Python Data Processing with Pandas CSE 5542 Introduc:on to Data - PowerPoint PPT Presentation

Python Data Processing with Pandas CSE 5542 Introduc:on to Data Visualiza:on

Pandas • A very powerful package of Python for manipula:ng tables • Built on top of numpy, so is efficient • Save you a lot of effort from wri:ng lower python code for manipula:ng, extrac:ng, and deriving tables related informa:on • Easy visualiza:on with Matplotlib • Main data structures – Series and DataFrame

• First thing first • Series: an indexed 1D array

• Explicit index • Access data

• Can work as a dic:onary • Access and slice data

DataFrame Object • Generalized two dimensional array with flexible row and column indices

DataFrame Object • Generalized two dimensional array with flexible row and column indices

DataFrame Object • From Pandas Series

DataFrame Object • From Pandas Series

DataFrame Object • Another example

Viewing Data • View the first or last N rows

Viewing Data • Display the index, columns, and data

Viewing Data • Quick sta:s:cs (for columns A B C D in this case)

Viewing Data • Sor:ng: sort by the index (i.e., reorder columns or rows), not by the data in the table column

Viewing Data • Sor:ng: sort by the data values

Selec:ng Data • Selec:ng using a label

Selec:ng Data • Mul:-axis, by label

Selec:ng Data • Mul:-axis, by label Slicing: last included

Selec:ng Data • Select by posi:on

Selec:ng Data • Boolean indexing

Selec:ng Data • Boolean indexing

SeZng Data • SeZng a new column aligned by indexes

SeZng Data

Opera:ons • Descrip:ve sta:s:cs – Across axis 0 (rows), i.e., column mean – Across axis 1 (column), i.e., row mean

Opera:ons • Apply • Histogram

Merge Tables • Join

Merge Tables • Append

Grouping

File I/O • CSV

File I/O • Excel