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## LIBRARIES ###
from cProfile import label
from tkinter import font
from turtle import width
import streamlit as st
import pandas as pd
from datetime import datetime
import plotly.express as px
def read_file_to_df(file):
return pd.read_csv(file)
def date_range(df):
time = df.index.to_list()
time_range = []
for t in time:
time_range.append(str(datetime.strptime(t, '%Y-%m-%dT%H:%M:%S.%fZ').date().month) +'/' + str(datetime.strptime(t, '%Y-%m-%dT%H:%M:%S.%fZ').date().day))
return time_range
if __name__ == "__main__":
### STREAMLIT APP CONGFIG ###
st.set_page_config(layout="wide", page_title="HF Hub Model Usage Visualization")
popularity = st.sidebar.radio(
"Model popularity", ('Low', 'Moderate', 'High'), key = "popularity", index=2)
st.header("Model Usage Visualization")
with st.container():
df_2021 = read_file_to_df("./assets/2021/model_init_time.csv")
df_2021.fillna(0, inplace=True)
df_plot = df_2021.set_index('Model').T
df_plot.index = date_range(df_plot)
df_plot_2021 = pd.DataFrame()
if popularity == 'Low':
df_plot_2021 = df_plot[df_plot.columns[(df_plot.mean(axis=0)<=5000) & (df_plot.mean(axis=0)>=3500)]]
elif popularity == 'Moderate':
df_plot_2021 = df_plot[df_plot.columns[(df_plot.mean(axis=0)<=40000) & (df_plot.mean(axis=0)>=5000)]]
else:
df_plot_2021 = df_plot[df_plot.columns[df_plot.mean(axis=0)>=40000]]
fig = px.line(df_plot_2021, title="Model Usage Trends in 2021", labels={"index": "Weeks", "value": "Usage", "variable": "Model"})
st.plotly_chart(fig, use_container_width=True)
with st.container():
df_2022 = read_file_to_df("./assets/2022/model_init_time.csv")
df_2022.fillna(0, inplace=True)
df_plot = df_2022.set_index('Model').T
df_plot.index = date_range(df_plot)
df_plot_2022 = pd.DataFrame()
if popularity == 'Low':
df_plot_2022 = df_plot[df_plot.columns[(df_plot.mean(axis=0)<500) & (df_plot.mean(axis=0)>=300)]]
elif popularity == 'Moderate':
df_plot_2022 = df_plot[df_plot.columns[(df_plot.mean(axis=0)<=1500) & (df_plot.mean(axis=0)>=500)]]
else:
df_plot_2022 = df_plot[df_plot.columns[df_plot.mean(axis=0)>=1500]]
fig = px.line(df_plot_2022, title="Model Usage Trends in 2022", labels={"index": "Weeks", "value": "Usage", "variable": "Model"})
st.plotly_chart(fig, use_container_width=True)
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