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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import seaborn as sns | |
| from pickle import load | |
| import base64 | |
| import streamlit as st | |
| #stocker les donneer dans la memoire cash | |
| def load_data(dataset): | |
| df= pd.read_csv(dataset) | |
| return df | |
| def filedownload(df):# permert de telecharger un fichier depuis streamlit | |
| csv = df.to_csv(index=False) | |
| b64 = base64.b64encode(csv.encode()).decode() # strings <-> bytes conversions | |
| href = f'<a href="data:file/csv;base64,{b64}" download="diabete_predictions.csv">Download CSV File</a>' | |
| return href | |
| st.sidebar.image("diab.jpg", width=300)# ajouter une image sur la barre de navigation gauche | |
| def main(): | |
| st.markdown("<h1 style='text-align:center;color: brown;'>Streamlit Diabetis App ❤️</h1>",unsafe_allow_html=True)#affiche des titres en html | |
| st.markdown("<h2 style='text-align:center;color: black;'>Diabetis study in Cameroon</h2>",unsafe_allow_html=True) | |
| menu= ["Home", "Analysis", "Data Visualization", "Machine Learning"]#creer une liste de menus | |
| choice = st.sidebar.selectbox("Select Menu ", menu)#ajouter la liste de menus a la barre de navigation gauche | |
| data= load_data("diabetes.csv")#appler la fonction pour charger les donneer | |
| if choice== menu[0]: | |
| left, middle , right = st.columns((2,3,2))#creation de 3 colonnes | |
| with middle: | |
| st.image("homei.jpg", width=300)#insertion d une image | |
| #afficher de textte en dessous de l image | |
| st.write("This is an app that will analyse diabetes Datas with some python tools that can optimize decisions") | |
| st.subheader("Diabete Informations") | |
| st.write("In Cameroon, the prevalence of diabetes in adults in urban areas is currently estimated at 6 – 8%, with as much as 80% of people living with diabetes who are currently undiagnosed in the population. Further, according to data from Cameroon in 2002, only about a quarter of people with known diabetes actually had adequate control of their blood glucose levels. The burden of diabetes in Cameroon is not only high but is also rising rapidly. Data in Cameroonian adults based on three cross-sectional surveys over a 10-year period (1994–2004) showed an almost 10-fold increase in diabetes prevalence.") | |
| elif choice == menu[1]: | |
| st.subheader("Diabetis Dataset") | |
| st.write(data.head()) | |
| if st.checkbox("Summary"):#insert checkbox button | |
| st.write(data.describe()) | |
| elif st.checkbox("Correlation"): | |
| fig=plt.figure(figsize=(15,15)) | |
| st.write(sns.heatmap(data.corr(), annot=True)) | |
| st.pyplot(fig) | |
| elif choice== menu[2]: | |
| if st.checkbox("CountPlot"): | |
| fig=plt.figure(figsize=(15,15)) | |
| sns.countplot(x="Age", data=data) | |
| st.pyplot(fig) | |
| if st.checkbox("ScatterPlot"): | |
| fig=plt.figure(figsize=(5,5)) | |
| sns.scatterplot(x="Glucose", y= "Age",data=data, hue="Outcome") | |
| st.pyplot(fig) | |
| elif choice == menu[3]: | |
| tab1, tab2, tab3 = st.tabs([":clipboard: Data ",":bar_chart: Visualisation", ":mask: :smile: Prediction"]) | |
| uploaded_file= st.sidebar.file_uploader("Upload your csv file here", type=["csv"]) | |
| if uploaded_file: | |
| dfs= load_data(uploaded_file) | |
| with tab1: | |
| st.subheader("Loaded dataset") | |
| st.write(dfs) | |
| with tab2: | |
| st.subheader("Histogram Of Gluccose") | |
| fig= plt.figure(figsize=(8,8)) | |
| sns.histplot(x="Glucose", data=data) | |
| st.pyplot(fig) | |
| with tab3: | |
| pickled_model = load(open("finalDiabeteModel.pkl", "rb"))#chargement du model de prediction | |
| pred= pickled_model.predict(dfs) | |
| pp= pd.DataFrame(pred,columns=["predictions"]) | |
| ndf= pd.concat([dfs,pp], axis=1) | |
| ndf["predictions"].replace(0, "No Diabete Risk",inplace=True) | |
| ndf["predictions"].replace(1, " Diabete Risk",inplace=True) | |
| st.write(ndf) | |
| button = st.button("Download") | |
| if button: | |
| st.markdown(filedownload(ndf), unsafe_allow_html=True) | |
| main() |