Finance Skillpath Capstone Project in Python

orroy7 · May 6, 2020, 12:29pm

Hey guys!

I’ve just finished the capstone project for finance:
https://www.codecademy.com/paths/finance-python/tracks/analyze-financial-data-with-python-capstone/modules/analyze-financial-data-with-python-capstone/informationals/analyze-financial-data-with-python-capstone

Here’s my code, would love to hear thoughts and improvements!

github.com

Quaniful/Codeacademy-Projects/blob/master/codeacademy-capstone-finance.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Welcome to my Codeacademy finance path Capstone project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 922,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pandas_datareader.data as web\n",
    "import datetime\n",
    "import quandl\n",

This file has been truncated. show original

Thank you

jsheldon2009 · May 6, 2020, 10:54pm

Hi Team,
I need help with getting the X axis. It needs to show dates, but I can’t figure out how to convert it.
Do I use datetime? Mathplotlib? Pandas?
This dataset was pulled from Yahoo Finance for the past 5 years from 5/6/2015 to 5/5/2020 for the following ticker symbols:
Disney
Facebook
Netflix
GM
MDT
Any help would be greatly appreciate.

import numpy as np
import matplotlib as plt
from matplotlib import pyplot as plt
from datetime import datetime
import pandas as pd
import pandas_datareader.data as web
start = datetime(2015, 5, 6)
end = datetime(2020, 5, 5)
stock_data = web.get_data_yahoo(symbols, start, end)

disney = pd.read_csv(“DIS.csv”)
Facebook = pd.read_csv(“FB.csv”)
netflix = pd.read_csv(“NFLX.csv”)
GM = pd.read_csv(“GM.csv”)
mdt = pd.read_csv(“mdt.csv”)

DIS = ‘DIS.csv’
FB = ‘FB.csv’
NFLX = ‘NFLX.csv’
GM = ‘GM.csv’
MDT = ‘MDT.csv’

disney_stock = pd.read_csv(DIS)
disney_stock_closing_prices = disney_stock[‘Adj Close’]
disney_stock_closing_prices.plot(label=‘Disney’)
Facebook_stock = pd.read_csv(FB)
Facebook_stock_closing_prices = Facebook_stock[‘Adj Close’]
Facebook_stock_closing_prices.plot(label=‘Facebook’)
netflix_stock = pd.read_csv(NFLX)
netflix_stock_closing_prices = netflix_stock[‘Adj Close’]
netflix_stock_closing_prices.plot(label=‘Netflix’)
GM_stock = pd.read_csv(GM)
GM_stock_closing_prices = GM_stock[‘Adj Close’]
GM_stock_closing_prices.plot(label=‘GM’)
MDT_stock = pd.read_csv(MDT)
MDT_stock_closing_prices = MDT_stock[‘Adj Close’]
MDT_stock_closing_prices.plot(label=‘Medtronics’)
plt.xlabel(“Date”)
plt.ylabel(“Adjusted Closing Price”)
plt.title(“Tech Stocks Adjusted Price Over Time”)
plt.legend()
columns=[‘Date’, ‘Adj Close’]
plt.plot(columns)
plt.show()
disney_stock_closing_prices
Facebook_stock_closing_prices
netflix_stock_closing_prices
GM_stock_closing_prices
MDT_stock_closing_prices

#print(disney)
#print(Facebook)
#print(netflix)
#print(GM)
#print(mdt)