eps comparison graph ready

Elaborated_Data/eps_comparison.csv

@@ -0,0 +1,361 @@
+,Ticker,quarter,epsDifferential
+0,AAPL,2022-06-30,3.448275862068969
+1,AAPL,2022-09-30,1.5748031496063006
+2,AAPL,2022-12-31,-3.092783505154642
+3,AAPL,2023-03-31,6.2937062937062995
+4,ABBV,2022-06-30,1.8126888217522674
+5,ABBV,2022-09-30,2.5210084033613533
+6,ABBV,2022-12-31,1.1235955056179785
+7,ABBV,2023-03-31,0.0
+8,ABT,2022-06-30,26.54867256637169
+9,ABT,2022-09-30,22.34042553191489
+10,ABT,2022-12-31,11.956521739130432
+11,ABT,2023-03-31,4.040404040404044
+12,ACN,2022-05-31,-2.1052631578947385
+13,ACN,2022-08-31,1.1673151750972859
+14,ACN,2022-11-30,5.841924398625427
+15,ACN,2023-02-28,7.599999999999999
+16,ADBE,2022-05-31,1.2084592145015116
+17,ADBE,2022-08-31,2.1021021021020974
+18,ADBE,2022-11-30,2.85714285714286
+19,ADBE,2023-02-28,3.2608695652173822
+20,AMAT,2022-07-31,8.379888268156419
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+22,AMAT,2023-01-31,5.181347150259061
+23,AMAT,2023-04-30,8.69565217391304
+24,AMGN,2022-06-30,5.681818181818182
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+27,AMGN,2023-03-31,3.3766233766233738
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+38,AVGO,2022-10-31,1.653696498054474
+39,AVGO,2023-01-31,2.2772277227722815
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+47,BAC,2023-03-31,14.634146341463413
+48,BDX,2022-06-30,6.400000000000006
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+50,BDX,2022-12-31,11.194029850746261
+51,BDX,2023-03-31,4.379562043795607
+52,BIDU,2022-06-30,51.38888888888891
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+54,BIDU,2022-12-31,12.060301507537687
+55,BIDU,2023-03-31,29.213483146067404
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+57,BMY,2022-09-30,8.7431693989071
+58,BMY,2022-12-31,5.813953488372099
+59,BMY,2023-03-31,4.060913705583748
+60,CAT,2022-06-30,5.647840531561474
+61,CAT,2022-09-30,25.0
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+63,CAT,2023-03-31,29.894179894179906
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+72,CMCSA,2022-06-30,10.989010989010985
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+75,CMCSA,2023-03-31,12.195121951219525
+76,CME,2022-06-30,2.072538860103629
+77,CME,2022-09-30,2.061855670103095
+78,CME,2022-12-31,2.1276595744680873
+79,CME,2023-03-31,2.1097046413502034
+80,COST,2022-05-31,0.3300330033003377
+81,COST,2022-08-31,0.9615384615384623
+82,COST,2022-11-30,-1.2861736334405156
+83,COST,2023-02-28,2.8037383177570048
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+125,EXC,2022-09-30,7.1428571428571495
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+127,EXC,2023-03-31,6.060606060606049
+128,FDX,2022-05-31,0.14577259475218346
+129,FDX,2022-08-31,-33.07392996108949
+130,FDX,2022-11-30,12.765957446808523
+131,FDX,2023-02-28,24.908424908424916
+132,FIS,2022-06-30,1.1695906432748548
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+160,IBM,2022-06-30,1.7621145374449354
+161,IBM,2022-09-30,2.25988700564972
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+163,IBM,2023-03-31,7.936507936507943
+164,INTC,2022-06-30,-58.57142857142858
+165,INTC,2022-09-30,84.37499999999999
+166,INTC,2022-12-31,-50.0
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+355,WMT,2023-04-30,11.363636363636356
+356,XOM,2022-06-30,10.695187165775385
+357,XOM,2022-09-30,17.414248021108182
+358,XOM,2022-12-31,3.3434650455927013
+359,XOM,2023-03-31,9.266409266409276

backend/api/past_performance.py

@@ -0,0 +1,17 @@
+import os
+import pandas as pd
+import numpy as np
+from scraper.top100_extractor import programming_crime_list
+from typing import Optional
+
+DF_EPS_PATH: str = os.path.join(os.path.dirname(__file__), '..', '..', 'Elaborated_Data', 'eps_comparison.csv')
+
+
+def get_eps_comp(tickers: list[str]) -> list[dict]:
+    df = pd.read_csv(DF_EPS_PATH)
+    ticker_series = pd.Series(tickers)
+    df = df.loc[df['Ticker'].isin(ticker_series), :] \
+        .rename(columns={"epsDifferential": "quarterlyDifferential", "Ticker": "ticker"}) \
+        .reset_index(drop=True)
+    df = df.pivot(index='quarter', columns='ticker', values='quarterlyDifferential').reset_index(drop=False)
+    return df.replace({ np.nan: None }).to_dict('records')

indexer/comparison_indexer.py

@@ -37,6 +37,23 @@ def concatenate_eps():
     
     eps_df.to_csv('Elaborated_Data/eps_quarterly_bar_chart.csv')
 
+def eps_comparison():
+    # Read earnings csv
+    eps_comp_df = pd.DataFrame()
+
+    for ticker in programming_crime_list:
+        earnings = pd.read_csv(f'Companies_Data/{ticker}_Data/{ticker}earnings.csv')
+        earnings = earnings[['symbol', 'epsActual', 'epsEstimate', 'quarter']]
+        earnings['epsDifferential'] = ((earnings['epsActual'] - earnings['epsEstimate']) / earnings['epsEstimate']) * 100  
+        earnings = earnings.drop(columns=['epsActual', 'epsEstimate'])
+        earnings = earnings.rename(columns={'symbol': 'Ticker'})
+        eps_comp_df = pd.concat([eps_comp_df, earnings], ignore_index=True, axis=0)
+
+    # Save the earnings df to Elaborated_Data
+    eps_comp_df.to_csv(f'Elaborated_Data/eps_comparison.csv')
+
+    return earnings
 if __name__ == '__main__':
     concatenate_price_history()
     concatenate_eps()
+    eps_comparison()

stockingly-frontend/src/api/index.ts

@@ -44,6 +44,11 @@ export interface Eps {
 
 }
 
+export interface EpsComp {
+    [ticker: string]: string | number; // really just number
+    quarter: string;
+}
+
 export const getCompanies = (tickers?: string[]): Promise<Company[]> =>
     fetch(BACKEND_URL + '/companies' + (tickers ? ('/' + tickers.join('/')) : ''))
         .then(r => r.json())
@@ -61,6 +66,8 @@ export const getPriceHistory = (tickers: string[]): Promise<PriceHistory[]> =>
 export const getBalanceSheet = (tickers: string[]): Promise<BalanceSheet[]> =>
     fetch(BACKEND_URL + '/assets_debts/' + tickers.join('/')).then(r=>r.json())
 
-
 export const getEps = (tickers: string[]): Promise<Eps[]> =>
     fetch(BACKEND_URL + '/eps/' + tickers.join('/').toUpperCase()).then(r => r.json())
+
+export const getEpsComp = (tickers: string[]): Promise<EpsComp[]> =>
+    fetch(BACKEND_URL + '/eps_comp/' + tickers.join('/').toUpperCase()).then(r => r.json())

stockingly-frontend/src/components/EpsComparisonChart.vue

@@ -0,0 +1,112 @@
+<template>
+    <v-row>
+      <v-col cols="12">
+        <v-card>
+          <v-card-item>
+            <v-card-title>Past Performance</v-card-title>
+          </v-card-item>
+          <v-card-text>
+            <v-skeleton-loader class="chart-loader" v-if="epsCompData.loading" />
+            <ag-charts-vue class="chart" v-else :options="options" />
+          </v-card-text>
+        </v-card>
+      </v-col>
+    </v-row>
+  </template>
+   
+  <script setup lang="ts">
+  import { EpsComp, getEpsComp } from '@/api';
+  import { defineLoader } from '@/api/loader';
+  import { DateTime } from 'luxon';
+  import { AgAxisLabelFormatterParams } from 'ag-charts-community';
+  import { roundTo } from 'round-to';
+  import { onMounted, computed } from 'vue';
+  import { AgChartsVue } from 'ag-charts-vue3';
+  
+  const renderer = (params: any) => ({
+    title: params.title,
+    content: DateTime.fromMillis(params.xValue).toFormat('yyyy-MM') + ': ' + roundTo(params.yValue, 4) + '%',
+  });
+  
+  const props = defineProps<{
+    tickers: string[],
+    colors: string[]
+  }>();
+  
+  const getTickerColor = (ticker: string) => props.colors[props.tickers.indexOf(ticker)];
+  
+  const epsCompData = defineLoader<EpsComp[]>(() => getEpsComp(props.tickers));
+  
+  const options = computed(() => {
+    if (epsCompData.loading) return null;
+  
+    return {
+      theme: 'ag-material',
+      data: epsCompData.data?.map(e => ({ ...e, quarter: Date.parse(e.quarter) })),
+      series: props.tickers.map((t: string) => ({
+        xKey: 'quarter',
+        type: 'line',
+        yKey: t,
+        yName: t,
+        fill: getTickerColor(t),
+        stroke: getTickerColor(t),
+        tooltip: { renderer: renderer },
+        highlightStyle: {
+          item: { fillOpacity: 0 },
+          series: { enabled: false }
+        },
+      })),
+      axes: [
+        {
+          type: 'category',
+          position: 'bottom',
+          label: {
+            autoRotate: true,
+            autoRotateAngle: 335,
+            formatter: (params: any) => {
+              return DateTime.fromMillis(parseInt(params.value)).toFormat('yyyy-MM');
+            }
+          },
+          gridStyle: [
+            {
+              lineDash: [Infinity],
+            }, {
+                lineDash: [Infinity],
+            }
+          ],
+        },
+        {
+          type: 'number',
+          position: 'left',
+            label: {
+                format: '$~s',
+                formatter: (params: AgAxisLabelFormatterParams) => {
+                params?.formatter?.(params.value)
+                return params.value + '%';
+                }
+            },
+          gridStyle: [{
+            lineDash: [Infinity],
+          }, {
+              lineDash: [Infinity],
+          }],
+          crossLines:[
+            {
+                type: 'range',
+                value: 0,
+                lineDash: [6, 3],
+                stroke: 'black',
+            }
+          ]
+        },
+      ],
+      legend: {
+        position: 'bottom',
+      }
+    };
+  });
+  
+  onMounted(() => {
+    epsCompData.load();
+  });
+  </script>

stockingly-frontend/src/views/Comparison.vue

@@ -36,6 +36,9 @@
       <v-col cols="12">
         <eps-chart :colors="colors" :tickers="tickers" />
       </v-col>
+      <v-col cols="12">
+        <eps-comparison-chart :colors="colors" :tickers="tickers" />
+      </v-col>
     </v-row>
   </v-container>
 </template>
@@ -66,6 +69,7 @@ import EmployeesChart from '@/components/EmployeesChart.vue';
 import BalanceSheet from '@/components/BalanceSheet.vue';
 import EpsChart from '@/components/EpsChart.vue';
 import StockPrice from '@/components/StockPrice.vue';
+import EpsComparisonChart from '@/components/EpsComparisonChart.vue';
 
 const route = useRoute();
 const router = useRouter();

stockingly.py

@@ -10,6 +10,7 @@ import sys
 import subprocess
 from typing import Optional
 from backend.api.eps import get_eps
+from backend.api.past_performance import get_eps_comp
 
 ROOT_DIR: str = os.path.dirname(__file__)
 
@@ -63,6 +64,11 @@ def eps(tickers: Optional[str]) -> object:
     return jsonify(get_eps(tickers.split('/')))
 
 
+@app.route('/eps_comp/<path:tickers>', methods=['GET'])
+def eps_comp(tickers: Optional[str]) -> object:
+    return jsonify(get_eps_comp(tickers.split('/')))
+
+
 if __name__ == '__main__':
     if len(sys.argv) < 2 or sys.argv[1] != 'no-frontend':
         build_frontend()