Data Management and Visualization: WEEK 3

DATA MANAGEMENT

Source: GapMinder

Variables observed: incomeperperson, oilperperson, relectricperperson

*incomeperperson – Gross Domestic Product (GDP) per capita

*oilperperson – Oil Consumption per capita

* relectricperperson -  Consumption of electricity per capita

Introduction:

Numerous researches conducted by leading economists show an interdependence between GDP, oil consumption and electricity consumption.

In this assignment, I decided to manage the data and observe the results in the following way:

1. Collapse incomeperperson into 3 ranges, i.e. Low income, Middle Income and High Income Countries (according to the WORLD BANK thresholds), and check what percent of countries falls into each of these categories.
2. Observe Oil and Electricity consumption across the world by collapsing oilperperson, relectricperperson values into LOW, AVERAGE and HIGH consumption.
3.  Run frequency distribution for 3 new variables.
4. Observe what are the differences in Oil and Electricity consumption according to the GDP range of countries.
5. Observe how much Oil and Electricity consumption data is missing according to the GDP range of countries.

CODE:

Results:

Categories for each variable:

Category	GDP	OIL *oil consumption	ELECTRO *electricity consumption
1	High Income Countries	High	High
2	Middle Income Countries	Average	Average
3	Low income Countries	Low	Low

Summary:

I collapsed the responses for incomeperperson, oilperperson, relectricperperson to create three new variables: GDP, OIL, and ELECTRO. The table above shows what each of categories stands for.

I deleted all rows with missing incomeperperson and ended up with 190 results.

I kept missing data for oilperperson, relectricperperson and incorporated it into the results table, as "NO DATA", in order to see what percent of information is provided and, therefore, check how meaningful my research is.

•  All countries with GDP data

The results in GDP table show that 21.58% of countries from the data (Category “1”) are High Income Countries, 50.00% countries (Category “2”) are Middle Income Countries and 28.42% countries (Category “3”) are Low Income Countries.

For Oil, the highest oil consumption is found in 7.37% countries (Category “1”), average consumption in 16.32% countries (Category “2”), and low consumption in 8.42% countries (Category “3”). 67.89% of Oil data is missing which means that all results and assumptions are based on very limited data.

For Electro, the highest electricity consumption is found in 16.32% countries (Category “1”), average consumption in 34.21% countries (Category “2”), and low consumption in 17.89% countries (Category “3”). 31.58% of electricity consumption data is missing which means that there´s much more data than in case of oil consumption.

•  Comparison of oil and electricity consumption according to different ranges of GDP:

Variable	Low Income Countries	Middle Income Countries	High Income Countries
No. of countries observed	54 countries	95 countries	41 countries
Oil Consumption	There are only 4 countries (7.41 %) with available data for this variable. And all of them fall into category “3”, meaning low oil consumption .	In this range, data is provided for 34.74 % of countries: 1.05% with high 21.05% with average 12.63% with low oil consumption.	From the available data (58.54%), most countries (31.71%) hadhigh oil consumption. And 26.83%had average oil consumption. There were no cases of low consumption.
Electricity Consumption	For Electricity, there was much more data than for oil: 31 out of 54 countries (57.41%). 12.96% of all results are countries with average consumption and 44.44% percent with low consumption. The rest is missing.	Again, For Electricity, there was much more data than for oil (70.53%): 4.21 %with high 55.79%with average 10.53% with low electricity consumption.	Available data for 78.05% of countries including: Big majority (65.85%) of highconsumption results and 12.20% of averageconsumption results. Similarly to Oil results, there were no cases of low electricity consumption.
Missing Data	92.59% for Oil and 42.59% for Electricity Consumption	65.26% for Oil and 29.47% for Electricity Consumption	41.46% for Oil and 21.95% for Electricity Consumption

If we look at the above table, we can see that in GapMinder data sheet there´s much more data concerning developed countries than developing countries as it comes to Oil and Electricity Consumption. It shows that it would be much better to collect more data before making meaningful assumption, especially regarding oil consumption and low income countries. My whole analysis is based on 32.11% of data for oil and 68.42% for electricity. The amount of data is especially scarce in low-income countries with 7.41% for oil and 57.41% for electricity.

However, even with such limited data, it is still possible to see some patterns in Oil and Electricity Consumption across different GDP ranges of countries.

The data provided proves that there´s a strong correlation between Oil and Electricity Consumption and the GDP of a country. The higher average oil and electricity consumption, the higher GDP range:

For Oil, in low income countries, there was only low consumption. In middle income countries, there were all ranges of consumption, however, the high consumption was found only in one out of 33 countries with available data. In high income countries, there were more cases of high consumption than average consumption and no evidence of low consumption.

For electricity, in low income countries, most results were low consumption. In middle countries, the majority was average consumption with few cases of low and high consumption. And in high income countries, most of them had high consumption with few cases of average consumption and no evidence of low consumption.