<h2>Concatenating Columns for a New Period Column</h2>

<h3>Problem Statement:</h3>

Consider a Pandas dataframe with columns named "Year" and "quarter", as shown below:

<pre>
Year quarter
2000 q2
2001 q3
</pre>

The objective is to create a new column called "period" by combining the "Year" and "quarter" columns to obtain the following result:

<pre>
Year quarter period
2000 q2 2000q2
2001 q3 2001q3
</pre>

<h3>Solution:</h3>

To concatenate string columns in Python, one can directly use the "+" operator:

<pre>
df["period"] = df["Year"].astype(str) + df["quarter"]
</pre>

Note that in Python 3, it is necessary to convert the "Year" column to string before performing the concatenation, as shown in the above example using astype(str).

If one or both of the columns are not of string type, this conversion step is crucial to avoid unexpected results.

<h3>Additional Options:</h3>

For concatenating multiple string columns, Pandas provides a convenient agg function:

<pre>
df['period'] = df[['Year', 'quarter', ...]].agg('-'.join, axis=1)
</pre>

Here, '-' represents the separator string used to join the column values. This method is particularly useful when dealing with multiple string columns.