My first exploratory data analysis with Python

I am taking the Data Management and Visualization course in Coursera (Wesleyan University’s). My task is to write a program that helps me to explore the variables I have selected for my own research question: the association between prevalence of HIV and income per capita across the world according to the Gapminder data.

Step 1. Run my first program.

Step 2. Show the output that displays two of the variables as descriptive measures.

Step 3. Interpret the descriptive measures of the variables above.

The variable ‘Income per person’ is a quantitative variable and takes numeric values. The mean is equal to 8740.96 and the median is 2553.49. According to the count result, it seems that 23 values are missing. In the following plots, it can observe that the data is right-skewed and there are outliers.

The variable ‘HIV rate’ is also a numeric variable. The mean is 1.93 and the median is equal to 0.40. There are 66 missing values. According to the histogram and boxplot are shown below, the values in the HIV rate are right-skewed and there are extreme values.

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