Home Backend Development Python Tutorial Why Does pandas DataFrame Throw an AttributeError: 'DataFrame' object has no attribute 'append'?

Why Does pandas DataFrame Throw an AttributeError: 'DataFrame' object has no attribute 'append'?

Dec 07, 2024 pm 12:11 PM

Why Does pandas DataFrame Throw an AttributeError: 'DataFrame' object has no attribute 'append'?

Error: 'DataFrame' Object Has No Attribute 'append'

When attempting to append a dictionary to a DataFrame object, the following error may arise:

AttributeError: 'DataFrame' object has no attribute 'append'

Despite the apparent existence of the "append" method in DataFrame, this issue can be resolved by understanding its recent removal.

Reason for Removal

In pandas 2.0, the "append" method was deprecated and eventually removed due to its problematic nature. Users often attempted to mimic Python list behavior by employing "append" in a loop, leading to inefficiencies. "append" in pandas does not modify the original DataFrame but creates a new one, resulting in an O(n) complexity for repeated insertions.

Alternative Solutions

To append a dictionary to a DataFrame, two alternative methods are recommended:

1. Pandas Concatenation (concat)

df = pd.concat([df, pd.DataFrame([new_row])], ignore_index=True)
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This method combines the original DataFrame with the new row as a DataFrame.

2. Pandas Loc (only for RangeIndex)

df.loc[len(df)] = new_row # only use with a RangeIndex!
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This method adds the new row by setting it at the next available index in the DataFrame. Note that it only works when the DataFrame has a RangeIndex.

Appending Multiple Rows Effectively

If multiple rows need to be appended, consider the following approach:

  1. Collect the new rows in a list.
  2. Create a DataFrame from the list.
  3. Concatenate the new DataFrame to the original DataFrame.

This ensures efficient appending while avoiding the overhead of repetitive "append" or "concat" operations.

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