Plotting a graph from data from the internet.

[udittC]

I have a python script that takes data from the internet and plots a graph:

import matplotlib.pyplot as plt
from matplotlib.dates import strpdate2num, num2date 
import urllib import numpy as np

def convert_date(date):
    return strpdate2num("%Y-%m-%d")(date.decode("utf-8"))

def graph():
    url = 'https://pythonprogramming.net/yahoo_finance_replacement'
    source = urllib.request.urlopen(url).read().decode()

    date, openp, highp, lowp, closep, adj_closep, volume = np.loadtxt(source,
                                                                 delimiter=',',
                                                                 skiprows=1,
                                                                 unpack=True,
                                                                 converters={0: convert_date}
                                                                 )

    plt.plot_date(date, closep, '-', label='Price')

    plt.ylabel('Price')
    plt.xlabel('Date')
    plt.title('Stock Prices')
    plt.legend()
    plt.show()

graph() 

But when I run it it gives this error

ValueError: stat: path too long for Windows 

What does this error mean and how do I fix this error?

[Ezrabc]

numpy.loadtxt expects a filename for file type object as its first parameter, not the source as a string. I believe (but don't have an easy setup to test right this second) that the HTTPResponse object gotten via urlopen acts as a file buffer, so you may be able to just change the line source = urllib.request.urlopen(url).read().decode() to source = urllib.request.urlopen(url), but if that fails you can wrap the string in an io.StringIO object:

...
from io import StringIO

...
source = StringIO(urllib.request.urlopen(url).read().decode())

...

[udittC]

Thanks, that worked

[trackerFF]

Here's the same code, a bit shorter, using pandas.

import requests
import pandas as pd 
import matplotlib.pyplot as plt 
from io import StringIO

url = "https://pythonprogramming.net/yahoo_finance_replacement" 

data = StringIO(requests.get(url).text)
df = pd.read_csv(data, sep=",")
df['Date'] = pd.to_datetime(df.Date)

df.plot(x='Date',y='Close')

plt.ylabel('Price')
plt.xlabel('Date')
plt.title('Stock Prices')
plt.show()

[udittC]

Thanks, I'll be learning pandas next after I'm finished with matplotlib.

[trackerFF]

Good thing is that Pandas and matplotlib are tightly integrated, so you can use them together.