How to Efficiently Add a New Column to a Pandas DataFrame?

How to Add a New Column to an Existing DataFrame

Problem Statement

Given a DataFrame with indexed rows, you want to incorporate an additional column without modifying the existing data. For instance, given the DataFrame:

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<div class="code" style="position:relative; padding:0px; margin:0px;"><pre class="brush:php;toolbar:false">      a         b         c         d

Copy after login

2 0.671399 0.101208 -0.181532 0.241273
3 0.446172 -0.243316 0.051767 1.577318
5 0.614758 0.075793 -0.451460 -0.012493

Add a column named 'e' with the following values:

<br>0   -0.335485<br>1   -1.166658<br>2   -0.385571<br>dtype: float64<br>

Solution

Edit 2017

The most efficient method, as suggested by @Alexander and indicated in the comments, is to use the assign method:

df1 = df1.assign(e=pd.Series(np.random.randn(sLength)).values)

Edit 2015

Some users reported encountering the SettingWithCopyWarning with the original code. However, the code remains functional in the current pandas version, 0.16.1.

sLength = len(df1['a'])

df1['e'] = pd.Series(np.random.randn(sLength), index=df1.index)

Original Answer

Create a Series using the original indexes of df1 and assign it to the new column:

df1['e'] = pd.Series(np.random.randn(sLength), index=df1.index)

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