Why does the dataframe object have no attribute 'append'?

The reason why a Pandas DataFrame object doesn't have an append attribute is primarily because the append method, as traditionally used with Python lists, is an in-place operation that modifies the original object. DataFrames in Pandas are designed to be immutable for better performance and to avoid unintended side effects.

Instead of append, Pandas offers alternative methods that create a new DataFrame with the added data, thus preserving the original DataFrame. The most common methods are:

1. concat() function: This function from Pandas is the preferred way to combine DataFrames. It can combine DataFrames along rows (axis=0) or columns (axis=1). This function does not modify the existing dataframes; it creates a new dataframe. Example:

import pandas as pd
df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df2 = pd.DataFrame({'A': [5, 6], 'B': [7, 8]})
combined_df = pd.concat([df1, df2])
print(combined_df)

2. loc[] or iloc[] for row-wise addition: To add a row to a DataFrame, you can use loc[] or iloc[]. This method is helpful if you want to add a single row or a DataFrame containing the rows you intend to add. This also creates a new dataframe, it does not change the original dataframe.

import pandas as pd
df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
new_row = pd.DataFrame([{'A': 5, 'B': 6}])
df = pd.concat([df, new_row], ignore_index=True)
print(df)

The above examples shows how to correctly add a new row to a DataFrame. Note that ignore_index=True is added so that the indexing of the new dataframe is correct.

Key Takeaways

• DataFrames in Pandas are designed to be immutable for better performance, which is why methods like append are not part of its design.
• Always use pd.concat() to combine dataframes.
• When adding rows, utilize loc[], iloc[] or a new dataframe with the new rows then use pd.concat() to combine the dataframes.

By understanding these differences, you can avoid common errors when working with Pandas DataFrames and achieve more efficient data manipulation.

Learn more about this