Error while downloading the dataframe from Streamlit web application after data preprocessing

The required task is deploy the data preprocessing web application on Streamlit in which user can upload the raw dataframe and download the processed dataframe. I am trying to download the file on which data preprocessing like missing value imputation has been done but i am getting an error as below :

RuntimeError: Invalid binary data format: <class 'pandas.core.frame.DataFrame'>

I do not have any clue as to how to solve the problem. Please help me as I am new to python and StreamLit. The code is

import streamlit as st
import pandas as pd
import os
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
temp='\\temp.csv'
path=os.getcwd()
path=path+temp

def upload_csv(zxc):
    if zxc:
        df=pd.read_csv(zxc)
        st.dataframe(df)
        df.to_csv(path,index=False)
        return df
    

def upload_xlsx(zxc):
    if zxc:
        df=pd.read_excel(zxc)
        st.dataframe(df)
        df.to_csv(path,index=False)
        return df

def mvt_mean(df):
    new_df=df.fillna(df.mean())
    new_df=new_df.fillna(df.select_dtypes(include='object').mode().iloc[0])
    st.dataframe(new_df)
    return new_df


def mvt_median(df):
    new_df=df.fillna(df.median())
    new_df=new_df.fillna(df.select_dtypes(include='object').mode().iloc[0])
    st.dataframe(new_df)
    return new_df

def mvt_mode(df):
    new_df=df.fillna(df.select_dtypes(include='object').mode().iloc[0])
    st.dataframe(new_df)
    return new_df

def export_data():
    with open('temp.csv','r+') as f:
        #contents=csv.reader(f)
        df=pd.read_csv(path)
        result=mvt_mean(df)
        result.to_csv(index=False)
        st.sidebar.download_button(label='Download CSV',data=result,mime='text/csv',file_name='Download.csv')
        return



st.title('Hello Streamlit Front end for Python ')
option = st.sidebar.selectbox('DSA Application',('Data-PreProcessing', 'Data-Visualization', 'Machine-Learning'))
st.sidebar.write('You selected:', option)
if option=='Data-PreProcessing':
    format_options=['csv','xlsx']
    a=st.sidebar.radio('Choose the file type',format_options)
    if a=='csv':
        b=st.sidebar.file_uploader("Choose a file",type='csv')
        if b :
            if st.sidebar.checkbox('Upload File'):
                df=upload_csv(b)
                #if st.sidebar.checkbox('Proceed for missing value treatment'):
                opt=st.sidebar.radio('Impute Missing Value using',('Mean','Median','Mode'))
                st.sidebar.write('You selected',opt)
                if opt=='Mean':
                    mvt_mean(df)
                    
                    
                    export_data()
                elif opt=='Median':
                    mvt_median(df)
                    #st.sidebar.download_button(label='Download CSV',data=d,mime='text/csv',file_name='Download.csv')
                    export_data()
                elif opt=='Mode':
                    mvt_mode(df)
                    #st.sidebar.download_button(label='Download CSV',data=d,mime='text/csv',file_name='Download.csv')
                    export_data()
    #elif a=='xlsx':
        #a=st.sidebar.file_uploader("Choose a file",type='xlsx')
        #b=st.sidebar.button('Upload File')
        #if b:
            #df=upload_xlsx(a)
            #st.dataframe(df)