在python中，如何制作一列中每个值与另一列中的值出现的次数（多少行）的矩阵？

Question

I have a filtered data frame that changes how many rows it has, depending on how the user filters it. I need to count how many times a value in one column matches with a value in another column for each row. for example: Lets say my DF is: sample data frame I would need a 3x3 matrix that has the sums of each time a value in column A occurs with a value in column B. The matrix would be: sample matrix I can determine what the dimension of the matrix should be, and what the unique values are for each column and how many times they occur, but need to find an efficient way to sum how frequently the values appear together.

Answer 1

I was able to achieve your desired output like this:

from collections import Counter
import pandas as pd

df = pd.DataFrame({'A':[500,500,300,400,400,300],'B':[10,10,20,10,20,30]})
inp = df.groupby('A')['B'].agg(Counter).to_frame()
out = pd.DataFrame.from_records(inp['B'].tolist(), index=inp.index).fillna(0).T

output:

A   300  400  500
20  1.0  1.0  0.0
30  1.0  0.0  0.0
10  0.0  1.0  2.0

the groupyby/Counter counts how many occurrences of values in B occur in each value in A..then the second step unpacks the column of dictionaries into a dataframe