Python Data Analysis with Numpy, Pandas, and Matplotlib, Lecture notes of Data Structures and Algorithms

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Intermediate/Advanced

Python

Michael Weinstein

(Day 3)

Topics

› Review of basic data structures

› Accessing and working with objects in python

› Numpy

› Pandas

• What are dataframes?
• Sample column counting operation
• Test, refine, test, refine, test, refine to get the data structure we want
• Extracting a column

› Matplotlib

• Making a simple line plot

› Scipy

How to think of a dataframe?

How to count letters in a column?

Data looks almost right, except we need it transposed (we want position to be the columns).

How to transpose

Looks good!

Testing out our next data structure

Testing out the data structure

This is what we want to see

Finalize the function and call

Pyplot marker codes (Don’t worry about memorizing) Keep a reference if you use these often character description '-' solid line style '--' dashed line style '-.' dash-dot line style ':' dotted line style '.' point marker ',' pixel marker 'o' circle marker 'v' triangle_down marker '^' triangle_up marker '<' triangle_left marker '>' triangle_right marker '1' tri_down marker '2' tri_up marker '3' tri_left marker '4' tri_right marker 's' square marker 'p' pentagon marker '*' star marker 'h' hexagon1 marker 'H' hexagon2 marker '+' plus marker 'x' x marker 'D' diamond marker 'd' thin_diamond marker '|' vline marker '_' hline marker

character color

‘b’ blue

‘g’ green

‘r’ red

‘c’ cyan

‘m’ magenta

‘y’ yellow

‘k’ black

‘w’ white

Iterative plotting… it’s really this simple