weight_13" DOUBLE,
  "weight_14" VARCHAR,
  "weight_15" VARCHAR,
  "weight_16" DOUBLE,
  "weight_17" DOUBLE,
  "weight_18" DOUBLE,
  "weight_19" DOUBLE,
  "weight_20" DOUBLE,
  "ec_dim_10" DOUBLE,
  "ec_dim_11" DOUBLE,
  "ec_dim_12" DOUBLE,
  "ec_dim_13" DOUBLE,
  "ec_dim_14" DOUBLE,
  "ec_dim_15" DOUBLE,
  "ec_dim_16" DOUBLE,
  "ec_dim_17" VARCHAR,
  "ec_dim_18" DOUBLE,
  "ec_dim_19" DOUBLE,
  "ec_dim_20" DOUBLE,
  "quartile" VARCHAR
);