Customizing Your Plot

import pandas as pd, matplotlib.pyplot as plt # import statement
df = pd.read_csv('https://raw.githubusercontent.com/kwaldenphd/elements-of-computing/main/book/data/ch10/air_quality_no2.csv', index_col=0, parse_dates=True) # load data

We can customize the plot using parameters that work directly within the Pandas plotting function.

A few examples that set axis labels, plot title, etc.

# add axis labels and plot title
df['station_paris'].plot(xlabel = 'Paris Station', ylabel = 'No2 Level', title = 'Air Quality Level Readings')

# previous example, with grid set to True and color set to green
df['station_paris'].plot(xlabel = 'Paris Station', ylabel = 'No2 Level', title = 'Air Quality Level Readings', grid=True, color='green')

# sample example with adjusted font size
df['station_paris'].plot(xlabel = 'Paris Station', ylabel = 'No2 Level', title = 'Air Quality Level Readings', grid=True, color='green', fontsize=12)

Additional Resources

For more parameters that can be passed to .plot(): pandas.DataFrame.plot

Parameter	Explanation
ax	matplotlib axes object; axes for the current figure
subplots	Default is False; set to True to enable multiple plots in the same figure
layout	Follows (rows, columns) syntax to set subplot layout
figsize	Follows (width, height) syntax; Sets figure object width and height in inches
use_Index	Default is True; uses dataframe index as ticks for X axis
title	Title to use for the plot; can take a list with titles for corresponding subplots
grid	Default is False; set to True to show axis grid lines
legend	Places legend on axis subplot
xticks	Values to use for X axis ticks
yticks	Values to use for Y axis ticks
xlim	Follows (lower limit, upper limit) syntax; Sets X axis limits
ylim	Follows (lower limit, upper limit) syntax; Sets Y axis limits
xlabel	Label for X axis; default uses index column name
ylabel	Label for Y axis; default uses Y column name
fontsize	Sets font size for tickmarks
colormap	Sets matplotlib colormap to select colors from
table	Default is False; set to True to draw a table from data in the DataFrame
stacked	Default is False in line and bar plots, True in area plot; if True, creates stacked plot