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plurals

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13761574
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2012-12-07T10:48:58.003
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2012-12-07T10:55:44.973
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Body
You are looking for <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.apply.html?highlight=apply#pandas.DataFrame.apply" rel="noreferrer"><code>apply</code></a> (<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.merge.html?highlight=merge#pandas.DataFrame.merge" rel="noreferrer"><code>merge</code></a> is like a database join.): <pre><code>In [1]: from pandas import DataFrame In [2]: df = DataFrame([[1,11,2012],[1,10,2012]], columns=['day','month','year']) In [3]: df Out[3]: day month year 0 1 11 2012 1 1 10 2012 In [4]: df.apply(lambda row: str(row['day'])+'/'+str(row['month'])+'/'+str(row['year']), axis=1) Out[4]: 0 1/11/2012 1 1/10/2012 </code></pre> The <code>axis=1</code> part means you are selecting columns rather than row. If you wanted to give a specific date you could use datetime: <pre><code>In [5]: import datetime In [6]: df.apply(lambda row: datetime.datetime(row['year'],row['month'],row['day']), axis=1) Out[6]: 0 2012-11-01 00:00:00 1 2012-10-01 00:00:00 </code></pre> You can add these as columns in you dataframe as follows: <pre><code>In [7]: df['new_date'] = df.apply(lambda row: str(row['day'])+'/'+str(row['month'])+'/'+str(row['year']), axis=1) In [8]: df Out[8]: day month year new_date 0 1 11 2012 1/11/2012 1 1 10 2012 1/10/2012 </code></pre> . It's worth noting that pandas has an easy way to <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_csv.html" rel="noreferrer"><code>parse_dates</code> when reading as a csv</a>.
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1. This table or related slice is empty.
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1. POCombining rows in DataFrame
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1. USAndy Hayden
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1. USAndy Hayden
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1. POCombining rows in DataFrame
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