Mixing position-based and label-based selection

Since pd.DataFrame.iloc is used for position-based selection and pd.DataFrame.loc is for label-based selection, users must take an extra step if attempting to select by label in one dimension and by position in another. As mentioned in previous sections, the majority of pd.DataFrame objects constructed will place heavy significance on the labels used for the columns, with little care for how those columns are ordered. The inverse is true for the rows, so being able to effectively mix and match both styles is of immense value.

How to do it

Let’s start with a pd.DataFrame that uses the default auto-numbered pd.RangeIndex in the rows but has custom string labels for the columns:

df = pd.DataFrame([
    [24, 180, "blue"],
    [42, 166, "brown"],
    [22, 160, "green"],
], columns=["age", "height_cm", "eye_color"])
df

     age   height_cm    eye_color
0  ...