the tl;dr of https://medium.com/dunder-data/minimally-sufficient-pandas-a8e67f2a2428
select a column of data, use brackets df['column_name']
select rows of data, use .loc
or datetime index df['2019-01-01':'2019-02-28' ]
- if performance is primary concern, using numpy array instead of Pandas
use read_csv
and it's many arguments for reading files
use .isna
method to filter NaN rows