The Periodic Table as Data: Quick Revision

A brief note on The Periodic Table as Data. Read it before a test. Try each question at the end before you open its answer.

The table

• pd.read_csv(io.StringIO(text), sep=" ", names=cols) turns typed text into a DataFrame. nan is a missing value.
• df["ie"] is a column; df[["symbol", "ie"]] is a smaller table; df.set_index("symbol").loc["Na", "ie"] is one value.
• df.sort_values("radius", ascending=False) sorts; store the result to keep it.
• Filter with df[condition]; join conditions with & or |, each in brackets.
• A computed column: df["ie_eV"] = df["ie"] / 96.49, for every row at once.

The plots

• plt.plot(df["z"], df["ie"], "o-"); label each axis with its unit.
• plt.scatter(..., c=df["block"].map(colours)) colours points by block.
• Ionisation enthalpy peaks at the noble gases and dips at the alkali metals after them.
• Atomic radius falls across a period and rises down a group.

The patterns

• df.groupby("block")["ie"].mean(): the mean of each block.
• df["radius"].corr(df["ie"]): $r$ from $-1$ to $1$; here strongly negative.
• df.groupby("period")["ie"].diff(): the change from the element before, inside each period. A negative value is a break: boron and oxygen in period 2.

A worked example

What does this print?

1. The changes. Magnesium $+242$, aluminium $-161$, silicon $+209$; sodium has none.
2. The filter. Only aluminium is below zero.
3. The reason. Aluminium's outer electron is in a 3p orbital, higher in energy than magnesium's full 3s.

It prints ['Al'].

Practice with new numbers

A program to try

The program finds the break in the rise across the p-block of period 4.

Mistakes to avoid

• A capital letter in a column name. df["IE"] stops with KeyError: 'IE'.
• and between conditions. It stops with ValueError: The truth value of a Series is ambiguous; use & and brackets.
• diff() across periods. Group by period first, or a new shell looks like a break.
• Missing values in a plot. Filter with notna() before plotting the radius.
• Reading a correlation as a cause. It says that two columns move together, no more.

Check yourself

1. Which line keeps the d-block elements whose first ionisation enthalpy is above $700$ kJ/mol?

2. In a plot coloured by block, what does the flat green stretch of period 4 tell you?

3. df["radius"].corr(df["ie"]) gives a value near $-0.8$. What does that mean in words?

4. Why is magnesium's value higher than aluminium's, though aluminium comes later in the period?