vsumm/tesla-sentiment-analysis

1from datetime import date2from datetime import datetime3import re4 5import numpy as np  6import pandas as pd 7from PIL import Image8import plotly.express as px  9import plotly.graph_objects as go10import streamlit as st  11import time12 13from plotly.subplots import make_subplots14 15# Read CSV file into pandas and extract timestamp data16dfSentiment = pd.read_csv("./sentiment_data.csv")17dfSentiment['timestamp'] = [datetime.strptime(dt, '%Y-%m-%d') for dt in dfSentiment['timestamp'].tolist()]18 19# Multi-select columns to build chart20col_list = dfSentiment.columns.tolist()21 22r_sentiment = re.compile(".*sentiment")23sentiment_cols = list(filter(r_sentiment.match, col_list))24 25r_post = re.compile(".*post")26post_list = list(filter(r_post.match, col_list))27 28r_perc= re.compile(".*perc")29perc_list = list(filter(r_perc.match, col_list))30 31r_close = re.compile(".*close")32close_list = list(filter(r_close.match, col_list))33 34r_volume = re.compile(".*volume")35volume_list = list(filter(r_volume.match, col_list))36 37sentiment_cols = sentiment_cols + post_list38stocks_cols = close_list + volume_list39 40# Config for page41st.set_page_config(42    page_title= 'TSLA Bot',43    page_icon='✅',44    layout='wide',45)46 47with st.sidebar:48    # FourthBrain logo to sidebar49    fourthbrain_logo = Image.open('./images/fourthbrain_logo.png')50    st.image([fourthbrain_logo], width=300)51 52    # Date selection filters53    start_date_filter = st.date_input(54            'Start Date',55        min(dfSentiment['timestamp']),56        min_value=min(dfSentiment['timestamp']),57        max_value=max(dfSentiment['timestamp'])58        )59        60 61    end_date_filter = st.date_input(62        'End Date',63        max(dfSentiment['timestamp']),64        min_value=min(dfSentiment['timestamp']),65        max_value=max(dfSentiment['timestamp'])66        )67 68    sentiment_select = st.selectbox('Select Sentiment/Reddit Data', sentiment_cols)69    stock_select = st.selectbox('Select Stock Data', stocks_cols)70 71# Banner with TSLA and Reddit images72tsla_logo = Image.open('./images/tsla_logo.png')73reddit_logo = Image.open('./images/reddit_logo.png')74st.image([tsla_logo, reddit_logo], width=200)75 76# dashboard title77st.title('Vir\'s Sentiment Analysis for Tesla Stock Price')78 79## dataframe filter80# start date81dfSentiment = dfSentiment[dfSentiment['timestamp'] >= datetime(start_date_filter.year, start_date_filter.month, start_date_filter.day)]82    83# end date84dfSentiment = dfSentiment[dfSentiment['timestamp'] <= datetime(end_date_filter.year, end_date_filter.month, end_date_filter.day)]85dfSentiment = dfSentiment.reset_index(drop=True)86 87 88# creating a single-element container89placeholder = st.empty()90 91# near real-time / live feed simulation92for i in range(1, len(dfSentiment)-1):93 94    # creating KPIs95    last_close =  dfSentiment['close'][i]96    last_close_lag1 = dfSentiment['close'][i-1]97    last_sentiment = dfSentiment['sentiment_score'][i]98    last_sentiment_lag1 = dfSentiment['sentiment_score'][i-1]99 100 101    with placeholder.container():102 103        # create columns104        kpi1, kpi2, kpi3 = st.columns(3)105 106        # fill in those three columns with respective metrics or KPIs107        kpi1.metric(108            label='Sentiment Score',109            value=round(last_sentiment, 3),110            delta=round(last_sentiment_lag1, 3),111        )112        113        kpi2.metric(114            label='Last Closing Price',115            value=round(last_close),116            delta=round(last_close - last_close_lag1)117        )        118 119        # create two columns for charts120        fig_col1, fig_col2 = st.columns(2)121        122        with fig_col1:123            # Add traces124            fig=make_subplots(specs=[[{"secondary_y":True}]])125 126            fig.add_trace(                               127                go.Scatter(                          128                x=dfSentiment['timestamp'][0:i],129                y=dfSentiment[sentiment_select][0:i],130                name=sentiment_select,131                mode='lines',                            132                hoverinfo='none',                        133                )              134            )135 136            if sentiment_select.startswith('perc') == True:137                yaxis_label = '% Change Sentiment'138 139            elif sentiment_select in sentiment_cols:140                yaxis_label = 'Sentiment Score'141 142            elif sentiment_select in post_list:143                yaxis_label = 'Volume'144 145            fig.layout.yaxis.title=yaxis_label146                                          147            if stock_select.startswith('perc') == True:148                fig.add_trace(                               149                    go.Scatter(                          150                    x=dfSentiment['timestamp'][0:i],151                    y=dfSentiment[stock_select][0:i],152                    name=stock_select,153                    mode='lines',                            154                    hoverinfo='none', 155                    yaxis='y2',                    156                    ) 157                )158                fig.layout.yaxis2.title='% Change Stock Price ($US)'159            160            elif stock_select == 'volume':161                fig.add_trace(                               162                    go.Scatter(                          163                    x=dfSentiment['timestamp'][0:i],164                    y=dfSentiment[stock_select][0:i],165                    name=stock_select,166                    mode='lines',                            167                    hoverinfo='none', 168                    yaxis='y2',                    169                    ) 170                )171                172                fig.layout.yaxis2.title="Shares Traded"173 174 175            else:176                fig.add_trace(                               177                    go.Scatter(                          178                    x=dfSentiment['timestamp'][0:i],179                    y=dfSentiment[stock_select][0:i],180                    name=stock_select,181                    mode='lines',                            182                    hoverinfo='none', 183                    yaxis='y2',                    184                    ) 185                )186 187                fig.layout.yaxis2.title='Stock Price ($USD)'188 189 190            fig.layout.xaxis.title='Timestamp'191 192            # write the figure throught streamlit193            st.write(fig)194 195 196        st.markdown('### Detailed Data View')197        st.dataframe(dfSentiment.iloc[:, 1:][0:i])198        time.sleep(1)199