Merging/Append a DataFrame with itself results in new columns
<p>I have the following merge operation:</p>

<pre><code>data_static = pandas.merge(data_static, data_output[['TICKER', 'DATE', 'rolling_vola_40', 'rolling_vola_80', 'f_rolling_vola_40', 'f_rolling_vola_80', 'rolling_vola_prev_annum', 'rolling_vola_post_annum']], how='left', on=['TICKER', 'DATE'])
</code></pre>

<p>My problem now is that this results into the following headers:</p>

<pre><code>;YEAR;DATE;TICKER;LONG_COMP_NAME;ISSUER_INDUSTRY;INDUSTRY_SECTOR;COUNTRY;ACCOUNTING_STANDARD;ACCOUNTING_STANDARD_OVERRIDE;EQY_FUND_CRNCY;INDEX;DATE_PREV;DATE_NEXT;rolling_vola_40_x;rolling_vola_80_x;f_rolling_vola_40_x;f_rolling_vola_80_x;rolling_vola_prev_annum_x;rolling_vola_post_annum_x;rolling_vola_40_y;rolling_vola_80_y;f_rolling_vola_40_y;f_rolling_vola_80_y;rolling_vola_prev_annum_y;rolling_vola_post_annum_y
</code></pre>

<p>I want the data to go into the same column, like this:</p>

<pre><code>;YEAR;DATE;TICKER;LONG_COMP_NAME;ISSUER_INDUSTRY;INDUSTRY_SECTOR;COUNTRY;ACCOUNTING_STANDARD;ACCOUNTING_STANDARD_OVERRIDE;EQY_FUND_CRNCY;INDEX;DATE_PREV;DATE_NEXT;rolling_vola_40;rolling_vola_80;f_rolling_vola_40;f_rolling_vola_80;rolling_vola_prev_annum;rolling_vola_post_annum;
</code></pre>

<p>So instead of going next to each other like this (example):</p>

<pre><code>    TICKER   Val1_x   Val2_x   Val3_x   Val1_y   Val2_y   Val3_y
    A        80       6        1        NaN      NaN      NaN
    B        NaN      NaN      NaN      10       12       14
</code></pre>

<p>I want them to be like this:</p>

<pre><code>    TICKER   Val1     Val2     Val3
    A        80       6        1
    B        10       12       14
</code></pre>

<p>My merge joins on the columns <code>TICKER</code> and <code>DATE</code>, so don't be confused by the sample data.</p>