Splitting Tuple Columns in Pandas Dataframes
In Pandas, dataframes may contain columns that hold tuples as their elements. To efficiently extract and manipulate the individual elements of these tuples, a common task is to split them into separate columns. This article provides a detailed demonstration of how to achieve this split.
Consider the following dataframe sample:
<code class="python">import pandas as pd df = pd.DataFrame({'a': [1, 2], 'b': [(1, 2), (3, 4)]})</code>
The 'b' column contains tuples, and we want to split them into 'b1' and 'b2' columns. To do this, we can utilize the pd.DataFrame(col.tolist()) method applied to the 'b' column:
<code class="python">df[['b1', 'b2']] = pd.DataFrame(df['b'].tolist(), index=df.index)</code>
This operation creates a new dataframe with 'b1' and 'b2' columns, where each tuple element from the original 'b' column is assigned to its corresponding 'b1' and 'b2' column.
The resulting dataframe would now look like this:
<code class="python">print(df) a b b1 b2 0 1 (1, 2) 1 2 1 2 (3, 4) 3 4</code>
Now, the dataframe has the individual tuple elements split into separate columns, enabling convenient access and manipulation.
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