How Can I Insert a List into a Specific Cell in a Python Pandas Dataframe?

Insert List into a Cell in Python Pandas Dataframe

Inserting a list into a specific cell in a pandas dataframe can be a tricky task. Let's explore the various approaches and potential issues based on the given example:

Original Problem:

A dataframe 'df' with the following structure:

    A  B
0  12  NaN
1  23  NaN

and a list 'abc' containing ['foo', 'bar']. The goal is to insert this list into cell 1B.

Efforts:

1. df.ix[1,'B'] = abc: Throws a ValueError due to unequal length of keys and values.
2. df.ix[1,'B'] = [abc]: Inserts a list containing the 'abc' list instead of individual elements.
3. df.ix[1,'B'] = ', '.join(abc): Inserts a string instead of a list.
4. df.ix[1,'B'] = [', '.join(abc)]: Inserts a one-element list containing the joined string.

Solution:

The deprecated set_value method has been replaced with at. Using at guarantees setting a single value:

<code class="python">df.at[1, 'B'] = ['foo', 'bar']</code>

Additional Considerations:

• Ensure that the target column has dtype=object to accommodate list insertion.
• The same approach can be applied to insert lists into cells containing integer or string values.
• However, when inserting a list into a column containing mixed data types (integer and string), a ValueError may occur. This can be resolved by converting the column to dtype=object before insertion.

Updated Example:

Inserting the 'abc' list into df2.loc[1,'B'] and df3.loc[1,'B']:

<code class="python">df2 = pd.DataFrame({
    'A': [12],
    'B': [nan],
    'C': ['bla']
})

df3 = pd.DataFrame({
    'A': [12],
    'B': [nan],
    'C': ['bla bla'],
    'D': [['item1', 'item2'], [11, 12, 13]]
})

df2.loc[1, 'B'] = ['foo', 'bar']
df3.loc[1, 'B'] = ['foo', 'bar']</code>

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