title: pandas dataframe fillna() not working?
body: <p>I have a data set in which I am performing a principal components analysis (PCA). I get a <code>ValueError</code> message when I try to transform the data. Below is some of the code:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  import matplotlib as mpl
  from sklearn.preprocessing import StandardScaler
  from sklearn.decomposition import PCA as sklearnPCA
  
  data = pd.read_csv('test.csv',header=0)
  X = data.ix[:,0:1000].values   # values of 1000 predictor variables
  Y = data.ix[:,1000].values     # values of binary outcome variable
  sklearn_pca = sklearnPCA(n_components=2)
  X_std = StandardScaler().fit_transform(X)
  </code></pre>
  
  <p>It is here that I get the following error message:</p>
  
  <pre class="lang-none prettyprint-override"><code>ValueError: Input contains NaN, infinity or a value too large for dtype('float64').
  </code></pre>
  
  <p>So I then checked whether the original data set had any NaN values:</p>
  
  <pre><code>print(data.isnull().values.any())   # prints True
  data.fillna(0)                      # replace NaN values with 0
  print(data.isnull().values.any())   # prints True
  </code></pre>
  
  <p>I don't understand why <code>data.isnull().values.any()</code> is still printing <code>True</code> even after I replaced the NaN values with 0.</p>