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!pip install plotly==5.3.1 | |
import streamlit as st | |
import pandas as pd | |
import plotly.express as px | |
def load_data(): | |
"""Function for loading data""" | |
df = pd.read_csv("all_stocks_5yr.csv", index_col="date") | |
numeric_df = df.select_dtypes(['float','int']) | |
numeric_cols = numeric_df.columns | |
text_df = df.select_dtypes(['object']) | |
text_cols = text_df.columns | |
stock_column = df['Name'] | |
unique_stocks = stock_column.unique() | |
return df, numeric_cols, text_cols, unique_stocks | |
df, numeric_cols, text_cols, unique_stocks = load_data() | |
# Title of dashboard | |
st.title("Stock Dashboard") | |
# add checknob to sidebar | |
check_box = st.sidebar.checkbox(label="Display dataset") | |
if check_box: | |
# lets show the dataset | |
st.write(df) | |
# give sidebar a title | |
st.sidebar.title("Settings") | |
st.sidebar.subheader("Timeseries settings") | |
feature_selection = st.sidebar.multiselect(label="Features to plot", | |
options=numeric_cols) | |
stock_dropdown = st.sidebar.selectbox(label="Stock Ticker", | |
options=unique_stocks) | |
print(feature_selection) | |
df = df[df['Name']==stock_dropdown] | |
df_features = df[feature_selection] | |
plotly_figure = px.line(data_frame=df_features, | |
x=df_features.index,y=feature_selection, | |
title=(str(stock_dropdown) + ' ' +'timeline') | |
) | |
st.plotly_chart(plotly_figure) |