Add app

Dockerfile

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+# Start with a lightweight Linux Anaconda image
+FROM continuumio/miniconda3
+
+# Update all packages and install nano unzip and curl
+RUN apt-get update
+RUN apt-get install nano unzip curl -y
+
+# THIS IS SPECIFIC TO HUGGINFACE
+# We create a new user named "user" with ID of 1000
+RUN useradd -m -u 1000 user
+# We switch from "root" (default user when creating an image) to "user" 
+USER user
+# We set two environment variables 
+# so that we can give ownership to all files in there afterwards
+# we also add /home/user/.local/bin in the $PATH environment variable 
+# PATH environment variable sets paths to look for installed binaries
+# We update it so that Linux knows where to look for binaries if we were to install them with "user".
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+# We set working directory to $HOME/app (<=> /home/user/app)
+WORKDIR $HOME/app
+
+# Install basic dependencies
+RUN pip install boto3 pandas gunicorn streamlit scikit-learn matplotlib seaborn plotly
+
+# Copy all local files to /home/user/app with "user" as owner of these files
+# Always use --chown=user when using HUGGINGFACE to avoid permission errors
+COPY --chown=user . $HOME/app
+
+# THIS IS SPECIFIC TO HUGGINGFACE AS WELL
+# expose port 7860 which is the port used by HuggingFace for Web Applications
+EXPOSE 7860
+
+# Run streamlit server
+CMD streamlit run --server.port 7860 app.py

app.py

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+import streamlit as st
+import pandas as pd
+import plotly.express as px 
+import plotly.graph_objects as go
+import numpy as np
+
+
+### CONFIG
+st.set_page_config(
+    page_title="E-commerce",
+    page_icon="💸",
+    layout="wide"
+  )
+
+### TITLE AND TEXT
+st.title("Sport Heroes")
+st.image("https://stillmed.olympic.org/media/Images/OlympicOrg/IOC/The_Organisation/The-Olympic-Rings/Olympic_rings_TM_c_IOC_All_rights_reserved_1.jpg", width=300)
+
+### EXPANDER
+st.subheader("Opening French Olympic Games")
+with st.expander("⏯️ Watch "):
+    st.video("https://youtu.be/6ldC6uHxHIc?si=94yBjIq41YakFQ1C")
+
+st.subheader("The Raw Data")
+st.markdown("""
+    All the __Heroes__ are in this Raw Datas 👇
+""")
+
+### LOAD AND CACHE DATA
+DATA_URL = ('athlete_events.csv')
+
+@st.cache_data # this lets the 
+def load_data(nrows):
+    data = pd.read_csv(DATA_URL, nrows=nrows)
+    return data
+
+data_load_state = st.text('Loading data...')
+data = load_data(1000)
+data_load_state.text("") # change text from "Loading data..." to "" once the the load_data function has run
+
+## Run the below code if the check is checked ✅
+if st.checkbox('Show raw data'):
+    st.subheader('Raw data')
+    st.write(data) 
+
+
+### SHOW GRAPH STREAMLIT
+
+st.subheader("Medals per Country")
+medal_per_country = data.groupby("NOC")["Medal"].describe()  # Fix bar chart issue
+st.bar_chart(medal_per_country)
+
+### SHOW GRAPH PLOTLY + STREAMLIT
+
+st.subheader("All the Olympic Countries X events")
+
+fig = px.histogram(data, x="Year", color='City', barmode="group")
+st.plotly_chart(fig, use_container_width=True)
+
+
+### SIDEBAR
+st.sidebar.header("Build dashboards with Streamlit")
+st.sidebar.markdown("""
+    * [Opening French Olympic Games](#opening-french-olympic-games)
+    * [Sport Heros Top](#sport-heroes)
+    * [Medals per Country](#medals-per-country)
+    * [Input Data](#input-data)
+""")
+e = st.sidebar.empty()
+e.write("")
+st.sidebar.write("Made with 💖 by [Jedha](https://jedha.co)")
+st.sidebar.image("Leon-Marchand.png")
+
+
+
+st.markdown("---")
+
+#### CREATE TWO COLUMNS
+
+@st.cache_data # this lets the 
+def load_datam():
+    datam = pd.read_csv(DATA_URL)
+    return datam
+datam = load_datam()
+st.markdown("**1️⃣ Example of input widget**")
+country = st.selectbox("Select a country you want to see all the medals", datam["NOC"].sort_values().unique())
+country_medal = datam[datam["NOC"]==country].groupby('Medal')['Sex'].value_counts().reset_index()
+fig = px.bar(country_medal, x='Medal', y='count', color='Sex', barmode='group')
+fig.update_layout(bargap=0.2)
+st.plotly_chart(fig, use_container_width=True)
+