I have a dataframe that has the number 6 in each row. Which will be my main number I would like to use to find values that appear most often with the number 6 that has more than 2 of the same values. Here is my dataframe below, import pandas as pd df = pd.DataFrame([[1,2,4,5,6,8], [5,6,20,22,23,34], [6,12,13,34,45,46], [4,6,10,29,32,33], [1,6,13,23,33,35], [1,2,5,6,9,10], [1,2,3,5,6,8]], columns = ['Num1','Num2','Num3','Num4','Num5','Num6']) I have tried this code below which is close to what I'm looking for. However, I would like to return the number 6, values, and values count. df1 = df.stack().value_counts() df2 = df1[df1 >= 2] I would like my results to be like this below if possible or similar import pandas as pd result = pd.DataFrame([[6,1,4], [6,5,4], [6,2,3], [6,4,2], [6,8,2], [6,10,2], [6,13,2], [6,23,2], [6,33,2], [6,34,2]], columns = ['Num1','Values','Count']) Continue reading...
