如何对 dataframe 中的唯一值进行分类和分组？

Question

I am using this dataset from Kaggle: https://www.kaggle.com/kwadwoofosu/predict-test-scores-of-students

Sample of data I am working with:

I am building an input form on streamlit based on predictions made on this dataset. Upon selecting the school name, I want to auto select the school setting and school type based on this and if possible show only the selected available classrooms of that school.

Suppose, the school selected is ANKYI then my application should set the school_setting value as Urban, School_type as Non-public and show me only the classrooms available in the school.

How to achieve this categorization of the dataframe using python?

Answer 1

For each column in the pandas dataframe, you can use the .unique() method to return an array of unique values.

So, for your data, you could do

school_types = list(df[df['school']=='ANKYI']['school_type'].unique())

To break this apart - the return of the .unique() method is an array-type object, and so we can turn it into a list (if you want to). Then we are using our dataframe (whatever you call it), but we want to filter to just look at rows where 'school' is equal to 'ANKYI'. Within those rows, we just want to look at the column called 'school_type', and that column (filtered to just those rows) is what we want to return the unique values from.