initial commit

README.md

@@ -1,8 +1,8 @@
 ---
 title: TeslaInSpace
 emoji: 😻
-colorFrom: yellow
-colorTo: purple
+colorFrom: purple
+colorTo: yellow
 sdk: streamlit
 sdk_version: 1.10.0
 app_file: app.py

app.py

@@ -0,0 +1,207 @@
+# author sridhar iyer
+
+from datetime import date
+from datetime import datetime
+import re
+
+import numpy as np  
+import pandas as pd 
+from PIL import Image
+import plotly.express as px  
+import plotly.graph_objects as go
+import streamlit as st  
+import time
+
+from plotly.subplots import make_subplots
+
+# Read CSV file into pandas and extract timestamp data
+dfSentiment = pd.read_csv('sentiment_data.csv')### YOUR LINE OF CODE HERE
+dfSentiment['timestamp'] = [datetime.strptime(dt, '%Y-%m-%d') for dt in dfSentiment['timestamp'].tolist()]
+
+# Multi-select columns to build chart
+col_list = dfSentiment.columns.values.tolist()### YOUR LINE OF CODE HERE #### Extract columns into a list
+
+r_sentiment = re.compile(".*sentiment")
+sentiment_cols = list(filter(r_sentiment.match, col_list))### YOUR LINE OF CODE HERE
+
+r_post = re.compile(".*post")
+post_list = list(filter(r_post.match, col_list))### YOUR LINE OF CODE HERE
+
+r_perc= re.compile(".*perc")
+perc_list = list(filter(r_perc.match, col_list))
+
+r_close = re.compile(".*close")
+close_list = list(filter(r_close.match, col_list))
+
+r_volume = re.compile(".*volume")
+volume_list = list(filter(r_volume.match, col_list))
+
+sentiment_cols = sentiment_cols + post_list
+stocks_cols = close_list + volume_list ### YOUR LINE OF CODE HERE
+
+# Config for page
+st.set_page_config(
+    page_title= 'TSLA Sentiment Analyzer Using Huggingface and StreamLit App',### YOUR LINE OF CODE HERE
+    page_icon='✅',
+    layout='wide',
+)
+
+with st.sidebar:
+    # FourthBrain logo to sidebar
+    fourthbrain_logo = Image.open('./images/fourthbrain_logo.png')
+    st.image([fourthbrain_logo], width=300)
+
+    # Date selection filters
+    start_date_filter = st.date_input(
+        ### YOUR LINE OF CODE HERE
+        'Start Date',
+        min(dfSentiment['timestamp']),
+        min_value=min(dfSentiment['timestamp']),
+        max_value=max(dfSentiment['timestamp'])
+        )
+        
+
+    end_date_filter = st.date_input(
+        'End Date',
+        max(dfSentiment['timestamp']),
+        min_value=min(dfSentiment['timestamp']),
+        max_value=max(dfSentiment['timestamp'])
+        )
+
+    sentiment_select = st.selectbox('Select Sentiment Data', sentiment_cols) ### YOUR LINE OF CODE HERE
+    stock_select = st.selectbox('Select Stock Data', stocks_cols) ### YOUR LINE OF CODE HERE
+
+# Banner with TSLA and Reddit images
+tsla_logo = Image.open('./images/tsla_logo.png')### YOUR LINE OF CODE HERE
+reddit_logo = Image.open('./images/reddit_logo.png')
+st.image([tsla_logo, reddit_logo], width=200)
+
+# dashboard title
+### YOUR LINE OF CODE HERE
+st.title('TSLA Dashboard')
+
+## dataframe filter
+# start date
+dfSentiment = dfSentiment[dfSentiment['timestamp'] >= datetime(start_date_filter.year, start_date_filter.month, start_date_filter.day)]
+    
+# end date
+dfSentiment = dfSentiment[dfSentiment['timestamp'] <= datetime(end_date_filter.year, end_date_filter.month, end_date_filter.day)]
+dfSentiment = dfSentiment.reset_index(drop=True)
+
+
+# creating a single-element container
+placeholder = st.empty()### YOUR LINE OF CODE HERE
+
+# near real-time / live feed simulation
+for i in range(1, len(dfSentiment)-1):
+
+    # creating KPIs
+    last_close =  dfSentiment['close'][i]
+    last_close_lag1 = dfSentiment['close'][i-1]
+    last_sentiment = dfSentiment['sentiment_score'][i] ### YOUR LINE OF CODE HERE
+    last_sentiment_lag1 = dfSentiment['sentiment_score'][i-1]### YOUR LINE OF CODE HERE
+
+
+    with placeholder.container():
+
+        # create columns
+        kpi1, kpi2 = st.columns(2)
+
+        # fill in those three columns with respective metrics or KPIs
+        kpi1.metric(
+            label='Sentiment Score',
+            value=round(last_sentiment, 3),
+            delta=round(last_sentiment_lag1, 3),
+        )
+        
+        kpi2.metric(
+            label='Last Closing Price',
+            ### YOUR LINE 1 OF CODE HERE
+            ### YOUR LINE 2 OF CODE HERE
+            value=round(last_close),
+            delta=round(last_close - last_close_lag1)
+        )
+        
+
+        # create two columns for charts
+        fig_col1, fig_col2 = st.columns(2)
+        
+        with fig_col1:
+            # Add traces
+            fig=make_subplots(specs=[[{"secondary_y":True}]])
+
+
+            fig.add_trace(                               
+                go.Scatter(                          
+                x=dfSentiment['timestamp'][0:i],
+                y=dfSentiment[sentiment_select][0:i],
+                name=sentiment_select,
+                mode='lines',                            
+                hoverinfo='none',                        
+                )              
+            )
+
+            if sentiment_select.startswith('perc') == True:
+                yaxis_label = '% Change Sentiment'
+
+            elif sentiment_select in sentiment_cols:
+                yaxis_label = 'Sentiment Score'
+
+            elif sentiment_select in post_list:
+                yaxis_label = 'Volume'
+
+            fig.layout.yaxis.title=yaxis_label
+                                          
+            if stock_select.startswith('perc') == True:
+                fig.add_trace(                               
+                    go.Scatter(                          
+                    x=dfSentiment['timestamp'][0:i],
+                    y=dfSentiment[stock_select][0:i],
+                    name=stock_select,
+                    mode='lines',                            
+                    hoverinfo='none', 
+                    yaxis='y2',                    
+                    ) 
+                )
+                fig.layout.yaxis2.title='% Change Stock Price ($US)'
+            
+            elif stock_select == 'volume':
+                fig.add_trace(                               
+                    go.Scatter(                          
+                    x=dfSentiment['timestamp'][0:i],
+                    y=dfSentiment[stock_select][0:i],
+                    name=stock_select,
+                    mode='lines',                            
+                    hoverinfo='none', 
+                    yaxis='y2',                    
+                    ) 
+                )
+                
+                fig.layout.yaxis2.title="Shares Traded"
+
+
+            else:
+                fig.add_trace(                               
+                    go.Scatter(                          
+                    x=dfSentiment['timestamp'][0:i],
+                    y=dfSentiment[stock_select][0:i],
+                    name=stock_select,
+                    mode='lines',                            
+                    hoverinfo='none', 
+                    yaxis='y2',                    
+                    ) 
+                )
+
+                fig.layout.yaxis2.title='Stock Price ($USD)'
+
+
+            fig.layout.xaxis.title='Timestamp'
+
+            # write the figure throught streamlit
+            ### YOUR LINE OF CODE HERE
+            st.write(fig)
+
+
+        st.markdown('### Detailed Data View')
+        st.dataframe(dfSentiment.iloc[:, 1:][0:i])
+        time.sleep(1)

requirements.txt

@@ -0,0 +1,11 @@
+loguru==0.6.0
+matplotlib==3.5.2
+numpy==1.23.0
+pandas==1.4.2
+Pillow==9.2.0
+plotly==5.9.0
+praw==7.6.0
+pydantic==1.9.1
+requests==2.28.1
+streamlit==1.10.0
+transformers==4.19.4

sentiment_data.csv

@@ -0,0 +1,9 @@
+,timestamp,counter,close,volume,sentiment_score,close_lag1,perc_change_close,sentiment_score_lag1,perc_change_sentiment,sentiment_SMA3mo
+1,2022-07-02,361,0.0,,0.8339518653719049,681.78998,-1.0,0.9120607078075409,-0.0856399598919222,0.0
+2,2022-07-03,289,0.0,,0.8884219457121456,0.0,0.0,0.8339518653719049,0.06531561664647095,0.8781448396305306
+3,2022-07-04,784,0.0,,0.919358315212386,0.0,0.0,0.8884219457121456,0.034821707916548865,0.8805773754321455
+4,2022-07-05,4,699.20001,28193700,0.9892416596412659,0.0,inf,0.919358315212386,0.07601317492052678,0.9323406401885991
+5,2022-07-06,289,695.20001,23951200,0.9044164594481973,699.20001,-0.0057208237168074405,0.9892416596412659,-0.08574770316873759,0.937672144767283
+6,2022-07-07,1,0.0,,0.8769211769104004,695.20001,-1.0,0.9044164594481973,-0.03040113019899295,0.9235264319999544
+7,2022-07-08,169,0.0,,0.9258403640526992,0.0,0.0,0.8769211769104004,0.055785158837938685,0.9023926668037657
+8,2022-07-09,324,0.0,,0.9318263298935361,0.0,0.0,0.9258403640526992,0.006465440558925727,0.9115292902855452