title: Binarizing pandas dataframe column
body: <pre><code>mean radius mean texture    mean perimeter  mean area   mean smoothness mean compactness    mean concavity  mean concave points mean symmetry   mean fractal dimension  ... worst texture   worst perimeter worst area  worst smoothness    worst compactness   worst concavity worst concave points    worst symmetry  worst fractal dimension classification
  0   17.99   10.38   122.80  1001.0  0.11840 0.27760 0.3001  0.14710 0.2419  0.07871 ... 17.33   184.60  2019.0  0.1622  0.6656  0.7119  0.2654  0.4601  0.11890 0
  1   20.57   17.77   132.90  1326.0  0.08474 0.07864 0.0869  0.07017 0.1812  0.05667 ... 23.41   158.80  1956.0  0.1238  0.1866  0.2416  0.1860  0.2750  0.08902 0
  2   19.69   21.25   130.00  1203.0  0.10960 0.15990 0.1974  0.12790 0.2069  0.05999 ... 25.53   152.50  1709.0  0.1444  0.4245  0.4504  0.2430  0.3613  0.08758 0
  3   11.42   20.38   77.58   386.1   0.14250 0.28390 0.2414  0.10520 0.2597  0.09744 ... 26.50   98.87   567.7   0.2098  0.8663  0.6869  0.2575  0.6638  0.17300 0
  4   20.29   14.34   135.10  1297.0  0.10030 0.13280 0.1980  0.10430 0.1809  0.05883 ... 16.67   152.20  1575.0  0.1374  0.2050  0.4000  0.1625  0.2364  0.07678 0
  </code></pre>
  
  <p>Suppose I have a pandas dataFrame that looks like above.
  I want to binarize (change to 0 or 1) of the <code>mean radius</code> column if it the value is higher than <code>12.0</code>.</p>
  
  <p>What I've tried is</p>
  
  <p><code>data_df.loc[data_df["mean radius"] &gt; 12.0] = 0</code></p>
  
  <p>But this gave me a weird result.</p>
  
  <p>How can I solve this?</p>