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import streamlit as st
import pandas as pd
import numpy as np
import plotly.express as px
# Set the page configuration to wide layout
st.set_page_config(layout="wide")
data = pd.read_csv("encodings_2.csv")
# Select only the 'token' and 'count' columns
token_count_data = data[['token', 'count']]
# Set the 'token' column as the index
token_count_data = token_count_data.set_index('token')
# Sort the data by 'count' in descending order
token_count_data = token_count_data.sort_values('count', ascending=False)
# Add sliders with floating-point values
slider1 = st.slider('Select lower percentage', min_value=0.0,
max_value=100.0, value=0.0, step=0.1)
slider2 = st.slider('Select upper percentage', min_value=0.0,
max_value=100.0, value=1.0, step=0.1)
if slider1 > slider2:
st.warning(
"Lower percentage should be less than or equal to upper percentage.")
else:
# Calculate the number of rows to display based on the selected percentage range
total_rows = len(token_count_data)
lower_index = int(total_rows * slider1 / 100)
upper_index = int(total_rows * slider2 / 100)
# Filter the data based on the selected range and sort by 'count' in ascending order
filtered_data = token_count_data.iloc[lower_index:upper_index].sort_values(
'count', ascending=True)
# Create a bar chart using Plotly with all labels
fig = px.bar(filtered_data, x='count',
y=filtered_data.index, text=filtered_data.index)
fig.update_yaxes(type='category', tickmode='array',
tickvals=filtered_data.index)
fig.update_layout(height=5000)
# Display the bar chart using Streamlit
st.plotly_chart(fig, use_container_width=True)
# Set the chart width to a percentage of the container width
width_percentage = 90
html_code = f"""
<script>
document.addEventListener("DOMContentLoaded", function() {{
var chart = document.getElementsByClassName('js-plotly-plot')[0];
if (chart) {{
chart.style.width = '{width_percentage}%';
}}
}});
</script>
"""
st.markdown(html_code, unsafe_allow_html=True)
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