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import streamlit as st |
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from utilities.components import get_data, choose_algo, get_plot |
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from types import NoneType |
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import pandas as pd |
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def get_info(category): |
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infos = { |
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" --- Choose --- ":'We Provide several different types of algorithms, such as Clustering or Classification', |
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"Clustering":'Unsupervised, creates clusters of similars individuals', |
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"Classification":"""Supervised, assigns individuals to a class using |
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training data. Last column will be used as targer class.""", |
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"Regression":"Supervised, predicts numerical value to a column, usign training data", |
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"Data Exploration":"Univariate and bivariate data analysis", |
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"Data Preprocessing":"Prepare data for Machine Learning", |
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"Others":'Other algorithms, such as linear regression' |
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} |
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st.info(infos[category]) |
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class Page: |
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def __init__(self, title) -> None: |
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self.title = title |
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self.data = None |
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self.algo = None |
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self.plot = None |
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self.results = None |
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def render(self): |
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st.title(self.title.upper()) |
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col1, col2 = st.columns([2,5]) |
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with col1.container(): |
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data = get_data(self.title) |
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if type(data) == tuple: |
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if self.title == 'Clustering' and type(data[0]) is not NoneType: |
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st.dataframe(data[0], use_container_width=True,height=280) |
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self.data = data |
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with col2.container(): |
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self.algo = choose_algo(self.title) |
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if self.algo is not None and self.data is not None: |
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self.results = pd.DataFrame(self.algo(self.data)) |
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self.plot = get_plot(self.results, self.title) |
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if self.plot is not None: |
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st.plotly_chart(self.plot) |
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if self.results is not None: |
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col1.download_button("Download Results", |
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self.results.to_csv(index=False), |
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"results.csv", |
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"text/csv", |
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key="download-csv") |
