append a dataframe with a new line in python

To append a new row to an existing dataframe in pandas, you can use the append method along with the loc attribute.

First, create a dictionary with the data for the new row. For example:


main.py
new_data = {'Name': 'John Doe', 'Age': 35, 'City': 'New York'}
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Then, convert the dictionary to a dataframe using the pd.DataFrame.from_dict() method:


main.py
new_row = pd.DataFrame.from_dict(new_data, orient='columns')
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Finally, append the new row to the existing dataframe using the append method:


main.py
existing_df = existing_df.append(new_row, ignore_index=True)
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The ignore_index=True parameter ensures that the index of the appended row is unique and does not overlap with existing indices. The append method returns a new dataframe with the appended row, so you need to assign it back to the original dataframe variable.

Here's an example that puts these steps together:


main.py
import pandas as pd

# Example existing dataframe
existing_data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30], 'City': ['London', 'Paris']}
existing_df = pd.DataFrame(data=existing_data)

# New row to append
new_data = {'Name': 'John Doe', 'Age': 35, 'City': 'New York'}
new_row = pd.DataFrame.from_dict(new_data, orient='columns')

# Append the new row to the existing dataframe
existing_df = existing_df.append(new_row, ignore_index=True)

print(existing_df)
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This will output:


main.py
       Name  Age      City
0     Alice   25    London
1       Bob   30     Paris
2  John Doe   35  New York
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