How can i Parse my Date Column after getting Nasdaq dataset from yahoofinance in Python

Question

I got a live data from yahoo finance as follows:

ndx = yf.Ticker("NDX")

# get stock info

print(ndx.info)

# get historical market data
hist = ndx.history(period="1825d")

I downloaded it and Exported to CSV file as follows:
 #Download stock data then export as CSV

df = yf.download("NDX", start="2016-01-01", end="2022-11-02")
df.to_csv('ndx.csv')

Viewed the data as follows:
df = pd.read_csv("ndx.csv")
df

The data was displayed as seen in the picture:

THE PROBLEM….
Anytime i tried to use the Date column it throws an error as KeyError ‘Date’. here is my Auto Arima Model and the error thrown. Please Help.

ERROR THROWN

i want to be able to use the Date column. i tried Parsing the Date column but throw the same error. i will need help parsing the data first so as to convert Date to day format or string. Thanks

Asked By: Emy

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Source

Answer 1

Always great to see people trying to learn financial analysis:

Before I get into the solution I just want to remind you to make sure you put your imports in your question (yfinance isn’t always aliased as yf). Also make sure you type or copy/paste your code so that we can easily grab it and run it!
So, I am going to assume the variable "orig_df" is just the call to pd.read_csv(‘ndx.csv’) since that’s what the screenshot looks like.
Firstly, always check your data types of your columns after reading in the file:
(assuming you are using Jupyter)

orig_df = pd.read_csv(‘ndx.csv’)
orig_df.dtypes

Date is an object, which just means string in pandas.
if orig_df is the actual call to yf.ticker(…), then "Date" is your index, so it is does not act like a column.

How to fix and Run:

from statsmodels.api import tsa
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime as dt, timedelta    

orig_df = pd.read_csv('ndx.csv', parse_dates=['Date'], index_col=0)

model = tsa.arima.ARIMA(np.log(orig_df['Close']), order=(10, 1, 10))
fitted = model.fit()
fc = fitted.get_forecast(5)
fc = (fc.summary_frame(alpha=0.05))
fc_mean = fc['mean']
fc_lower = fc['mean_ci_lower']
fc_upper = fc['mean_ci_upper']

orig_df.iloc[-50:,:].plot(y='Close', title='Nasdaq 100 Closing price', figsize=(10, 6))

# call orig_df.index[-1] for most recent trading day, not just today
future_5_days = [orig_df.index[-1] + timedelta(days=x) for x in range(5)]
plt.plot(future_5_days, np.exp(fc_mean), label='mean_forecast', linewidth=1.5)
plt.fill_between(future_5_days, 
                 np.exp(fc_lower), 
                 np.exp(fc_upper), 
                 color='b', alpha=.1, label='95% confidence')
plt.title('Nasdaq 5 Days Forecast')
plt.legend(loc='upper left', fontsize=8)
plt.show()

Answered By: finman69

How can i Parse my Date Column after getting Nasdaq dataset from yahoofinance in Python

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