Scikit-learn : Input contains NaN, infinity or a value too large for dtype ('float64')
<p>I'm using Python scikit-learn for simple linear regression on data obtained from csv.</p>

<pre><code>reader = pandas.io.parsers.read_csv("data/all-stocks-cleaned.csv")
stock = np.array(reader)

openingPrice = stock[:, 1]
closingPrice = stock[:, 5]

print((np.min(openingPrice)))
print((np.min(closingPrice)))
print((np.max(openingPrice)))
print((np.max(closingPrice)))

peningPriceTrain, openingPriceTest, closingPriceTrain, closingPriceTest = \
    train_test_split(openingPrice, closingPrice, test_size=0.25, random_state=42)


openingPriceTrain = np.reshape(openingPriceTrain,(openingPriceTrain.size,1))

openingPriceTrain = openingPriceTrain.astype(np.float64, copy=False)
# openingPriceTrain = np.arange(openingPriceTrain, dtype=np.float64)

closingPriceTrain = np.reshape(closingPriceTrain,(closingPriceTrain.size,1))
closingPriceTrain = closingPriceTrain.astype(np.float64, copy=False)

openingPriceTest = np.reshape(openingPriceTest,(openingPriceTest.size,1))
closingPriceTest = np.reshape(closingPriceTest,(closingPriceTest.size,1))

regression = linear_model.LinearRegression()

regression.fit(openingPriceTrain, closingPriceTrain)

predicted = regression.predict(openingPriceTest)
</code></pre>

<p>The min and max values are showed as 0.0
0.6
41998.0
2593.9</p>

<p>Yet I'm getting this error ValueError: <code>Input contains NaN, infinity or a value too large for dtype('float64').</code></p>

<p>How should I remove this error?
Because from the above result it is true that it doesn't contain infinites or Nan values.</p>

<p>What's the solution for this?</p>

<p>Edit: all-stocks-cleaned.csv is avaliabale at <a href="http://www.sharecsv.com/s/cb31790afc9b9e33c5919cdc562630f3/all-stocks-cleaned.csv" rel="noreferrer">http://www.sharecsv.com/s/cb31790afc9b9e33c5919cdc562630f3/all-stocks-cleaned.csv</a></p>