Create New Columns by Calculating the Columns that Already Exists

1. Calculate the columns directly to add a new column

There is a DataFrame scores of different subject from 2019 to 2022.

You can do various calculations directly by the columns.

 

Below is the codes for the DataFrame.

dict_scores = {'Year' : [2019, 2020, 2021, 2022],
               'Math' : [80, 70, 90, 100],
               'History' : [60, 40, 70, 60],
               'Science' : [70, 80, 60, 90]}
               
df_scores = pd.DataFrame(dict_scores)

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2. Sum up each row

You want to sum up the scores by each year.

df_scores['Math'] + df_scores['History'] + df_scores['Science']

 

It will return a series of the score sums.

Not only the addition, you can execute subtraction, multiplying, and division.

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If you want to add the series to the right end of the DataFrame,

df_scores['Sum'] = df_scores['Math'] + df_scores['History'] + df_scores['Science']
df_scores

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3. Get the average of each row

If you want to add a column of the average score by each year,

df_scores['Sum'] = (df_scores['Math'] + df_scores['History'] + df_scores['Science']) / 3
df_scores

Even though the 3 as denominator is a numeric, not a series or a DataFrame,

It can process calculation of DataFrames.

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In order to calculate a whole column,

the new data or array has to be in the same type with the elements in the column.