{"id":9928,"date":"2020-10-26T17:43:43","date_gmt":"2020-10-26T17:43:43","guid":{"rendered":"https:\/\/www.askpython.com\/?p=9928"},"modified":"2020-10-26T17:43:45","modified_gmt":"2020-10-26T17:43:45","slug":"plot-a-treemap-in-python","status":"publish","type":"post","link":"https:\/\/www.askpython.com\/python\/examples\/plot-a-treemap-in-python","title":{"rendered":"How to Plot a Treemap in Python?"},"content":{"rendered":"\n

A treemap in Python is a visualization of data that splits a rectangle into sub-parts. The size of each subpart is in proportion to the data it represents. It is somewhat like a pie-chart. Although, treemaps can represent much-more complex data as compared to a pie-chart. <\/p>\n\n\n\n

It can help you visualize how single values compose a whole. Treemap<\/strong> charts also let you visualize hierarchical data using nested rectangles. <\/p>\n\n\n\n

In this tutorial, we will learn how to plot treemaps in Python using the Squarify library in python. <\/strong><\/p>\n\n\n\n

Let’s start by installing Squarify.<\/p>\n\n\n

\npip install squarify\n<\/pre><\/div>\n\n\n
\"Squarify\"
Squarify<\/figcaption><\/figure><\/div>\n\n\n\n
Using Squarify to Plot a Treemap in Python<\/h2>\n\n\n\n
Once we have installed Squarify, we can start by importing it into our notebook. Let’s also import matplotlib<\/a>. <\/p>\n\n\n
\nimport matplotlib.pyplot as plt\nimport squarify \n<\/pre><\/div>\n\n\n
1. Plotting a basic treemap <\/h3>\n\n\n\n
To plot a very basic treemap, we just need the values for each rectangle. After plotting the treemap, the rectangles would be in proportion to these values. <\/p>\n\n\n
\nimport matplotlib.pyplot as plt\nimport squarify \nsizes = [40, 30, 5, 25]\nsquarify.plot(sizes)\nplt.show()\n<\/pre><\/div>\n\n\n
\"Treemap\"
Treemap<\/figcaption><\/figure><\/div>\n\n\n\n
2. Add labels to your treemap<\/h3>\n\n\n\n
You can add labels to the treemap in Python, using the following lines of code :<\/p>\n\n\n
\nimport matplotlib.pyplot as plt\nimport squarify \nsizes=[40, 30, 5, 25]\nlabel=["A", "B", "C", "D"]\nsquarify.plot(sizes=sizes, label=label, alpha=0.6 )\nplt.show()\n<\/pre><\/div>\n\n\n
\"Lables\"
Labels<\/figcaption><\/figure><\/div>\n\n\n\n
If you run the same piece of code again, you will get the following output :<\/p>\n\n\n\n
\"Labels\"<\/figure><\/div>\n\n\n\n
You can see that the color scheme of our treemap is different each time we run it. The colors for rectangles are picked randomly<\/em>. Treemap also gives you the option to mention the colors along with sizes and labels. We will learn how to change the colors of a treemap next. <\/p>\n\n\n\n
3. Change the colors in your treemap <\/h3>\n\n\n\n
To change the colors in your treemap in Python, make a list with the colors you want the treemap to have. Then pass that list to squarify.plot method.<\/p>\n\n\n
\nimport matplotlib.pyplot as plt\nimport squarify \nsizes=[40, 30, 5, 25]\nlabel=["A", "B", "C", "D"]\ncolor=['red','blue','green','grey']\nsquarify.plot(sizes=sizes, label=label, color=color, alpha=0.6 )\nplt.show()\n<\/pre><\/div>\n\n\n
\"Changing
Changing Color<\/figcaption><\/figure><\/div>\n\n\n\n
4. Turn-off the plot axis <\/h3>\n\n\n\n
To plot the treemap without the plot-axis, use:<\/p>\n\n\n
\nplt.axis('off')\n<\/pre><\/div>\n\n\n
This line of code will turn off the plot axis. The complete code is as follows:<\/p>\n\n\n
\nimport matplotlib.pyplot as plt\nimport squarify \nsizes=[40, 30, 5, 25]\nlabel=["A", "B", "C", "D"]\ncolor=['red','blue','green','grey']\nsquarify.plot(sizes=sizes, label=label, color=color, alpha=0.6 )\nplt.axis('off')\nplt.show()\n<\/pre><\/div>\n\n\n
\"Plot
Plot Axis Off<\/figcaption><\/figure><\/div>\n\n\n\n
Plot treemap for a Dataset <\/h2>\n\n\n\n
In this part of the tutorial, we will learn how to plot a treemap for a dataset. We are going to use the titanic dataset. Let’s start by importing the dataset. To simplify the process of importing the dataset we are going to use the seaborn<\/strong> library. <\/p>\n\n\n\n
1. Importing the dataset <\/h3>\n\n\n\n
To import the titanic dataset from the seaborn library<\/a> into your Python notebook, use:<\/p>\n\n\n
\nimport seaborn as sns\ntitanic = sns.load_dataset('titanic')\ntitanic.head()\n<\/pre><\/div>\n\n\n
\"Titanic
Titanic Dataset<\/figcaption><\/figure><\/div>\n\n\n\n
The dataset contains information about the passengers of Titanic. <\/p>\n\n\n\n
We want to plot a treemap for the people who survived according to the class they were travelling in. <\/p>\n\n\n\n
The data in its original format is not ready for plotting a treemap. We will carry out some manipulations and try to extract data that we can use to plot a treemap. <\/p>\n\n\n\n
To get the survivors for each class we are going to use group by method<\/strong> on our data. <\/p>\n\n\n\n
2. Preparing the Data for Plotting<\/h3>\n\n\n\n
You can use the groupby function on the dataset as shown below :<\/p>\n\n\n
\nn = titanic.groupby('class')[['survived']].sum()\n<\/pre><\/div>\n\n\n
\"Groupby\"
Groupby<\/figcaption><\/figure><\/div>\n\n\n\n
This gives us the sum of total survivors grouped according to the class.<\/p>\n\n\n\n
Now we need to extract the data and labels as lists<\/a> from this.<\/p>\n\n\n
\na = titanic.groupby('class')[['survived']].sum().index.get_level_values(0).tolist()\nprint(a)\n<\/pre><\/div>\n\n\n
Output :<\/p>\n\n\n
\n['First', 'Second', 'Third']\n<\/pre><\/div>\n\n\n
This gives us the labels in the form of a list. To get the values corresponding to these labels, use :<\/p>\n\n\n
\nd = titanic.groupby('class')[['survived']].sum().reset_index().survived.values.tolist()\nprint(d)\n<\/pre><\/div>\n\n\n
Output :<\/p>\n\n\n
\n[136, 87, 119]\n<\/pre><\/div>\n\n\n
Now we have the labels and data as lists. We can use these to plot a treemap.<\/p>\n\n\n\n
3. Plot the treemap <\/h3>\n\n\n\n
To plot the treemap, use the following line of code : <\/p>\n\n\n
\nsquarify.plot(sizes=d, label=a, alpha=.8)\nplt.axis('off')\nplt.show()\n<\/pre><\/div>\n\n\n
\"Titanic
Titanic Treemap<\/figcaption><\/figure><\/div>\n\n\n\n
Visualizing the treemap, we can get a rough idea about the number of survivors in the first, second, and third class. Just by looking at the treemap, we can confidently say that the second class has the least number of survivors. <\/p>\n\n\n\n
Complete code to plot a treemap in Python<\/h3>\n\n\n\n
The complete code from this section is given below :<\/p>\n\n\n
\nimport seaborn as sns\nimport squarify \nimport matplotlib.pyplot as plt\n\ntitanic = sns.load_dataset('titanic')\n\na = titanic.groupby('class')[['survived']].sum().index.get_level_values(0).tolist()\n\nd = titanic.groupby('class')[['survived']].sum().reset_index().survived.values.tolist()\n\nsquarify.plot(sizes=d,label=a, alpha=.8 )\nplt.axis('off')\nplt.show()\n\n<\/pre><\/div>\n\n\n
Conclusion <\/h2>\n\n\n\n
In this tutorial, we learned how to plot a treemap in python using Squarify. Hope you had fun learning with us.<\/p>\n","protected":false},"excerpt":{"rendered":"
A treemap in Python is a visualization of data that splits a rectangle into sub-parts. The size of each subpart is in proportion to the data it represents. It is somewhat like a pie-chart. Although, treemaps can represent much-more complex data as compared to a pie-chart. It can help you visualize how single values compose […]<\/p>\n","protected":false},"author":14,"featured_media":9938,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[],"class_list":["post-9928","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-examples"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts\/9928","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/comments?post=9928"}],"version-history":[{"count":0,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts\/9928\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/media\/9938"}],"wp:attachment":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/media?parent=9928"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/categories?post=9928"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/tags?post=9928"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}