Why is `DataFrame.append` Deprecated and How Do I Add Rows to a Pandas DataFrame?

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

When attempting to add a dictionary to a DataFrame object, users may encounter the error message "AttributeError: 'DataFrame' object has no attribute 'append'." While DataFrame was previously equipped with the append method, it was removed in pandas version 2.0.

Solution

To append data to a DataFrame, use the concat method instead:

df = pd.concat([df, pd.DataFrame([new_row])], ignore_index=True)

Alternative Solution

If the index is a RangeIndex, the loc attribute can also be used:

df.loc[len(df)] = new_row # Note: Only use with a RangeIndex!

Why the Change?

The append method was removed because it was an inefficient operation, especially when repeated. Unlike list.append, which operates in-place, DataFrame's append created a new DataFrame. This made repeated insertion operations quadratic in time complexity.

Best Practices for Repeated Insertion

Instead of using append or concat repeatedly, collect the new items into a list and convert them to a DataFrame at the end of the loop. Then, concatenate the new DataFrame to the original.

lst = []

for new_row in items_generation_logic:
    lst.append(new_row)

# create extension
df_extended = pd.DataFrame(lst, columns=['A', 'B', 'C'])

# concatenate to original
out = pd.concat([df, df_extended])

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