Fundamentals of Python for Financial Econometrics

Chapter 12: Data Visualization with Python

What should a figure reveal that a table or coefficient cannot show as clearly?

Loading notebook...Construct line, scatter, distribution, and categorical chartsLabel units, sources, and transformationsDesign for accessibility and grayscale printingRecognize misleading scales and overplotting

Notebook lab guide

Related dataset

Ceteris Lab teaching sample

Estimated time

25 to 40 min

Packages

pandas, numpy, matplotlib

Expected output

A printed summary plus a chart in the output panel.

Learning goals

Load and inspect Ceteris Lab teaching sample.
Run the Python cells connected to Data Visualization with Python.
Interpret the output using Construct line, scatter, distribution, and categorical charts and Label units, sources, and transformations.

Common errors

File not found: check that wage_sample.csv is installed or use the course data folder.
Package import error: use the browser notebook first, then download for local Jupyter if your local packages differ.
Column name error: compare your variable names with the dataset variables listed for this notebook.

Dataset path helper

import pandas as pd

df = pd.read_csv("/data/wage_sample.csv")
df.head()

Loading notebook runner...