Python uses Pandas to achieve data sorting and grouping

Preparation work: 1. Install Python and Pandas: Ensure that Python has been installed and run the following command on the terminal to install the Pandas library: ` pip install Pandas` Dependent class libraries: 1. Pandas: Python library for data processing and analysis Dataset introduction: This example will use an example dataset that contains information about movies, such as movie name, movie type, release year, etc. You can download the dataset from the following website: https://github.com/pandas-dev/pandas/blob/master/doc/data/titanic.csv Sample data description: The movie dataset contains the following columns: -Title: Movie Title -Genre: Movie genre -Year: Release year Implementation sample code: python import pandas as pd #Read data Data=pd.read_ CSV ('Movie Dataset. csv ') #View the first few rows of data print(data.head()) #Sort in ascending order based on the Year column sorted_data = data.sort_values('Year', ascending=True) #View sorted data print(sorted_data.head()) #Group according to the Genre column and calculate the amount of data in each group grouped_data = data.groupby('Genre').size() #View grouped data print(grouped_data) The above code first imported the Pandas library, and then used 'read'_ The CSV 'function reads a data file called' Movie Dataset. csv '. Next, we used the 'head' function to view the first few rows of data. Then, use 'sort'_ The values' function sorts the data in ascending order according to the 'Year' column and uses the 'head' function to view the sorted data. Finally, use the 'groupby' function to group the data according to the 'Genre' column, calculate the number of data in each group using the 'size' function, and then use the print function to output the grouped data.