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# Expanding strings vertically in a DataFrame in Pandas

schedule Aug 12, 2023
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local_offer
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To expand strings vertically in Pandas, use the DataFrame's `explode(~)` method.

As an example, consider the following DataFrame:

``` df = pd.DataFrame({"A":["a,b","b,c"],"B":[4,5]})df A B0 a,b 41 b,c 5 ```

# Solution

To split the strings of column `A` by `,`, and then vertically expand the rows:

``` df["A"] = df["A"].str.split(",")df = df.explode("A")df A B0 a 40 b 41 b 51 c 5 ```

# Explanation

Here, we are first splitting the strings of column `A` by `,` using `str.split(",")`:

``` df["A"] = df["A"].str.split(",")df A B0 [a, b] 41 [b, c] 5 ```

Next, we used the `explode(~)` method to let each element of the lists have its own row:

``` df.explode("A") A B0 a 40 b 41 b 51 c 5 ```

# Supplement - resetting the index

Notice how the resulting DataFrame has duplicate indices `[0,0,1,1]`, which is bad practise in Pandas. To reset the index to the default integer index, call `reset_index(drop=True)` like so:

``` df.reset_index(drop=True) A B0 a 41 b 42 b 53 c 5 ```

Here, the parameter `drop=True` is needed - otherwise the current index will become included as a column.

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