Python Pandas DataFrame to draw area graphs with different options

Pandas.DataFrame.plot to generate area using data
DataFrame area chart

import pandas as pd 
my_dict={
'Sale':[80,90,75,80,85,80,75],
'cost':[50,40,55,45,65,60,55],
'prof':[8,12,13,10,9,12,13]    
}
df =pd.DataFrame(data=my_dict)
df.plot.area(title='Area Plot')

area chart with options

There are several options we can add to above area diagram.

title :

title='Area Plot' String used as Title of the graph.

figsize :

Size of the graph , it is a tuple saying width and height in inches, figsize=(6,3). Here width is 6 inches and height is 3 inches.

df.plot.area(figsize=(6,3))

color

We can use the option colors to give different colors to line . We can use one tuple to define the colours.

my_color=[(.9,.4,.3),(.1,.8,.1),(.1,.5,.9)]
df.plot.area(title='Area Plot',color=my_color)

style

This is a list or dict. We can specify how the style of the line.
Style

#my_style=[':']
my_style=['.-']
df.plot.area(title='style',style=my_style)

grid

We will show grid ( grid=True ) or not ( grid=False) grid=True option

df.plot.area(title='grid=True',grid=True)

logx

We can specify log scaling or symlog scaling for x ( logx=True )

df.plot.area(logx=True)

secondary_y

Whether to plot on secondary Y Axis ( secondary_y=True ) or not ( secondary_y=False )

df.plot.area(secondary_y=True)

mark_right

Check the image above when secondary_y=True. There is a automatic marking in column lebels saying (right). We can manage this to show ( mark_right=True) or not ( mark_right=False)

df.plot.area(title='mark_right=False',secondary_y=True,mark_right=True,alpha=.4)

rot

Rotation of ticks ( check the label at x axis )
rot=45

df.plot.area(title='rot=180',rot=180)

Pandas plot plot.barh()

Numpy arrays Python & MySQL Python- Tutorials

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

About the author Watch on YouTube

Connect: