How Can I Combine Pandas DataFrame Columns to Create a New Period Column?

Combining Columns to Create a New Period Column in a Pandas DataFrame

In pandas, you may encounter instances where you need to combine columns to create a new column, often representing a combination of their values. Consider a scenario where you have a DataFrame with columns 'Year' and 'quarter,' as shown below:

Year  quarter
2000       q2
2001       q3

You want to create a new column named 'period' that combines the values from the 'Year' and 'quarter' columns, resulting in a DataFrame that looks like this:

Year  quarter  period
2000       q2  2000q2
2001       q3  2001q3

Combining String Columns

If both 'Year' and 'quarter' are strings, you can concatenate them directly using the ' ' operator:

df["period"] = df["Year"] + df["quarter"]

Combining Non-String Columns

If either 'Year' or 'quarter' is not a string, you need to convert it to a string first, as demonstrated below:

df["period"] = df["Year"].astype(str) + df["quarter"]

NOTE: Be cautious of NaN values when performing this operation.

Combining Multiple String Columns Using agg

If you have multiple string columns to combine, you can use the 'agg' function to apply a join operation:

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

In this case, '-' is the separator used to concatenate the columns.

By following these steps, you can effectively combine columns in a pandas DataFrame to create a new column that represents a combination of their values.

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