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This article mainly introduces "what is the practical method of python data visualization JupyterLab". In daily operation, I believe that many people have doubts about what the practical method of python data visualization JupyterLab is. Xiaobian consulted all kinds of materials and sorted out simple and easy-to-use operation methods. I hope it will be helpful to answer the doubts of "what is the practical method of python data visualization JupyterLab?" Next, please follow the editor to study!

JupyterLab is the latest data science production tool featured by Jupyter. In a sense, it appears to replace Jupyter Notebook.

As a web-based integrated development environment, you can use it to write notebook, operate terminals, edit markdown text, open interactive mode, view csv files and pictures, and other functions.

The best experience of JupyterLab is that it has rich extensions, and I remember we had to rely on numpy and matplotlib for exploratory data analysis in the past. Fortunately for us, those days are long gone.

Here comes Mito!

Meet Mito

Mito is a free JupyterLab extension that makes it easy to explore and transform datasets using Excel.

When you start Mito, it displays a spreadsheet view of Pandas Dataframe. With just a few clicks, you can create, read, update, and delete.

How to start Mito

Using Mito to load data and display a spreadsheet view is simple:

Import mitosheetimport pandas as pdurl = 'https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv'iris = pd.read_csv (url) mitosheet.sheet (iris)

Mito opens a powerful spreadsheet viewer that can filter, sort, and edit data.

PivotTable report

Mito can create a PivotTable report with just a few clicks. It supports many common aggregations, such as sum, median, mean, count, unique, etc.

A PivotTable is a grouped values table that aggregates items from a wider range of tables in one or more discrete categories.

Impressive features of Mito

Spreadsheet formula

Dynamic formula is a killer function of Excel. Excel allows people who are not familiar with programming to easily create complex spreadsheets. What if I told you that Mito supports dynamic formulas in Excel. This feature really surprised me.

Take a look at the following dynamic diagram to see how Mito's summation formula works:

Visual data

In recent years, Python data visualization libraries emerge one after another, from matplotlib to seaborn, plotly, it only takes a few commands to achieve amazing visualization in Python.

Mito can visualize your data without writing any code. It supports bar charts, box charts, histograms, and scatter charts.

Automatic code generation

Mito can convert each operation into Pandas code, which you can then share with your colleagues. This is a great feature for inexperienced data scientists. I made a few clicks, and Mito generated the following code snippet:

Mito installation

First, you need to download the Mito installer using the following command:

Python-m pip install mitoinstaller

Then install it, just run:

Python-m mitoinstaller install at this point, on the "what is the practical method of python data visualization JupyterLab" study is over, I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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