Once a table is loaded, check what kind of data each column holds. The type decides what you can do with it: you can add up numbers, but not text.
df.dtypes lists every column's type. int64 is whole numbers, float64 is decimals, str is text (older pandas versions say object) and datetime64 is dates.df.info() prints the same types plus how many values in each column aren't missing. It prints rather than returns, so use it for reading, not as a result.df.describe() gives the count, mean, standard deviation, minimum, quartiles and maximum of each number column.
For a column of categories, value_counts() counts how often each value appears, largest first, and nunique() counts how many different values there are. Analysts run these on every new file. They catch wrong types, odd categories and typos before those spoil a result.