Python: Stock Market Analysis

Cargamos librerias de R y Pyhon

library(reticulate)
library(tidyverse)

import pandas as pd
import yfinance as yf
import datetime
from datetime import date, timedelta
import plotly.graph_objects as go
import plotly.express as px

Configuramos fecha de inicio y fin

today = date.today()
d1 = today.strftime("%Y-%m-%d")
end_date = d1
d2 = date.today() - timedelta(days=365)
d2 = d2.strftime("%Y-%m-%d")
start_date = d2

f'Start: {d2}, End: {d1}'

'Start: 2021-08-28, End: 2022-08-28'

Descargamos los datos de Yahoo Finance

data = yf.download(
  'GOOG',
  start= start_date,
  end= end_date,
  progress= False
)

data["Date"] = data.index
data = data[[
  "Date", "Open", "High", "Low",
  "Close", "Adj Close", "Volume"
]]

data.reset_index(
  drop=True, inplace=True
)

Candlestick Chart

figure = go.Figure(
  data = [go.Candlestick(
    x= data["Date"],
    open= data["Open"],
    high= data["High"],
    low= data["Low"],
    close= data["Close"]
  )]
)
figure.update_layout(
  title= "Google Stock Price",
  xaxis_rangeslider_visible=True
)
#figure.show()

Line Chart

figure = px.line(
  data, x="Date", y="Close",
  title= "Google Close Price"
)
figure.update_xaxes(
  rangeslider_visible=True
)
#figure.show()

Time period selectors

figure = px.line(
  data, x="Date",y="Close",
  title="Time period selectors"
)
figure.update_xaxes(
  rangeselector=dict(
    buttons=list([
      dict(count=1, label="1m", step="month", stepmode="backward"),
      dict(count=6, label="6m", step="month", stepmode="backward"),
      dict(count=3, label="3m", step="month", stepmode="backward"),
      dict(count=1, label="1y", step="year", stepmode="backward"),
      dict(step="all")
    ])
  )
)
#figure.show()