Try it on paper first. A hint, the key idea and the worked solution are here when you need them.
For lithium to fluorine, the radii are , , , , , and pm, and the first ionisation enthalpies are , , , , , and kJ/mol. radius.corr(ie) gives . Explain the sign, and say why the value is not exactly .
df.groupby("block")["ie"].mean() gives the mean of each block. df["a"].corr(df["b"]) gives the correlation , from to . df.groupby("period")["ie"].diff() gives the change from the element before, inside each period; a negative value is a break in the rise.
Have you tried it?
Work it out on paper first. It is fine to get stuck or make a mistake: that is how we learn. When you are ready, go through the solution one step at a time, and check each step against your own.
Step 1. The sign. Across the period the radius falls while the ionisation enthalpy rises overall. One goes down as the other goes up: a negative .
Step 2. Not . would need every point on one straight line. Boron and oxygen fall below their neighbours, and the steps are uneven, so the points scatter about the line.
Answer: negative because small atoms hold electrons tightly; not because the breaks at boron and oxygen pull points off the line.
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