In this assignment, you have access to the OECDS 2019 publication on Electricity Generation.
Your job is to sort the data given by the country. To learn more about the data provided visit the
following website: https://data.oecd.org/energy/electricity-generation.htm
Dataset: https://acrobat.adobe.com/id/urn%3Aaaid%3Asc%3AUS%3Acfef4ac4-ee77-4c59-b695-
191eda50bcc0/?x_api_client_id=adobe_com&x_api_client_location=excel_to_pdf&viewer%21meg
aVerb=group-convert
Sorting the data in Python
1. Sort the data by country/location by creating a two-column variable for each.
1. Please make sure that the variables you create differentiate between whether or not the source
was nuclear. Example for AUS- AUS can be used for total and N_AUS can be used for nuclear
2. Each variable you create of a location should contain the time in the first column and the value
in the second column. Note: the year (time) should align with the value (Gigawatt-hours) were
produced
2. Using Numpy find the following as it relates to the country/location variables (explain these
values in a Word Document):
1. Minimum power generation (per country)
2. Maximum power generation (per country)
3. Mean power generation (per country)
4. Standard deviation of power generation (per country)
5. Variance of power generation (per country)
3. Store all the data in a variable called Gpower (Combine all the data into one variable)
4. Using Numpy find the following as it relates to the Gpower variable (explain these values in a
Word Document)::
1. Minimum power generation (overall: What country, year etc.)
2. Maximum power generation (overall: What country, year etc.)
3. Mean power generation (overall: What country, year etc.)
4. Standard deviation of power generation (overall: What country, year etc.)
5. Variance of power generation (overall: What country, year etc.).
In this assignment you have access to the OECDS 2019 publi.pdf
1. In this assignment, you have access to the OECDS 2019 publication on Electricity Generation.
Your job is to sort the data given by the country. To learn more about the data provided visit the
following website: https://data.oecd.org/energy/electricity-generation.htm
Dataset: https://acrobat.adobe.com/id/urn%3Aaaid%3Asc%3AUS%3Acfef4ac4-ee77-4c59-b695-
191eda50bcc0/?x_api_client_id=adobe_com&x_api_client_location=excel_to_pdf&viewer%21meg
aVerb=group-convert
Sorting the data in Python
1. Sort the data by country/location by creating a two-column variable for each.
1. Please make sure that the variables you create differentiate between whether or not the source
was nuclear. Example for AUS- AUS can be used for total and N_AUS can be used for nuclear
2. Each variable you create of a location should contain the time in the first column and the value
in the second column. Note: the year (time) should align with the value (Gigawatt-hours) were
produced
2. Using Numpy find the following as it relates to the country/location variables (explain these
values in a Word Document):
1. Minimum power generation (per country)
2. Maximum power generation (per country)
3. Mean power generation (per country)
4. Standard deviation of power generation (per country)
5. Variance of power generation (per country)
3. Store all the data in a variable called Gpower (Combine all the data into one variable)
4. Using Numpy find the following as it relates to the Gpower variable (explain these values in a
Word Document)::
1. Minimum power generation (overall: What country, year etc.)
2. Maximum power generation (overall: What country, year etc.)
3. Mean power generation (overall: What country, year etc.)
4. Standard deviation of power generation (overall: What country, year etc.)
5. Variance of power generation (overall: What country, year etc.)
