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import pandas as pd
import numpy as np
from ydata_synthetic.synthesizers.regular import RegularSynthesizer
from ydata_synthetic.synthesizers import ModelParameters, TrainParameters
import streamlit as st
from os import getcwd
text_file=st.file_uploader("Upload the Data File")
st.write("-----------------------------")
if text_file is not None:
df=pd.read_csv(text_file)
dd_list=df.columns
cat_cols=st.multiselect("Select the Categorical Columns",dd_list)
num_cols=st.multiselect("Select the Numerical Columns",dd_list)
Output_file=st.text_input('Enter Output File Name')
s=st.number_input('Enter the Sample Size',1000)
OP=Output_file + '.csv'
sub=st.button('Submit')
if sub:
batch_size = 50
epochs = 3
learning_rate = 2e-4
beta_1 = 0.5
beta_2 = 0.9
ctgan_args = ModelParameters(batch_size=batch_size,
lr=learning_rate,
betas=(beta_1, beta_2))
train_args = TrainParameters(epochs=epochs)
synth = RegularSynthesizer(modelname='ctgan', model_parameters=ctgan_args)
synth.fit(data=df, train_arguments=train_args, num_cols=num_cols, cat_cols=cat_cols)
df_syn = synth.sample(s)
df_syn.to_csv(OP)
c=getcwd()
c=c + '/' + OP
with open(c,"rb") as file:
st.download_button(label=':blue[Download]',data=file,file_name=OP,mime="image/png")
st.success("Thanks for using the app !!!")
# st.markdown("""
# <style>
# /* Hide Streamlit Branding */
# #MainMenu {visibility: hidden;}
# footer {visibility: hidden;}
# header {visibility: hidden;}
# </style>
# """, unsafe_allow_html=True) |