Question

How do I add a row to a DataFrame?

Answer and Explanation

Adding a row to a Pandas DataFrame in Python can be achieved using several methods. Here are the most common approaches:

1. Using `loc`: The `.loc` method is primarily used for label-based indexing, but it also allows you to add a new row if the index label doesn't exist. It's generally recommended for clarity and avoiding potential errors with implicit integer indexing.

- Example:

import pandas as pd

data = {'Name': ['Alice', 'Bob'],
       'Age': [25, 30],
       'City': ['New York', 'London']}

df = pd.DataFrame(data)

new_row = {'Name': 'Charlie', 'Age': 35, 'City': 'Paris'}
df.loc[len(df)] = new_row
print(df)

Explanation: Here, `len(df)` computes the length of the DataFrame which serves as the new index label. The new row values are inserted.

2. Using `append` (Not Recommended): The `append` method can be used to add a new row, but this is an older, less efficient method. It creates a new DataFrame instead of modifying the existing one in-place. It's generally discouraged.

- Example (Avoid Using):

import pandas as pd

data = {'Name': ['Alice', 'Bob'],
       'Age': [25, 30],
       'City': ['New York', 'London']}

df = pd.DataFrame(data)

new_row = pd.Series({'Name': 'Charlie', 'Age': 35, 'City': 'Paris'})
df = df.append(new_row, ignore_index=True)
print(df)

Explanation: `ignore_index=True` is used to ensure that the resulting DataFrame has a new integer index. However, the operation copies all the data and that is inefficient.

3. Using `DataFrame.concat`: When you have multiple rows to add or need to combine dataframes you should use `DataFrame.concat` which is more performant than repeated use of `loc`.

- Example:

import pandas as pd

data = {'Name': ['Alice', 'Bob'],
       'Age': [25, 30],
       'City': ['New York', 'London']}

df = pd.DataFrame(data)

new_rows = pd.DataFrame([{'Name': 'Charlie', 'Age': 35, 'City': 'Paris'}, {'Name': 'Diana', 'Age': 28, 'City': 'Rome'}])
df = pd.concat([df, new_rows], ignore_index = True)
print(df)

Explanation: `pd.concat` is used to efficiently concatenate two DataFrames, one existing and one new, into one.

Recommendation:

- The recommended method to add a single row is using `df.loc[len(df)] = new_row` because it's clear and efficient. Use `.concat` for multiple rows or for concatenating other DataFrames.

By understanding and using these methods, you can efficiently add rows to DataFrames within your Pandas projects.

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