Use pandas to read in the tab separated file Datasets/ZirconData.txt. These data are from Bisnath et al (2006) and were downloaded from the Pangaea database (https://doi.pangaea.de/10.1594/PANGAEA.847015)
These data are Lead-Lead and Uranium-Lead age dates for zircons from Dronning Maud Land, Antartica. The zircon ages show two stages of growth associated with two stages of mountain building in the region.
The columns ['Age dated [ka] (Age, 206Pb/238U Lead-Uranium)'] and ['Age dated [ka] (Age, 207Pb/206Pb Lead-Lead)'] are the different age systems. Get the mean of each of these ages.
Use plt.hist() to plot a histogram of both age dates.
Use sns.kdeplot() to plot a kernel density of both age systems. Experiment with the bw argument to see how this alters your result. According to the seaborn documentation, the bandwidth (bw) parameter of the KDE controls how tightly the estimation is fit to the data, much like the bin size in a histogram. It corresponds to the width of the kernels we plotted above. The default behavior tries to guess a good value using a common reference rule, but it may be helpful to try larger or smaller values:
Use sns.jointplot() to plot a 2d kernel density estimate of the data.