Counting values

value_counts counts how often each value appears in a column.

• Results are sorted from most to least common.
• normalize=True gives shares instead of counts.
• Missing values are left out unless you pass dropna=False.

import pandas as pd
s = pd.Series(["Pune", "Delhi", "Pune", "Pune"])
print(s.value_counts().to_dict())

{'Pune': 3, 'Delhi': 1}

Remember: Quickest way to see what's in a column.

Common mistake: Using groupby(...).count() just to count values; value_counts is simpler.