title: Python: Adding a row when row iteration in dataframe find letter in string of a column
body: <p>I'm looking for an efficient way of adding a row in an existing dataframe
  when a row iteration find a specific character in a column. this new row is gonna be a copy of the currently iterating row with just a modified value.</p>
  
  <p>Here is an example of what I'm looking for:
  For example with row iteration if object in "string" column contain a "M"
  create a copy of the row just after with 50 added to the value in "Value"
  column</p>
  
  <p>What I have:</p>
  
  <pre><code>        Name               String        Value
  0      name1                 EXAN        100.1
  1      name2                EXAN_        200.2
  2      name3               EXAMPL        300.3 
  3      name4              EXAMPLE        400.4 
  4      name5                 TEST        500.5 
  </code></pre>
  
  <p>What I'm looking for:</p>
  
  <pre><code>        Name               String        Value
  0      name1                 EXAN        100.1
  1      name2                EXAN_        200.2
  2      name3               EXAMPL        300.3
  3      name3               EXAMPL        350.3
  4      name4              EXAMPLE        400.4
  5      name4              EXAMPLE        450.4 
  6      name5                 TEST        500.5 
  </code></pre>
  
  <p>I have tried :</p>
  
  <pre><code>for i, row in df.iterrows():
      if "M" in row['String']:
          df.add_row([row.Name, row.String, row.Value+50])
  </code></pre>
  
  <p>I get:</p>
  
  <pre><code>Traceback (most recent call last):
    File "&lt;stdin&gt;", line 3, in &lt;module&gt;
    File "/usr/local/lib/python2.7/dist-packages/pandas/core/generic.py", line 1843, in __getattr__
      (type(self).__name__, name))
  AttributeError: 'DataFrame' object has no attribute 'add_row'
  </code></pre>
  
  <p>Here some more informations:</p>
  
  <pre><code>&gt;&gt;&gt; df.dtypes
  Name              object
  String            object
  Value             float64
  
  &gt;&gt;&gt; type(df)
  &lt;class 'pandas.core.frame.DataFrame'&gt;
  </code></pre>
  
  <p>Any help would be greatly appreciated</p>