Append or Add Row to a Pandas DataFrame

0. How to append a row to a DataFrame?

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1. Make a DataFrame to be Appended

Let's say you have a DataFrame of 3-year history of exam scores.

The codes below create the DataFrame.

import pandas as pd

dict_scores = {'Year' : [2019, 2020, 2021],
               'Math' : [80, 70, 90],
               'History' : [60, 40, 70],
               'Science' : [70, 80, 60]}

df_scores = pd.DataFrame(dict_scores)

 

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One year passed, so you need to update 1 row of the year to the DataFrame.

In 2022,

- Math score is 100.

- History score is 60.

- Science score is 90.

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Use .append() method.

 

Make sure put column elements in lists.

dict_new = {'Year' : [2022],
            'Math' : [100],
            'History' : [60],
            'Science' : [90]}
            
df_new = pd.DataFrame(dict_new)

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If a ValueError like below occurs, check if the element of each column is in list or not.

dict_new = {'Year' : 2022,
            'Math' : 100,
            'History' : 60,
            'Science' : 90}
            
df_new = pd.DataFrame(dict_new)

ValueError: If using all scalar values, you must pass an index

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If the elements are not contained in lists,

add index argument to the pd.DataFrame() method.

df_new = pd.DataFrame(dict_new, index = [0])

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2. Append the New DataFrame to the Old DataFrame.

To append the new DataFrame to old DataFrame, use .append() method.

df_scores.append(df_new)

It will make the result below.

The problem is that the index numbers do not look clean.

0 -> 1 -> 2 -> 0

The last zero(0) should be changed to 3.

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Add ignore_index argument in the .append() method.

df_scores.append(df_new, ignore_index = True)

The argument ignores what the index of the new DataFrame was.

It incorporates the new DataFrame into the order of the old DataFrame.

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Otherwise, you can use .reset_index() method afterwards,

instead of ignore_index argument.

df_scores.append(df_new).reset_index()