Data Selection and Filtering with Pandas
In this lesson you will learn how to access exactly what you need in any DataFrame
🔍 WHAT YOU WILL LEARN
loc and iloc — access rows and columns by label and position
&, |, ~ — boolean filters with multiple conditions
query() — SQL-like syntax for more readable filters
isin() — 16,791 card sales in one row
between() — 23,007 sales between R$1,000 and R$5,000
str.contains() — search for LTDA, ME, EPP using regex
select_dtypes and filter() — select columns dynamically
#pandas #python #datascience #datafiltering #dataanalysis