Here is a code for automatic scoring once you get students' answer sheet and standard answer sheet.

Problem	1	2	3	4
Alice	A	BD	D	C
Bob	B	CD	D	C
David	B	AB	A	C
Mike	B	AC	C	D

Problem	1	2	3	4
Answer	A	BD	D	C
Score	1	2	1	1

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import openpyxl


#input two dataframe, stdt_ans is students' answer sheet dataframe (row: Name, column: problem), 
#and corr_ans is the standard answer dataframe (1st row: standard answer for each problem, 2nd row, score for each prolem)

def Get_scores(stdt_ans,corr_ans): 
    Score_matrix = stdt_ans.copy()
    row_num = len(stdt_ans) #row number, i.e. student number
    col_num = len(stdt_ans.columns)#col number, i.e. problem number
    for m in range(row_num): #iterate by row
        for n in range(1,col_num): #iterate by column
            if stdt_ans.iat[m,n] == corr_ans.iat[0,n]: #if same as std ans, get score
                Score_matrix.iat[m,n] = float(corr_ans.iat[1,n])
            else: #otherwise no score
                Score_matrix.iat[m,n] = 0
    Score_matrix['Sum'] = Score_matrix.iloc[:,1:col_num].sum(axis = 1) #get total score of each student
    Score_matrix = Score_matrix.sort_values(by=['Sum'], ascending = False)#sort by total score
    print(Score_matrix)
    df3 = Score_matrix.drop(columns = ['Name'], axis = 1)
    df3 = df3.astype('float')
    result = df3.describe(include = 'all' ) #get average scores for each problem
    print(result)
    Score_matrix.to_excel('Score_results.xlsx')
    result.to_excel('Analysis.xlsx')
    fig = Score_matrix['Sum'].plot(kind ='hist') #plot histogram
    fig.set_xlabel("Total scores")
    fig.set_ylabel("Counts")
    plt.savefig('sum_hist.pdf')
    return


#an example
df1 = pd.read_excel("ans.xlsx")
df2 = pd.read_excel("standard.xlsx")

Get_scores(df1,df2)