Datastream Sustainable Development Goals Country Scores
Read Jonathan Legrand’s full article on the Developer Portal.
Environmental, Social and Governance data is not always the easiest to get, and yet it is increasingly important for effective investment analysis relating to companies’ performance, climate change, executive remuneration, and diversity & inclusion. The opacity and non-standardization in ESG reporting is a growing issue in this field.
In this article, we exemplify a way to allow any investor to gather, analyze and produce insight into ESG metrics at granular and macro (country-wide) levels. It uses the DataStream Sustainable Development Goals Country Scores such as the one used in the similarly named Refinitiv Excel capability. The file ‘ESG-DS.csv’ will be needed to collect individual country series codes from our ESG database.
In the full article, we build Python functions such as:
Overall_Results_Chart
Overall_Results_Chart.dropna().sort_values(
ascending = True,
by = ["Overall Results"]
).plot.barh(
x = "Countries",
y = "Overall Results",
figsize = (10,40),
title = "Overall ESG Scores (out of 10)\n",
grid = True
)To give graphs such as the below:
Before saving the rendered data.
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Article.DataStream.Python.DatastreamSustainableDevelopmentGoalsCountryScoresGitHub
