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import streamlit as st
import pandas as pd
import numpy as np
df = pd.read_csv('last_results_4.csv')
image1 = 'images/rs_pmpa.PNG'
title_html = """
<style>
@font-face {
font-family: 'Quicksand';
src: url('font/Quicksand-VariableFont_wght.ttf') format('truetype');
}
body {
font-family: 'Quicksand', sans-serif;
}
.custom-title {
color: darkgreen;
font-size: 30px;
font-weight: bold;
}
</style>
<span class='custom-title'>PREVISÕES DE RECEITAS</span>
"""
# Set a fixed width for the sidebar
st.markdown(
"""
<style>
.sidebar .sidebar-content {
width: 300px;
}
</style>
""",
unsafe_allow_html=True
)
with st.sidebar:
st.image(image1, use_column_width=True)
st.markdown(title_html, unsafe_allow_html=True)
selected_instituicao = st.selectbox('Seleciona Instituição', df['Instituição'].unique())
selected_conta = st.selectbox('Seleciona Conta', df['Conta'].unique())
# Filter the DataFrame based on selected values
filtered_df = df[(df['Instituição'] == selected_instituicao) & (df['Conta'] == selected_conta)]
# Set custom width for columns
col1_width = 400
col2_width = 400
col1, col2 = st.columns([col1_width, col2_width])
# Display the Forecasts values in the first column
col1.header('Valores previstos')
if not filtered_df.empty:
data_string = filtered_df['Forecasts'].iloc[0]
# Split the string into lines
lines = data_string.split('\n')
# Iterate through the lines and extract the values
for line in lines[:-2]:
period, value = line.split()
num_float = float(value)
monetary_value = f'R$ {num_float:,.2f}' # Adding commas for thousands separator
col1.write(f"Período {period}: {monetary_value}")
else:
col1.warning('No data available for the selected filters.')
# Display the Forecasts values as line plots in the second column
col2.header('Gráfico com previsões')
if not filtered_df.empty:
data_string = filtered_df['Forecasts'].iloc[0]
# Create a list to store data for each period
data = []
# Split the string into lines
lines = data_string.split('\n')
# Iterate through the lines and extract the values
for line in lines[:-2]:
period, value = line.split()
num_float = float(value)
monetary_value = f'R$ {num_float:,.2f}' # Adding commas for thousands separator
data.append({'Period': int(period), 'Monetary Value': num_float})
# Create a DataFrame from the list
chart_data = pd.DataFrame(data)
# Sort the DataFrame by 'Period'
chart_data = chart_data.sort_values(by='Period')
# Display line chart with "period" on X-axis and "Monetary Value" on Y-axis
col2.line_chart(chart_data.set_index('Period'))
else:
col2.warning('No data available for the selected filters.')
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