Filled area chart using plotly in Python

Plotly is a Python library that is used to design graphs, especially interactive graphs. It can plot various graphs and charts like histogram, barplot, boxplot, spreadplot, and many more. It is mainly used in data analysis as well as financial analysis. plotly is an interactive visualization library. 

Filled Area Chart

Filled area plot is the easy-to-use, high-level articulation to plotly which completes a variety of types of data and produces easy-to-style figures. Each filled area harmonizes with one value of the column given by the line_group parameter. Filled area charts are most commonly used to show trends, rather than convey specific values. Two popular variations of Area Graphs are: grouped and Stacked Area Graphs.

Syntax: plotly.express.area(data_frame=None, x=None, y=None, line_group=None, color=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, orientation=None, groupnorm=None, log_x=False, log_y=False, range_x=None, range_y=None, line_shape=None, title=None, template=None, width=None, height=None)

Parameters:

data_frame:  This argument needs to be passed for column names (and not keyword names) to be used. Array-like and dict are tranformed internally to a pandas DataFrame.



x, y: Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to position marks along the x and y axis in cartesian coordinates.

color: Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign color to marks.

Example 1:

Python3

filter_none

edit
close

play_arrow

link
brightness_4
code

import plotly.express as px
  
df = px.data.iris()
  
fig = px.area(df, x="sepal_width", y="sepal_length",
            color="species",
            hover_data=['petal_width'],)
  
fig.show()

chevron_right


Output:

Example 2:

Python3



filter_none

edit
close

play_arrow

link
brightness_4
code

import plotly.express as px
import numpy as np
  
# creating random data through randomint 
# function of numpy.random 
np.random.seed(42
    
random_x= np.random.randint(1,101,100
random_y= np.random.randint(1,101,100)
  
fig = px.area(x = random_x, y = random_y)
fig.show()

chevron_right


Output:

Example 3:

Python3

filter_none

edit
close

play_arrow

link
brightness_4
code

import plotly.express as px
  
  
df = px.data.tips()
    
fig = px.area(df, x ='total_bill', y = 'day')
fig.show()

chevron_right


Output:

Example 4:

Python3

filter_none

edit
close

play_arrow

link
brightness_4
code

import plotly.express as px
  
  
df = px.data.tips()
    
  
fig = px.area(df, x ='time', y = 'day',
              color="total_bill")
fig.show()

chevron_right


Output:


Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.




My Personal Notes arrow_drop_up


If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.


Article Tags :

Be the First to upvote.


Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.