append rows to a pandas dataframe without making a new copy

## Appending Rows to a Pandas DataFrame Efficiently: Avoiding Unnecessary Copies

This tutorial will explore different methods for appending rows to a Pandas DataFrame while minimizing or eliminating unnecessary copies. We'll cover best practices and illustrate them with practical code examples.

**Methods to Avoid Unnecessary Copies**

Here are several techniques to append rows efficiently, avoiding or minimizing copies:

1. **Appending to a List and Concatenating Once:**

This is generally the *most* efficient approach for appending a large number of rows, especially when performance is critical. Instead of appending directly to the DataFrame, you accumulate the new rows in a Python list, and then concatenate the entire list to the DataFrame *once* at the end.



**Explanation:**

* We initialize an empty DataFrame (or use your existing DataFrame).
* `rows_to_append` is a standard Python list. We iterate and create dictionaries representing the new rows. Appending to a list is very fast.
* `pd.DataFrame(rows_to_append)` converts the list of dictionaries into a new DataFrame. This ...

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