import seaborn as sns
sns.boxplot(data=elections, y='%', hue='Result', width=0.2);
Box Plots
Box plots display distributions using information about quartiles.
A quartile represents a 25% portion of the data. We say that:
The first quartile (Q1) repesents the 25th percentile – 25% of the data lies below the first quartile
The second quartile (Q2) represents the 50th percentile, also known as the median – 50% of the data lies below the second quartile
The third quartile (Q3) represents the 75th percentile – 75% of the data lies below the third quartile.
In a box plot, the lower extent of the box lies at Q1, while the upper extent of the box lies at Q3. The horizontal line in the middle of the box corresponds to Q2 (equivalently, the median).
The Inter-Quartile Range (IQR) measures the spread of the middle % of the distribution, calculated as the (\(3^{rd}\) Quartile \(-\) \(1^{st}\) Quartile).
The whiskers of a box-plot are the two points that lie at the [\(1^{st}\) Quartile \(-\)(\(1.5 \times\) IQR)], and the [\(3^{rd}\) Quartile \(+\) (\(1.5 \times\) IQR)]. They are the lower and upper ranges of “normal” data (the points excluding outliers). Subsequently, the outliers are the data points that fall beyond the whiskers, or further than ( \(1.5 \times\) IQR) from the extreme quartiles.
ax = sns.boxplot(data = elections, y = '%', x="Result", width=0.2);