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Streamlit_rava.py
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import streamlit as st
import altair as alt
import numpy as np
import pandas as pd
import base64
def download_link(object_to_download, download_filename, download_link_text):
if isinstance(object_to_download,pd.DataFrame):
object_to_download = object_to_download.to_csv(index=True)
b64 = base64.b64encode(object_to_download.encode()).decode()
return f'<a href="data:file/txt;base64,{b64}" download="{download_filename}">{download_link_text}</a>'
def main():
bonos = ["AL29", "AL30","AL35","AE38","AL41","AL29D","AL30D","AL35D","AE38D","AL41D",
"GD29", "GD30", "GD35", "GD38", "GD41", "GD46", "GD29D", "GD30D", "GD35D", "GD38D", "GD41D","GD46D"]
periodos = ["Historico", "Intradiario"]
st.sidebar.title("Bonos Argy")
choice = st.sidebar.selectbox("Seleccionar bono 1", bonos)
choice1 = st.sidebar.selectbox("Seleccionar bono 2", bonos)
periodo = st.sidebar.selectbox("Seleccionar periodo", periodos)
if periodo == 'Historico':
url = 'http://clasico.rava.com/empresas/precioshistoricos.php?e=' + choice
df_1 = pd.read_html(url, thousands='.')[0]
df_1.columns = list(df_1.loc[0, :])
df_1 = df_1.drop(0, axis=0)
df_1 = df_1.rename(columns={'Fecha': 'index'}).set_index('index')
# df = df.drop(columns=['Apertura', 'Mínimo', 'Volumen', 'Máximo'], axis=1)
df_1 = df_1.replace('\.', '', regex=True)
df_1 = df_1.replace(',', '.', regex=True)
df_1[df_1.columns[0:5]] = df_1[df_1.columns[0:5]].apply(pd.to_numeric, errors='coerce').round(2)
df_1.rename(columns=lambda col: choice + '_' + col, inplace=True)
url = 'http://clasico.rava.com/empresas/precioshistoricos.php?e=' + choice1
df_2 = pd.read_html(url, thousands='.')[0]
df_2.columns = list(df_2.loc[0, :])
df_2 = df_2.drop(0, axis=0)
df_2 = df_2.rename(columns={'Fecha': 'index'}).set_index('index')
# df = df.drop(columns=['Apertura', 'Mínimo', 'Volumen', 'Máximo'], axis=1)
df_2 = df_2.replace('\.', '', regex=True)
df_2 = df_2.replace(',', '.', regex=True)
df_2[df_2.columns[0:5]] = df_2[df_2.columns[0:5]].apply(pd.to_numeric, errors='coerce').round(2)
if choice == choice1:
choice1 = choice1 + '_1'
df_2.rename(columns=lambda col: choice1 + '_' + col, inplace=True)
df_ratio = pd.concat([df_1, df_2], axis=1, sort=False)
# print(df_ratio)
df_ratio['Ratio'] = df_ratio[choice + '_' + 'Cierre'] / df_ratio[choice1 + '_' + 'Cierre']
df_ratio.index = pd.to_datetime(df_ratio.index, format='%d/%m/%y')
df_ratio.sort_index(ascending=True, inplace=True)
st.dataframe(df_ratio.style.highlight_max(color='green', axis=0).format('{:,.2f}').format({'Ratio': '{:,.5f}'}))
else:
df = pd.read_csv("intradiario.csv",sep=';')
df = df.replace('\.', '', regex=True)
df = df.replace(',', '.', regex=True)
df = df.rename(columns={'Fecha': 'index'}).set_index('index')
df [df.columns[0:22]] = df[df.columns[0:22]].apply(pd.to_numeric, errors='coerce').round(2)
df = df.replace(0,np.nan)
if choice == choice1:
choice1 = choice1 + '_1'
df_ratio = df.filter([choice + '_' + 'Cierre'], axis=1)
df_ratio[choice1 + '_' + 'Cierre'] = df_ratio[choice + '_' + 'Cierre']
else:
df_ratio = df.filter([choice + '_' + 'Cierre',choice1 + '_' + 'Cierre'], axis=1)
df_ratio['Ratio'] = (df_ratio[choice + '_' + 'Cierre'] / df_ratio[choice1 + '_' + 'Cierre']).replace(np.inf, np.nan )
df_ratio.index = pd.to_datetime(df_ratio.index, format='%d/%m/%Y %H:%M')
df_ratio.sort_index(ascending=True, inplace=True)
#cm = sns.light_palette("green", as_cmap=True)
st.dataframe(df_ratio.style.highlight_max(color='green', axis=0).format('{:,.2f}').format({'Ratio':'{:,.5f}'}))
if st.button("Descargar"):
# open('bonos.csv', 'w').write(df_ratio.to_csv())
tmp_download_link = download_link(df_ratio, 'bonos_' + choice + '_' + choice1 + '.csv',
'Presione para descargar el archivo')
st.markdown(tmp_download_link, unsafe_allow_html=True)
if st.button("Resumen"):
st.write(df_ratio.describe())
if st.button("Graficar"):
cust_data = df_ratio["Ratio"]
line = alt.Chart(cust_data.reset_index()).mark_line(
color='red',
size=3
).transform_window(
rolling_mean='mean(Ratio)'
).encode(
x=alt.X('index'),
y=alt.Y('rolling_mean:Q', scale=alt.Scale(zero=False))
).properties(title=choice + '/' + choice1).interactive()
points = alt.Chart(cust_data.reset_index()).mark_line().encode(
x=alt.X('index', axis=alt.Axis(title='Fecha')),
y=alt.Y('Ratio:Q',
axis=alt.Axis(title='Ratio - Media'), scale=alt.Scale(zero=False))
).interactive()
chart = line + points
st.altair_chart(chart, use_container_width=True)
base1 = alt.Chart(df_ratio.reset_index()).encode(
alt.X('index', axis=alt.Axis(title='Fecha')))
line_1 = base1.mark_line(
color='red',
size=3
).encode(
y=alt.Y(choice + '_' + 'Cierre:Q', scale=alt.Scale(zero=False),
axis=alt.Axis(title='Cierre', titleColor='red'))
).properties(title=choice).interactive()
area_1 = base1.mark_area(opacity=0.3, color='#57A44C').encode(
alt.Y(choice + '_' + 'Máximo:Q', scale=alt.Scale(zero=False)
),
alt.Y2(choice + '_' + 'Mínimo:Q')
)
bar_1 = base1.mark_bar().encode(
alt.Y(choice + '_' + 'Volumen:Q', axis=alt.Axis(title='Volumen', titleColor='red'))
)
layer1 = alt.layer(line_1 + area_1, bar_1).resolve_scale(
y='independent'
)
st.altair_chart(layer1, use_container_width=True)
base2 = alt.Chart(df_ratio.reset_index()).encode(
alt.X('index', axis=alt.Axis(title='Fecha')))
line_2 = base2.mark_line(
color='red',
size=3
).encode(
y=alt.Y(choice1 + '_' + 'Cierre:Q', scale=alt.Scale(zero=False),
axis=alt.Axis(title='Cierre', titleColor='red'))
).properties(title=choice1).interactive()
area_2 = base2.mark_area(opacity=0.3, color='#57A44C').encode(
alt.Y(choice1 + '_' + 'Máximo:Q', scale=alt.Scale(zero=False)
),
alt.Y2(choice1 + '_' + 'Mínimo:Q')
)
bar_2 = base2.mark_bar().encode(
alt.Y(choice1 + '_' + 'Volumen:Q', axis=alt.Axis(title='Volumen', titleColor='red')
)
)
layer2 = alt.layer(line_2 + area_2, bar_2).resolve_scale(
y='independent'
)
st.altair_chart(layer2, use_container_width=True)
st.sidebar.info('\nEsta app fue creada usando Streamlit y es mantenida por [herfedo]('
'https://twitter.com/herfedo).\n\n'
'La informacion historica e intradiaria se actualiza al finalizar la rueda.')
if __name__ == '__main__':
main()