Grouping numerical values in categories

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I have numeric data within Student marks and I would like to group them into 3 categories A, B and C.

df = pd.DataFrame([('Adel',  3.5),
                   ('Betty',  2.75),
                   ('Djamel',  2.10),
                   ('Ramzi',  1.75),
                   ('Alexa', 3.15)],
                  columns=('Name', 'GPA'))

I tried function pd.cut() but it didn't lead to wanted result .

Here's a way using pd.cut:

df = df.sort_values('GPA')

df['bins'] = pd.cut(df['GPA'], bins=3, labels = ['A','B','C'])

     Name   GPA bins
3   Ramzi  1.75    A
2  Djamel  2.10    A
1   Betty  2.75    B
4   Alexa  3.15    C
0    Adel  3.50    C

R Handbook: Converting Numeric Data to Categories, Clear examples in R. Categorizing data; Percentiles; Clustering, PAM, Medoids. One approach is to create categories according to logical cut-off values in the� Select any cells in the row labels that have the sales value. Go to Analyze –> Group –> Group Selection. In the grouping dialog box, specify the Starting at, Ending at, and By values. In this case, By value is 250, which would create groups with an interval of 250. Click OK.

In a recent research, a PSO was implemented to classify students under unknown number of groups. PSO showed improved capabilities compared to GA. I think that all you need is the specific research.

The paper is: Forming automatic groups of learners using particle swarm optimization for applications of differentiated instruction

You can find the paper here: https://doi.org/10.1002/cae.22191

Perhaps the researchers could guide you through researchgate: https://www.researchgate.net/publication/338078753

You just need to remove the technic from automatic number of groups

Grouping data and assigning alphabet and numeric values for new , Every time a new combination of values appear in the concatenated values (col 4 ) for a particular group (col2), I need to assign a new category for that row both� One approach is to create categories according to logical cut-off values in the scores or measured values. An example of this is the common grading system in the U.S. in which a 90% grade or better is an “A”, 80–89% is “B”, etc. It is common in this approach to make the categories with equal spread in values.

I found this solution :

import pandas as pd, numpy as np

df = pd.DataFrame({'GPA': [99, 53, 71, 84, 84],
                   'Name': ['Betty', 'Djamel', 'Ramzi', 'Alexa', 'Adel']})

bins = [0, 50, 60, 70, 80, 100]
names = ['F', 'D', 'C', 'B', "A"]

d = dict(enumerate(names, 1))

df['Rank'] = np.vectorize(d.get)(np.digitize(df['GPA'], bins))


thanks to this link here.

Grouping Variables To Split Data - MATLAB & Simulink, A grouping variable can be any of these data types: The findgroups function returns a vector of group numbers that define groups based on the unique values � How to group numeric fields. Firstly, right click on the numeric field in the field list, as select “group”. Once grouped, you can then use these groups (or bins) to count how many values fall into each bin, create "totals" for each bin etc. Is it possible to create 'bins' to categorise the result of a measure?

Grouping Variables - MATLAB & Simulink, A grouping variable can be any of these data types: Observations that have the same grouping variable value belong to the same group. If G is a numeric or logical vector, then the groups correspond to the distinct values in G , in the� Grouping numeric values is useful when you use a numeric field in a row or column field. Excel enables you to specify numeric ranges into which the field items are grouped. For example, suppose you have an Excel PivotTable of invoice data that shows the extended price (the row field) and the salesperson (the column field).

Array that contains values assigned to categories, A common use of categorical arrays is to specify groups of rows in a table. You can use valueset to include categories for values not present in A . Conversely, numeric array | logical array | categorical array | datetime array | duration array� Assign a value or category based on a number range with formula. The following formulas can help you to assign a value or category based on a number range in Excel. Please do as follows. 1. Select a blank cell, enter the below formula into it and then press the Enter key.

Grouping Data - SPSS Tutorials, will see each unique numeric value as a distinct category. In order to split the file, SPSS requires that the data be sorted with respect to the splitting variable. Ordinal data mixes numerical and categorical data. The data fall into categories, but the numbers placed on the categories have meaning. For example, rating a restaurant on a scale from 0 (lowest) to 4 (highest) stars gives ordinal data. Ordinal data are often treated as categorical, where the groups are ordered when graphs and charts are made.

Comments
  • What is the error you got ?