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